Sample records for network database final
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Inferring Network Controls from Topology Using the Chomp Database
2015-12-03
AFRL-AFOSR-VA-TR-2016-0033 INFERRING NETWORK CONTROLS FROM TOPOLOGY USING THE CHOMP DATABASE John Harer DUKE UNIVERSITY Final Report 12/03/2015...INFERRING NETWORK CONTROLS FROM TOPOLOGY USING THE CHOMP DATABASE 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-10-1-0436 5c. PROGRAM ELEMENT NUMBER 6...area of Topological Data Analysis (TDA) and it’s application to dynamical systems. The role of this work in the Complex Networks program is based on
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Guide on Data Models in the Selection and Use of Database Management Systems. Final Report.
ERIC Educational Resources Information Center
Gallagher, Leonard J.; Draper, Jesse M.
A tutorial introduction to data models in general is provided, with particular emphasis on the relational and network models defined by the two proposed ANSI (American National Standards Institute) database language standards. Examples based on the network and relational models include specific syntax and semantics, while examples from the other…
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Report on Approaches to Database Translation. Final Report.
ERIC Educational Resources Information Center
Gallagher, Leonard; Salazar, Sandra
This report describes approaches to database translation (i.e., transferring data and data definitions from a source, either a database management system (DBMS) or a batch file, to a target DBMS), and recommends a method for representing the data structures of newly-proposed network and relational data models in a form suitable for database…
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Functional Interaction Network Construction and Analysis for Disease Discovery.
Wu, Guanming; Haw, Robin
2017-01-01
Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.
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Knowledge representation in metabolic pathway databases.
Stobbe, Miranda D; Jansen, Gerbert A; Moerland, Perry D; van Kampen, Antoine H C
2014-05-01
The accurate representation of all aspects of a metabolic network in a structured format, such that it can be used for a wide variety of computational analyses, is a challenge faced by a growing number of researchers. Analysis of five major metabolic pathway databases reveals that each database has made widely different choices to address this challenge, including how to deal with knowledge that is uncertain or missing. In concise overviews, we show how concepts such as compartments, enzymatic complexes and the direction of reactions are represented in each database. Importantly, also concepts which a database does not represent are described. Which aspects of the metabolic network need to be available in a structured format and to what detail differs per application. For example, for in silico phenotype prediction, a detailed representation of gene-protein-reaction relations and the compartmentalization of the network is essential. Our analysis also shows that current databases are still limited in capturing all details of the biology of the metabolic network, further illustrated with a detailed analysis of three metabolic processes. Finally, we conclude that the conceptual differences between the databases, which make knowledge exchange and integration a challenge, have not been resolved, so far, by the exchange formats in which knowledge representation is standardized.
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Network-based statistical comparison of citation topology of bibliographic databases
Šubelj, Lovro; Fiala, Dalibor; Bajec, Marko
2014-01-01
Modern bibliographic databases provide the basis for scientific research and its evaluation. While their content and structure differ substantially, there exist only informal notions on their reliability. Here we compare the topological consistency of citation networks extracted from six popular bibliographic databases including Web of Science, CiteSeer and arXiv.org. The networks are assessed through a rich set of local and global graph statistics. We first reveal statistically significant inconsistencies between some of the databases with respect to individual statistics. For example, the introduced field bow-tie decomposition of DBLP Computer Science Bibliography substantially differs from the rest due to the coverage of the database, while the citation information within arXiv.org is the most exhaustive. Finally, we compare the databases over multiple graph statistics using the critical difference diagram. The citation topology of DBLP Computer Science Bibliography is the least consistent with the rest, while, not surprisingly, Web of Science is significantly more reliable from the perspective of consistency. This work can serve either as a reference for scholars in bibliometrics and scientometrics or a scientific evaluation guideline for governments and research agencies. PMID:25263231
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Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective
Gu, Shuo
2017-01-01
With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed. PMID:28690664
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Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective.
Gu, Shuo; Pei, Jianfeng
2017-01-01
With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.
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3D multi-view convolutional neural networks for lung nodule classification
Kang, Guixia; Hou, Beibei; Zhang, Ningbo
2017-01-01
The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context information of lung nodules, and the multi-view strategy has been shown to be useful for improving the performance of 2D CNN in classifying lung nodules. In this paper, we explore the classification of lung nodules using the 3D multi-view convolutional neural networks (MV-CNN) with both chain architecture and directed acyclic graph architecture, including 3D Inception and 3D Inception-ResNet. All networks employ the multi-view-one-network strategy. We conduct a binary classification (benign and malignant) and a ternary classification (benign, primary malignant and metastatic malignant) on Computed Tomography (CT) images from Lung Image Database Consortium and Image Database Resource Initiative database (LIDC-IDRI). All results are obtained via 10-fold cross validation. As regards the MV-CNN with chain architecture, results show that the performance of 3D MV-CNN surpasses that of 2D MV-CNN by a significant margin. Finally, a 3D Inception network achieved an error rate of 4.59% for the binary classification and 7.70% for the ternary classification, both of which represent superior results for the corresponding task. We compare the multi-view-one-network strategy with the one-view-one-network strategy. The results reveal that the multi-view-one-network strategy can achieve a lower error rate than the one-view-one-network strategy. PMID:29145492
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A distributed database view of network tracking systems
NASA Astrophysics Data System (ADS)
Yosinski, Jason; Paffenroth, Randy
2008-04-01
In distributed tracking systems, multiple non-collocated trackers cooperate to fuse local sensor data into a global track picture. Generating this global track picture at a central location is fairly straightforward, but the single point of failure and excessive bandwidth requirements introduced by centralized processing motivate the development of decentralized methods. In many decentralized tracking systems, trackers communicate with their peers via a lossy, bandwidth-limited network in which dropped, delayed, and out of order packets are typical. Oftentimes the decentralized tracking problem is viewed as a local tracking problem with a networking twist; we believe this view can underestimate the network complexities to be overcome. Indeed, a subsequent 'oversight' layer is often introduced to detect and handle track inconsistencies arising from a lack of robustness to network conditions. We instead pose the decentralized tracking problem as a distributed database problem, enabling us to draw inspiration from the vast extant literature on distributed databases. Using the two-phase commit algorithm, a well known technique for resolving transactions across a lossy network, we describe several ways in which one may build a distributed multiple hypothesis tracking system from the ground up to be robust to typical network intricacies. We pay particular attention to the dissimilar challenges presented by network track initiation vs. maintenance and suggest a hybrid system that balances speed and robustness by utilizing two-phase commit for only track initiation transactions. Finally, we present simulation results contrasting the performance of such a system with that of more traditional decentralized tracking implementations.
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Mallik, Saurav; Maulik, Ujjwal
2015-10-01
Gene ranking is an important problem in bioinformatics. Here, we propose a new framework for ranking biomolecules (viz., miRNAs, transcription-factors/TFs and genes) in a multi-informative uterine leiomyoma dataset having both gene expression and methylation data using (statistical) eigenvector centrality based approach. At first, genes that are both differentially expressed and methylated, are identified using Limma statistical test. A network, comprising these genes, corresponding TFs from TRANSFAC and ITFP databases, and targeter miRNAs from miRWalk database, is then built. The biomolecules are then ranked based on eigenvector centrality. Our proposed method provides better average accuracy in hub gene and non-hub gene classifications than other methods. Furthermore, pre-ranked Gene set enrichment analysis is applied on the pathway database as well as GO-term databases of Molecular Signatures Database with providing a pre-ranked gene-list based on different centrality values for comparing among the ranking methods. Finally, top novel potential gene-markers for the uterine leiomyoma are provided. Copyright © 2015 Elsevier Inc. All rights reserved.
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Forensic Carving of Network Packets and Associated Data Structures
2011-01-01
establishment of prior connection activity and services used; identification of other systems present on the system’s LAN or WLAN; geolocation of the...identification of other systems present on the system?s LAN or WLAN; geolocation of the host computer system; and cross-drive analysis. We show that network...Finally, our work in geolocation was assisted by geo- location databases created by companies such as Google (Google Mobile, 2011) and Skyhook
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Interhospital network system using the worldwide web and the common gateway interface.
Oka, A; Harima, Y; Nakano, Y; Tanaka, Y; Watanabe, A; Kihara, H; Sawada, S
1999-05-01
We constructed an interhospital network system using the worldwide web (WWW) and the Common Gateway Interface (CGI). Original clinical images are digitized and stored as a database for educational and research purposes. Personal computers (PCs) are available for data treatment and browsing. Our system is simple, as digitized images are stored into a Unix server machine. Images of important and interesting clinical cases are selected and registered into the image database using CGI. The main image format is 8- or 12-bit Joint Photographic Experts Group (JPEG) image. Original clinical images are finally stored in CD-ROM using a CD recorder. The image viewer can browse all of the images for one case at once as thumbnail pictures; image quality can be selected depending on the user's purpose. Using the network system, clinical images of interesting cases can be rapidly transmitted and discussed with other related hospitals. Data transmission from relational hospitals takes 1 to 2 minutes per 500 Kbyte of data. More distant hospitals (e.g., Rakusai Hospital, Kyoto) takes 1 minute more. The mean number of accesses our image database in a recent 3-month period was 470. There is a total about 200 cases in our image database, acquired over the past 2 years. Our system is useful for communication and image treatment between hospitals and we will describe the elements of our system and image database.
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Web application for detailed real-time database transaction monitoring for CMS condition data
NASA Astrophysics Data System (ADS)
de Gruttola, Michele; Di Guida, Salvatore; Innocente, Vincenzo; Pierro, Antonio
2012-12-01
In the upcoming LHC era, database have become an essential part for the experiments collecting data from LHC, in order to safely store, and consistently retrieve, a wide amount of data, which are produced by different sources. In the CMS experiment at CERN, all this information is stored in ORACLE databases, allocated in several servers, both inside and outside the CERN network. In this scenario, the task of monitoring different databases is a crucial database administration issue, since different information may be required depending on different users' tasks such as data transfer, inspection, planning and security issues. We present here a web application based on Python web framework and Python modules for data mining purposes. To customize the GUI we record traces of user interactions that are used to build use case models. In addition the application detects errors in database transactions (for example identify any mistake made by user, application failure, unexpected network shutdown or Structured Query Language (SQL) statement error) and provides warning messages from the different users' perspectives. Finally, in order to fullfill the requirements of the CMS experiment community, and to meet the new development in many Web client tools, our application was further developed, and new features were deployed.
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Integrated and Applied Curricula Discussion Group and Data Base Project. Final Report.
ERIC Educational Resources Information Center
Wisconsin Univ. - Stout, Menomonie. Center for Vocational, Technical and Adult Education.
A project was conducted to compile integrated and applied curriculum resources, develop databases on the World Wide Web, and encourage networking for high school and technical college educators through an Internet discussion group. Activities conducted during the project include the creation of a web page to guide users to resource banks…
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The NASA Science Internet: An integrated approach to networking
NASA Technical Reports Server (NTRS)
Rounds, Fred
1991-01-01
An integrated approach to building a networking infrastructure is an absolute necessity for meeting the multidisciplinary science networking requirements of the Office of Space Science and Applications (OSSA) science community. These networking requirements include communication connectivity between computational resources, databases, and library systems, as well as to other scientists and researchers around the world. A consolidated networking approach allows strategic use of the existing science networking within the Federal government, and it provides networking capability that takes into consideration national and international trends towards multivendor and multiprotocol service. It also offers a practical vehicle for optimizing costs and maximizing performance. Finally, and perhaps most important to the development of high speed computing is that an integrated network constitutes a focus for phasing to the National Research and Education Network (NREN). The NASA Science Internet (NSI) program, established in mid 1988, is structured to provide just such an integrated network. A description of the NSI is presented.
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NASA Astrophysics Data System (ADS)
Boulanger, Damien; Gautron, Benoit; Thouret, Valérie; Fontaine, Alain
2016-04-01
IAGOS (In-service Aircraft for a Global Observing System) is a European Research Infrastructure which aims at the provision of long-term, regular and spatially resolved in situ observations of the atmospheric composition. IAGOS observation systems are deployed on a fleet of commercial aircraft. The IAGOS database is an essential part of the global atmospheric monitoring network. It contains IAGOS-core data and IAGOS-CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container) data. The IAGOS Database Portal (http://www.iagos.fr, damien.boulanger@obs-mip.fr) is part of the French atmospheric chemistry data center AERIS (http://www.aeris-data.fr). The new IAGOS Database Portal has been released in December 2015. The main improvement is the interoperability implementation with international portals or other databases in order to improve IAGOS data discovery. In the frame of the IGAS project (IAGOS for the Copernicus Atmospheric Service), a data network has been setup. It is composed of three data centers: the IAGOS database in Toulouse; the HALO research aircraft database at DLR (https://halo-db.pa.op.dlr.de); and the CAMS data center in Jülich (http://join.iek.fz-juelich.de). The CAMS (Copernicus Atmospheric Monitoring Service) project is a prominent user of the IGAS data network. The new portal provides improved and new services such as the download in NetCDF or NASA Ames formats, plotting tools (maps, time series, vertical profiles, etc.) and user management. Added value products are available on the portal: back trajectories, origin of air masses, co-location with satellite data, etc. The link with the CAMS data center, through JOIN (Jülich OWS Interface), allows to combine model outputs with IAGOS data for inter-comparison. Finally IAGOS metadata has been standardized (ISO 19115) and now provides complete information about data traceability and quality.
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Advanced telemedicine development
DOE Office of Scientific and Technical Information (OSTI.GOV)
Forslund, D.W.; George, J.E.; Gavrilov, E.M.
1998-12-31
This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of this project was to develop a Java-based, electronic, medical-record system that can handle multimedia data and work over a wide-area network based on open standards, and that can utilize an existing database back end. The physician is to be totally unaware that there is a database behind the scenes and is only aware that he/she can access and manage the relevant information to treat the patient.
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Karbalaei, Reza; Allahyari, Marzieh; Rezaei-Tavirani, Mostafa; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza
2018-01-01
Analysis reconstruction networks from two diseases, NAFLD and Alzheimer`s diseases and their relationship based on systems biology methods. NAFLD and Alzheimer`s diseases are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on relation and same spreading pathways of these two diseases. In addition, they have some similar risk factors, exclusively lifestyle such as feeding, exercises and so on. Therefore, systems biology approach can help to discover their relationship. DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. An R package used to define best centrality method. Finally, based on degree and Betweenness, hubs and bottleneck nodes were defined. Common genes between NAFLD and Alzheimer`s disease were 190 genes that used construct a network with STRING database. The resulting network contained 182 nodes and 2591 edges and comprises from four clusters. Enrichment of these clusters separately lead to carbohydrate metabolism, long chain fatty acid and regulation of JAK-STAT and IL-17 signaling pathways, respectively. Also seven genes selected as hub-bottleneck include: IL6, AKT1, TP53, TNF, JUN, VEGFA and PPARG. Enrichment of these proteins and their first neighbors in network by OMIM database lead to diabetes and obesity as ancestors of NAFLD and AD. Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.
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Zhao, Mingzhu; Wei, Dong-Qing
2013-01-01
The traditional Chinese medicine (TCM), which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM. PMID:23818932
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Caillet, P; Oberlin, P; Monnet, E; Guillon-Grammatico, L; Métral, P; Belhassen, M; Denier, P; Banaei-Bouchareb, L; Viprey, M; Biau, D; Schott, A-M
2017-10-01
Osteoporotic hip fractures (OHF) are associated with significant morbidity and mortality. The French medico-administrative database (SNIIRAM) offers an interesting opportunity to improve the management of OHF. However, the validity of studies conducted with this database relies heavily on the quality of the algorithm used to detect OHF. The aim of the REDSIAM network is to facilitate the use of the SNIIRAM database. The main objective of this study was to present and discuss several OHF-detection algorithms that could be used with this database. A non-systematic literature search was performed. The Medline database was explored during the period January 2005-August 2016. Furthermore, a snowball search was then carried out from the articles included and field experts were contacted. The extraction was conducted using the chart developed by the REDSIAM network's "Methodology" task force. The ICD-10 codes used to detect OHF are mainly S72.0, S72.1, and S72.2. The performance of these algorithms is at best partially validated. Complementary use of medical and surgical procedure codes would affect their performance. Finally, few studies described how they dealt with fractures of non-osteoporotic origin, re-hospitalization, and potential contralateral fracture cases. Authors in the literature encourage the use of ICD-10 codes S72.0 to S72.2 to develop algorithms for OHF detection. These are the codes most frequently used for OHF in France. Depending on the study objectives, other ICD10 codes and medical and surgical procedures could be usefully discussed for inclusion in the algorithm. Detection and management of duplicates and non-osteoporotic fractures should be considered in the process. Finally, when a study is based on such an algorithm, all these points should be precisely described in the publication. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
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Mallik, Saurav; Sen, Sagnik; Maulik, Ujjwal
2016-07-15
Involvement of intrinsically disordered proteins (IDPs) with various dreadful diseases like cancer is an interesting research topic. In order to gain novel insights into the regulation of IDPs, in this article, we perform a transcriptomic analysis of mRNAs (genes) for transcripts encoding IDPs on a human multi-omics prostate carcinoma dataset having both gene expression and methylation data. In this regard, firstly the genes that consist of both the expression and methylation data, and that are corresponding to the cancer-related prostate-tissue-specific disordered proteins of MobiDb database, are selected. We apply standard t-test for determining differentially expressed genes as well as differentially methylated genes. A network having these genes and their targeter miRNAs from Diana Tarbase v7.0 database and corresponding Transcription Factors from TRANSFAC and ITFP databases, is then built. Thereafter, we perform literature search, and KEGG pathway and Gene Ontology analyses using DAVID database. Finally, we report several significant potential gene-markers (with the corresponding IDPs) that have inverse relationship between differential expression and methylation patterns, and that are hub genes of the TF-miRNA-gene network. Copyright © 2016 Elsevier B.V. All rights reserved.
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21SSD: a new public 21-cm EoR database
NASA Astrophysics Data System (ADS)
Eames, Evan; Semelin, Benoît
2018-05-01
With current efforts inching closer to detecting the 21-cm signal from the Epoch of Reionization (EoR), proper preparation will require publicly available simulated models of the various forms the signal could take. In this work we present a database of such models, available at 21ssd.obspm.fr. The models are created with a fully-coupled radiative hydrodynamic simulation (LICORICE), and are created at high resolution (10243). We also begin to analyse and explore the possible 21-cm EoR signals (with Power Spectra and Pixel Distribution Functions), and study the effects of thermal noise on our ability to recover the signal out to high redshifts. Finally, we begin to explore the concepts of `distance' between different models, which represents a crucial step towards optimising parameter space sampling, training neural networks, and finally extracting parameter values from observations.
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A novel deep learning algorithm for incomplete face recognition: Low-rank-recovery network.
Zhao, Jianwei; Lv, Yongbiao; Zhou, Zhenghua; Cao, Feilong
2017-10-01
There have been a lot of methods to address the recognition of complete face images. However, in real applications, the images to be recognized are usually incomplete, and it is more difficult to realize such a recognition. In this paper, a novel convolution neural network frame, named a low-rank-recovery network (LRRNet), is proposed to conquer the difficulty effectively inspired by matrix completion and deep learning techniques. The proposed LRRNet first recovers the incomplete face images via an approach of matrix completion with the truncated nuclear norm regularization solution, and then extracts some low-rank parts of the recovered images as the filters. With these filters, some important features are obtained by means of the binaryzation and histogram algorithms. Finally, these features are classified with the classical support vector machines (SVMs). The proposed LRRNet method has high face recognition rate for the heavily corrupted images, especially for the images in the large databases. The proposed LRRNet performs well and efficiently for the images with heavily corrupted, especially in the case of large databases. Extensive experiments on several benchmark databases demonstrate that the proposed LRRNet performs better than some other excellent robust face recognition methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Case retrieval in medical databases by fusing heterogeneous information.
Quellec, Gwénolé; Lamard, Mathieu; Cazuguel, Guy; Roux, Christian; Cochener, Béatrice
2011-01-01
A novel content-based heterogeneous information retrieval framework, particularly well suited to browse medical databases and support new generation computer aided diagnosis (CADx) systems, is presented in this paper. It was designed to retrieve possibly incomplete documents, consisting of several images and semantic information, from a database; more complex data types such as videos can also be included in the framework. The proposed retrieval method relies on image processing, in order to characterize each individual image in a document by their digital content, and information fusion. Once the available images in a query document are characterized, a degree of match, between the query document and each reference document stored in the database, is defined for each attribute (an image feature or a metadata). A Bayesian network is used to recover missing information if need be. Finally, two novel information fusion methods are proposed to combine these degrees of match, in order to rank the reference documents by decreasing relevance for the query. In the first method, the degrees of match are fused by the Bayesian network itself. In the second method, they are fused by the Dezert-Smarandache theory: the second approach lets us model our confidence in each source of information (i.e., each attribute) and take it into account in the fusion process for a better retrieval performance. The proposed methods were applied to two heterogeneous medical databases, a diabetic retinopathy database and a mammography screening database, for computer aided diagnosis. Precisions at five of 0.809 ± 0.158 and 0.821 ± 0.177, respectively, were obtained for these two databases, which is very promising.
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Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming
2015-04-01
This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate < 0.0005). Furthermore, 16 known glioma related genes were abstracted from Genetic Association Database. After mapping 8,890 DEGs and 16 known glioma related genes to Human Protein Reference Database, a glioma associated protein-protein interaction network (GAPN) was constructed. In addition, 51 sub-networks in GAPN were screened out through Molecular Complex Detection (score ≥ 1), and sub-network 1 was found to have the closest interaction (score = 3). What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value < 0.05) was performed, and DEGs involved in sub-network 1 and 2, such as BRMS1L and CCNA1, were predicted to regulate cell growth, cell cycle, and DNA replication via interacting with known glioma related genes. Finally, the overlaps of DEGs and human essential, housekeeping, tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.
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NASA Astrophysics Data System (ADS)
Li, Ming; Yin, Hongxi; Xing, Fangyuan; Wang, Jingchao; Wang, Honghuan
2016-02-01
With the features of network virtualization and resource programming, Software Defined Optical Network (SDON) is considered as the future development trend of optical network, provisioning a more flexible, efficient and open network function, supporting intraconnection and interconnection of data centers. Meanwhile cloud platform can provide powerful computing, storage and management capabilities. In this paper, with the coordination of SDON and cloud platform, a multi-domain SDON architecture based on cloud control plane has been proposed, which is composed of data centers with database (DB), path computation element (PCE), SDON controller and orchestrator. In addition, the structure of the multidomain SDON orchestrator and OpenFlow-enabled optical node are proposed to realize the combination of centralized and distributed effective management and control platform. Finally, the functional verification and demonstration are performed through our optical experiment network.
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Retinal blood vessel segmentation using fully convolutional network with transfer learning.
Jiang, Zhexin; Zhang, Hao; Wang, Yi; Ko, Seok-Bum
2018-04-26
Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or computer-aided diagnosis systems. In this paper, a supervised method is presented based on a pre-trained fully convolutional network through transfer learning. This proposed method has simplified the typical retinal vessel segmentation problem from full-size image segmentation to regional vessel element recognition and result merging. Meanwhile, additional unsupervised image post-processing techniques are applied to this proposed method so as to refine the final result. Extensive experiments have been conducted on DRIVE, STARE, CHASE_DB1 and HRF databases, and the accuracy of the cross-database test on these four databases is state-of-the-art, which also presents the high robustness of the proposed approach. This successful result has not only contributed to the area of automated retinal blood vessel segmentation but also supports the effectiveness of transfer learning when applying deep learning technique to medical imaging. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Deep neural network features for horses identity recognition using multiview horses' face pattern
NASA Astrophysics Data System (ADS)
Jarraya, Islem; Ouarda, Wael; Alimi, Adel M.
2017-03-01
To control the state of horses in the born, breeders needs a monitoring system with a surveillance camera that can identify and distinguish between horses. We proposed in [5] a method of horse's identification at a distance using the frontal facial biometric modality. Due to the change of views, the face recognition becomes more difficult. In this paper, the number of images used in our THoDBRL'2015 database (Tunisian Horses DataBase of Regim Lab) is augmented by adding other images of other views. Thus, we used front, right and left profile face's view. Moreover, we suggested an approach for multiview face recognition. First, we proposed to use the Gabor filter for face characterization. Next, due to the augmentation of the number of images, and the large number of Gabor features, we proposed to test the Deep Neural Network with the auto-encoder to obtain the more pertinent features and to reduce the size of features vector. Finally, we performed the proposed approach on our THoDBRL'2015 database and we used the linear SVM for classification.
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Leroux, Janette S; Moore, Spencer; Dubé, Laurette
2013-01-01
Recent research has shown the importance of networks in the spread of obesity. Yet, the translation of research on social networks and obesity into health promotion practice has been slow. To review the types of obesity interventions targeting social relational factors. Six databases were searched in January 2013. A Boolean search was employed with the following sets of terms: (1) social dimensions: social capital, cohesion, collective efficacy, support, social networks, or trust; (2) intervention type: intervention, experiment, program, trial, or policy; and (3) obesity in the title or abstract. Titles and abstracts were reviewed. Articles were included if they described an obesity intervention with the social relational component central. Articles were assessed on the social relational factor(s) addressed, social ecological level(s) targeted, the intervention's theoretical approach, and the conceptual placement of the social relational component in the intervention. Database searches and final article screening yielded 30 articles. Findings suggested that (1) social support was most often targeted; (2) few interventions were beyond the individual level; (3) most interventions were framed on behaviour change theories; and (4) the social relational component tended to be conceptually ancillary to the intervention. Theoretically and practically, social networks remain marginal to current interventions addressing obesity.
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Cascade heterogeneous face sketch-photo synthesis via dual-scale Markov Network
NASA Astrophysics Data System (ADS)
Yao, Saisai; Chen, Zhenxue; Jia, Yunyi; Liu, Chengyun
2018-03-01
Heterogeneous face sketch-photo synthesis is an important and challenging task in computer vision, which has widely applied in law enforcement and digital entertainment. According to the different synthesis results based on different scales, this paper proposes a cascade sketch-photo synthesis method via dual-scale Markov Network. Firstly, Markov Network with larger scale is used to synthesise the initial sketches and the local vertical and horizontal neighbour search (LVHNS) method is used to search for the neighbour patches of test patches in training set. Then, the initial sketches and test photos are jointly entered into smaller scale Markov Network. Finally, the fine sketches are obtained after cascade synthesis process. Extensive experimental results on various databases demonstrate the superiority of the proposed method compared with several state-of-the-art methods.
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South American foF2 database using genetic algorithms
NASA Astrophysics Data System (ADS)
Gularte, Erika; Bilitza, Dieter; Carpintero, Daniel; Jaen, Juliana
2016-07-01
We present the first step towards a new database of the ionospheric parameter foF2 for the South American region. The foF2 parameter, being the maximum of the ionospheric electronic density profile and its main sculptor, is of great interest not only in atmospheric studies but also in the realm of radio propagation. Due to its importance, its large variability and the difficulty to model it in time and space, it was the subject of an intense study since decades ago. The current databases, used by the IRI (International Reference Ionosphere) model, and based on Fourier expansions, has been built in the 60s from the available ionosondes at that time; therefore, it is still short of South American data. The main goal of this work is to upgrade the database, incorporating the now available data compiled by the RAPEAS (Red Argentina para el Estudio de la Atmósfera Superior, Argentine Network for the Study of the Upper Atmosphere) network. Also, we developed an algorithm to study the foF2 variability, based on the modern technique of genetic algorithms, which has been successfully applied on other disciplines. One of the main advantages of this technique is its ability in working with many variables and with unfavorable samples. The results are compared with the IRI databases, and improvements to the latter are suggested. Finally, it is important to notice that the new database is designed so that new available data can be easily incorporated.
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PyPathway: Python Package for Biological Network Analysis and Visualization.
Xu, Yang; Luo, Xiao-Chun
2018-05-01
Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.
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NASA Astrophysics Data System (ADS)
Dai, Shao-Xing; Li, Wen-Xing; Han, Fei-Fei; Guo, Yi-Cheng; Zheng, Jun-Juan; Liu, Jia-Qian; Wang, Qian; Gao, Yue-Dong; Li, Gong-Hua; Huang, Jing-Fei
2016-05-01
There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents.
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Dai, Shao-Xing; Li, Wen-Xing; Han, Fei-Fei; Guo, Yi-Cheng; Zheng, Jun-Juan; Liu, Jia-Qian; Wang, Qian; Gao, Yue-Dong; Li, Gong-Hua; Huang, Jing-Fei
2016-05-05
There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents.
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Dai, Shao-Xing; Li, Wen-Xing; Han, Fei-Fei; Guo, Yi-Cheng; Zheng, Jun-Juan; Liu, Jia-Qian; Wang, Qian; Gao, Yue-Dong; Li, Gong-Hua; Huang, Jing-Fei
2016-01-01
There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents. PMID:27145869
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Design of Knowledge Bases for Plant Gene Regulatory Networks.
Mukundi, Eric; Gomez-Cano, Fabio; Ouma, Wilberforce Zachary; Grotewold, Erich
2017-01-01
Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary information and resources, and outline the methods for obtaining data. The second stage consists of designing the schema, which involves defining the entire arrangement of the database in a systematic plan. The third stage is the implementation, defined by actualization of the database by using software according to a predefined schema. The final stage is development, where the database is made available to users in a web-accessible system. The result is a knowledgebase that integrates all the information pertaining to gene regulation, and which is easily expandable and transferable.
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A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases.
Barone, Antonio; Toti, Paolo; Giuca, Maria Rita; Derchi, Giacomo; Covani, Ugo
2015-07-01
In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes. Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved. Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.
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Integrating a local database into the StarView distributed user interface
NASA Technical Reports Server (NTRS)
Silberberg, D. P.
1992-01-01
A distributed user interface to the Space Telescope Data Archive and Distribution Service (DADS) known as StarView is being developed. The DADS architecture consists of the data archive as well as a relational database catalog describing the archive. StarView is a client/server system in which the user interface is the front-end client to the DADS catalog and archive servers. Users query the DADS catalog from the StarView interface. Query commands are transmitted via a network and evaluated by the database. The results are returned via the network and are displayed on StarView forms. Based on the results, users decide which data sets to retrieve from the DADS archive. Archive requests are packaged by StarView and sent to DADS, which returns the requested data sets to the users. The advantages of distributed client/server user interfaces over traditional one-machine systems are well known. Since users run software on machines separate from the database, the overall client response time is much faster. Also, since the server is free to process only database requests, the database response time is much faster. Disadvantages inherent in this architecture are slow overall database access time due to the network delays, lack of a 'get previous row' command, and that refinements of a previously issued query must be submitted to the database server, even though the domain of values have already been returned by the previous query. This architecture also does not allow users to cross correlate DADS catalog data with other catalogs. Clearly, a distributed user interface would be more powerful if it overcame these disadvantages. A local database is being integrated into StarView to overcome these disadvantages. When a query is made through a StarView form, which is often composed of fields from multiple tables, it is translated to an SQL query and issued to the DADS catalog. At the same time, a local database table is created to contain the resulting rows of the query. The returned rows are displayed on the form as well as inserted into the local database table. Identical results are produced by reissuing the query to either the DADS catalog or to the local table. Relational databases do not provide a 'get previous row' function because of the inherent complexity of retrieving previous rows of multiple-table joins. However, since this function is easily implemented on a single table, StarView uses the local table to retrieve the previous row. Also, StarView issues subsequent query refinements to the local table instead of the DADS catalog, eliminating the network transmission overhead. Finally, other catalogs can be imported into the local database for cross correlation with local tables. Overall, it is believe that this is a more powerful architecture for distributed, database user interfaces.
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Risk factors for Apgar score using artificial neural networks.
Ibrahim, Doaa; Frize, Monique; Walker, Robin C
2006-01-01
Artificial Neural Networks (ANNs) have been used in identifying the risk factors for many medical outcomes. In this paper, the risk factors for low Apgar score are introduced. This is the first time, to our knowledge, that the ANNs are used for Apgar score prediction. The medical domain of interest used is the perinatal database provided by the Perinatal Partnership Program of Eastern and Southeastern Ontario (PPPESO). The ability of the feed forward back propagation ANNs to generate strong predictive model with the most influential variables is tested. Finally, minimal sets of variables (risk factors) that are important in predicting Apgar score outcome without degrading the ANN performance are identified.
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Conversion of KEGG metabolic pathways to SBGN maps including automatic layout
2013-01-01
Background Biologists make frequent use of databases containing large and complex biological networks. One popular database is the Kyoto Encyclopedia of Genes and Genomes (KEGG) which uses its own graphical representation and manual layout for pathways. While some general drawing conventions exist for biological networks, arbitrary graphical representations are very common. Recently, a new standard has been established for displaying biological processes, the Systems Biology Graphical Notation (SBGN), which aims to unify the look of such maps. Ideally, online repositories such as KEGG would automatically provide networks in a variety of notations including SBGN. Unfortunately, this is non‐trivial, since converting between notations may add, remove or otherwise alter map elements so that the existing layout cannot be simply reused. Results Here we describe a methodology for automatic translation of KEGG metabolic pathways into the SBGN format. We infer important properties of the KEGG layout and treat these as layout constraints that are maintained during the conversion to SBGN maps. Conclusions This allows for the drawing and layout conventions of SBGN to be followed while creating maps that are still recognizably the original KEGG pathways. This article details the steps in this process and provides examples of the final result. PMID:23953132
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The Accounting Network: How Financial Institutions React to Systemic Crisis
Puliga, Michelangelo; Flori, Andrea; Pappalardo, Giuseppe; Chessa, Alessandro; Pammolli, Fabio
2016-01-01
The role of Network Theory in the study of the financial crisis has been widely spotted in the latest years. It has been shown how the network topology and the dynamics running on top of it can trigger the outbreak of large systemic crisis. Following this methodological perspective we introduce here the Accounting Network, i.e. the network we can extract through vector similarities techniques from companies’ financial statements. We build the Accounting Network on a large database of worldwide banks in the period 2001–2013, covering the onset of the global financial crisis of mid-2007. After a careful data cleaning, we apply a quality check in the construction of the network, introducing a parameter (the Quality Ratio) capable of trading off the size of the sample (coverage) and the representativeness of the financial statements (accuracy). We compute several basic network statistics and check, with the Louvain community detection algorithm, for emerging communities of banks. Remarkably enough sensible regional aggregations show up with the Japanese and the US clusters dominating the community structure, although the presence of a geographically mixed community points to a gradual convergence of banks into similar supranational practices. Finally, a Principal Component Analysis procedure reveals the main economic components that influence communities’ heterogeneity. Even using the most basic vector similarity hypotheses on the composition of the financial statements, the signature of the financial crisis clearly arises across the years around 2008. We finally discuss how the Accounting Networks can be improved to reflect the best practices in the financial statement analysis. PMID:27736865
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The Accounting Network: How Financial Institutions React to Systemic Crisis.
Puliga, Michelangelo; Flori, Andrea; Pappalardo, Giuseppe; Chessa, Alessandro; Pammolli, Fabio
2016-01-01
The role of Network Theory in the study of the financial crisis has been widely spotted in the latest years. It has been shown how the network topology and the dynamics running on top of it can trigger the outbreak of large systemic crisis. Following this methodological perspective we introduce here the Accounting Network, i.e. the network we can extract through vector similarities techniques from companies' financial statements. We build the Accounting Network on a large database of worldwide banks in the period 2001-2013, covering the onset of the global financial crisis of mid-2007. After a careful data cleaning, we apply a quality check in the construction of the network, introducing a parameter (the Quality Ratio) capable of trading off the size of the sample (coverage) and the representativeness of the financial statements (accuracy). We compute several basic network statistics and check, with the Louvain community detection algorithm, for emerging communities of banks. Remarkably enough sensible regional aggregations show up with the Japanese and the US clusters dominating the community structure, although the presence of a geographically mixed community points to a gradual convergence of banks into similar supranational practices. Finally, a Principal Component Analysis procedure reveals the main economic components that influence communities' heterogeneity. Even using the most basic vector similarity hypotheses on the composition of the financial statements, the signature of the financial crisis clearly arises across the years around 2008. We finally discuss how the Accounting Networks can be improved to reflect the best practices in the financial statement analysis.
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NASA Astrophysics Data System (ADS)
Ahn, Sul-Ah; Jung, Youngim
2016-10-01
The research activities of the computational physicists utilizing high performance computing are analyzed by bibliometirc approaches. This study aims at providing the computational physicists utilizing high-performance computing and policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of researchers for high-performance computational physics as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2004-2013. We extracted the author rank in the physics field utilizing high-performance computing by the number of papers published during ten years from 2004. Finally, we drew the co-authorship network for 45 top-authors and their coauthors, and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.
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The global transmission network of HIV-1.
Wertheim, Joel O; Leigh Brown, Andrew J; Hepler, N Lance; Mehta, Sanjay R; Richman, Douglas D; Smith, Davey M; Kosakovsky Pond, Sergei L
2014-01-15
Human immunodeficiency virus type 1 (HIV-1) is pandemic, but its contemporary global transmission network has not been characterized. A better understanding of the properties and dynamics of this network is essential for surveillance, prevention, and eventual eradication of HIV. Here, we apply a simple and computationally efficient network-based approach to all publicly available HIV polymerase sequences in the global database, revealing a contemporary picture of the spread of HIV-1 within and between countries. This approach automatically recovered well-characterized transmission clusters and extended other clusters thought to be contained within a single country across international borders. In addition, previously undescribed transmission clusters were discovered. Together, these clusters represent all known modes of HIV transmission. The extent of international linkage revealed by our comprehensive approach demonstrates the need to consider the global diversity of HIV, even when describing local epidemics. Finally, the speed of this method allows for near-real-time surveillance of the pandemic's progression.
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Liu, Zhi-Ping; Wu, Canglin; Miao, Hongyu; Wu, Hulin
2015-01-01
Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org PMID:26424082
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PROGRESS REPORT ON THE DSSTOX DATABASE NETWORK: NEWLY LAUNCHED WEBSITE, APPLICATIONS, FUTURE PLANS
Progress Report on the DSSTox Database Network: Newly Launched Website, Applications, Future Plans
Progress will be reported on development of the Distributed Structure-Searchable Toxicity (DSSTox) Database Network and the newly launched public website that coordinates and... -
Consistency Analysis of Genome-Scale Models of Bacterial Metabolism: A Metamodel Approach
Ponce-de-Leon, Miguel; Calle-Espinosa, Jorge; Peretó, Juli; Montero, Francisco
2015-01-01
Genome-scale metabolic models usually contain inconsistencies that manifest as blocked reactions and gap metabolites. With the purpose to detect recurrent inconsistencies in metabolic models, a large-scale analysis was performed using a previously published dataset of 130 genome-scale models. The results showed that a large number of reactions (~22%) are blocked in all the models where they are present. To unravel the nature of such inconsistencies a metamodel was construed by joining the 130 models in a single network. This metamodel was manually curated using the unconnected modules approach, and then, it was used as a reference network to perform a gap-filling on each individual genome-scale model. Finally, a set of 36 models that had not been considered during the construction of the metamodel was used, as a proof of concept, to extend the metamodel with new biochemical information, and to assess its impact on gap-filling results. The analysis performed on the metamodel allowed to conclude: 1) the recurrent inconsistencies found in the models were already present in the metabolic database used during the reconstructions process; 2) the presence of inconsistencies in a metabolic database can be propagated to the reconstructed models; 3) there are reactions not manifested as blocked which are active as a consequence of some classes of artifacts, and; 4) the results of an automatic gap-filling are highly dependent on the consistency and completeness of the metamodel or metabolic database used as the reference network. In conclusion the consistency analysis should be applied to metabolic databases in order to detect and fill gaps as well as to detect and remove artifacts and redundant information. PMID:26629901
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Hydroacoustic propagation grids for the CTBT knowledge databaes BBN technical memorandum W1303
DOE Office of Scientific and Technical Information (OSTI.GOV)
J. Angell
1998-05-01
The Hydroacoustic Coverage Assessment Model (HydroCAM) has been used to develop components of the hydroacoustic knowledge database required by operational monitoring systems, particularly the US National Data Center (NDC). The database, which consists of travel time, amplitude correction and travel time standard deviation grids, is planned to support source location, discrimination and estimation functions of the monitoring network. The grids will also be used under the current BBN subcontract to support an analysis of the performance of the International Monitoring System (IMS) and national sensor systems. This report describes the format and contents of the hydroacoustic knowledgebase grids, and themore » procedures and model parameters used to generate these grids. Comparisons between the knowledge grids, measured data and other modeled results are presented to illustrate the strengths and weaknesses of the current approach. A recommended approach for augmenting the knowledge database with a database of expected spectral/waveform characteristics is provided in the final section of the report.« less
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The research of network database security technology based on web service
NASA Astrophysics Data System (ADS)
Meng, Fanxing; Wen, Xiumei; Gao, Liting; Pang, Hui; Wang, Qinglin
2013-03-01
Database technology is one of the most widely applied computer technologies, its security is becoming more and more important. This paper introduced the database security, network database security level, studies the security technology of the network database, analyzes emphatically sub-key encryption algorithm, applies this algorithm into the campus-one-card system successfully. The realization process of the encryption algorithm is discussed, this method is widely used as reference in many fields, particularly in management information system security and e-commerce.
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The Latin American Social Medicine database
Eldredge, Jonathan D; Waitzkin, Howard; Buchanan, Holly S; Teal, Janis; Iriart, Celia; Wiley, Kevin; Tregear, Jonathan
2004-01-01
Background Public health practitioners and researchers for many years have been attempting to understand more clearly the links between social conditions and the health of populations. Until recently, most public health professionals in English-speaking countries were unaware that their colleagues in Latin America had developed an entire field of inquiry and practice devoted to making these links more clearly understood. The Latin American Social Medicine (LASM) database finally bridges this previous gap. Description This public health informatics case study describes the key features of a unique information resource intended to improve access to LASM literature and to augment understanding about the social determinants of health. This case study includes both quantitative and qualitative evaluation data. Currently the LASM database at The University of New Mexico brings important information, originally known mostly within professional networks located in Latin American countries to public health professionals worldwide via the Internet. The LASM database uses Spanish, Portuguese, and English language trilingual, structured abstracts to summarize classic and contemporary works. Conclusion This database provides helpful information for public health professionals on the social determinants of health and expands access to LASM. PMID:15627401
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Sharing Water Data to Encourage Sustainable Choices in Areas of the Marcellus Shale
NASA Astrophysics Data System (ADS)
Brantley, S. L.; Abad, J. D.; Vastine, J.; Yoxtheimer, D.; Wilderman, C.; Vidic, R.; Hooper, R. P.; Brasier, K.
2012-12-01
Natural gas sourced from shales but stored in more permeable formations has long been exploited as an energy resource. Now, however, gas is exploited directly from the low-porosity and low-permeability shale reservoirs through the use of hydrofracturing. Hydrofracturing is not a new technique: it has long been utilized in the energy industry to promote flow of oil and gas from traditional reservoirs. To exploit gas in reservoirs such as the Marcellus shale in PA, hydrofracturing is paired with directional drilling. Such hydrofracturing utilizes large volumes of water to increase porosity in the shale formations at depth. Small concentrations of chemicals are added to the water to improve the formation and maintenance of the fractures. Significant public controversy has developed in response to the use of hydrofracturing especially in the northeastern states underlain by the Marcellus shale where some citizens and scientists question whether shale gas recovery will contaminate local surface and ground waters. Researchers, government agencies, and citizen scientists in Pennsylvania are teaming up to run the ShaleNetwork (www.shalenetwork.org), an NSF-funded research collaboration network that is currently finding, collating, sharing, publishing, and exploring data related to water quality and quantity in areas that are exploiting shale gas. The effort, focussed initially on Pennsylvania, is now developing the ShaleNetwork database that can be accessed through HydroDesktop in the CUAHSI Hydrologic Information System. In the first year since inception, the ShaleNetwork ran a workshop and reached eight conclusions, largely focussed on issues related to the sources, entry, and use of data. First, the group discovered that extensive water data is available in areas of shale gas. Second, participants agreed that the Shale Network team should partner with state agencies and industry to move datasets online. Third, participants discovered that the database allows participants to assess data gaps. Fourth, the team was encouraged to search for data that plug gaps. Fifth, the database should be easily sustained by others long-term if the Shale Network team simplifies the process of uploading data and finds ways to create community buy-in or incentives for data uploads. Sixth, the database itself and the workshops for the database should drive future agreement about analytical protocols. Seventh, the database is already encouraging other groups to publish data online. Finally, a user interface is needed that is easier and more accessible for citizens to use. Overall, it is clear that sharing data is one way to build bridges among decision makers, scientists, and citizens to understand issues related to sustainable development of energy resources in the face of issues related to water quality and quantity.
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The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events
Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.
2010-01-01
The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624
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Network control processor for a TDMA system
NASA Astrophysics Data System (ADS)
Suryadevara, Omkarmurthy; Debettencourt, Thomas J.; Shulman, R. B.
Two unique aspects of designing a network control processor (NCP) to monitor and control a demand-assigned, time-division multiple-access (TDMA) network are described. The first involves the implementation of redundancy by synchronizing the databases of two geographically remote NCPs. The two sets of databases are kept in synchronization by collecting data on both systems, transferring databases, sending incremental updates, and the parallel updating of databases. A periodic audit compares the checksums of the databases to ensure synchronization. The second aspect involves the use of a tracking algorithm to dynamically reallocate TDMA frame space. This algorithm detects and tracks current and long-term load changes in the network. When some portions of the network are overloaded while others have excess capacity, the algorithm automatically calculates and implements a new burst time plan.
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Five years database of landslides and floods affecting Swiss transportation networks
NASA Astrophysics Data System (ADS)
Voumard, Jérémie; Derron, Marc-Henri; Jaboyedoff, Michel
2017-04-01
Switzerland is a country threatened by a lot of natural hazards. Many events occur in built environment, affecting infrastructures, buildings or transportation networks and producing occasionally expensive damages. This is the reason why large landslides are generally well studied and monitored in Switzerland to reduce the financial and human risks. However, we have noticed a lack of data on small events which have impacted roads and railways these last years. This is why we have collect all the reported natural hazard events which have affected the Swiss transportation networks since 2012 in a database. More than 800 roads and railways closures have been recorded in five years from 2012 to 2016. These event are classified into six classes: earth flow, debris flow, rockfall, flood, avalanche and others. Data come from Swiss online press articles sorted by Google Alerts. The search is based on more than thirty keywords, in three languages (Italian, French, German). After verifying that the article relates indeed an event which has affected a road or a railways track, it is studied in details. We get finally information on about sixty attributes by event about event date, event type, event localisation, meteorological conditions as well as impacts and damages on the track and human damages. From this database, many trends over the five years of data collection can be outlined: in particular, the spatial and temporal distributions of the events, as well as their consequences in term of traffic (closure duration, deviation, etc.). Even if the database is imperfect (by the way it was built and because of the short time period considered), it highlights the not negligible impact of small natural hazard events on roads and railways in Switzerland at a national level. This database helps to better understand and quantify this events, to better integrate them in risk assessment.
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Quantin, C; Collin, C; Frérot, M; Besson, J; Cottenet, J; Corneloup, M; Soudry-Faure, A; Mariet, A-S; Roussot, A
2017-10-01
The aim of the REDSIAM network is to foster communication between users of French medico-administrative databases and to validate and promote analysis methods suitable for the data. Within this network, the working group "Mental and behavioral disorders" took an interest in algorithms to identify adult schizophrenia in the SNIIRAM database and inventoried identification criteria for patients with schizophrenia in these databases. The methodology was based on interviews with nine experts in schizophrenia concerning the procedures they use to identify patients with schizophrenia disorders in databases. The interviews were based on a questionnaire and conducted by telephone. The synthesis of the interviews showed that the SNIIRAM contains various tables which allow coders to identify patients suffering from schizophrenia: chronic disease status, drugs and hospitalizations. Taken separately, these criteria were not sufficient to recognize patients with schizophrenia, an algorithm should be based on all of them. Apparently, only one-third of people living with schizophrenia benefit from the longstanding disease status. Not all patients are hospitalized, and coding for diagnoses at the hospitalization, notably for short stays in medicine, surgery or obstetrics departments, is not exhaustive. As for treatment with antipsychotics, it is not specific enough as such treatments are also prescribed to patients with bipolar disorders, or even other disorders. It seems appropriate to combine these complementary criteria, while keeping in mind out-patient care (every year 80,000 patients are seen exclusively in an outpatient setting), even if these data are difficult to link with other information. Finally, the experts made three propositions for selection algorithms of patients with schizophrenia. Patients with schizophrenia can be relatively accurately identified using SNIIRAM data. Different combinations of the selected criteria must be used depending on the objectives and they must be related to an appropriate length of time. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
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Sousa, Filipa L; Parente, Daniel J; Hessman, Jacob A; Chazelle, Allen; Teichmann, Sarah A; Swint-Kruse, Liskin
2016-09-01
The AlloRep database (www.AlloRep.org) (Sousa et al., 2016) [1] compiles extensive sequence, mutagenesis, and structural information for the LacI/GalR family of transcription regulators. Sequence alignments are presented for >3000 proteins in 45 paralog subfamilies and as a subsampled alignment of the whole family. Phenotypic and biochemical data on almost 6000 mutants have been compiled from an exhaustive search of the literature; citations for these data are included herein. These data include information about oligomerization state, stability, DNA binding and allosteric regulation. Protein structural data for 65 proteins are presented as easily-accessible, residue-contact networks. Finally, this article includes example queries to enable the use of the AlloRep database. See the related article, "AlloRep: a repository of sequence, structural and mutagenesis data for the LacI/GalR transcription regulators" (Sousa et al., 2016) [1].
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NASA Astrophysics Data System (ADS)
Ngamga, Eulalie Joelle; Bialonski, Stephan; Marwan, Norbert; Kurths, Jürgen; Geier, Christian; Lehnertz, Klaus
2016-04-01
We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.
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NASA Astrophysics Data System (ADS)
Fuchs, Christian; Poulenard, Sylvain; Perlot, Nicolas; Riedi, Jerome; Perdigues, Josep
2017-02-01
Optical satellite communications play an increasingly important role in a number of space applications. However, if the system concept includes optical links to the surface of the Earth, the limited availability due to clouds and other atmospheric impacts need to be considered to give a reliable estimate of the system performance. An OGS network is required for increasing the availability to acceptable figures. In order to realistically estimate the performance and achievable throughput in various scenarios, a simulation tool has been developed under ESA contract. The tool is based on a database of 5 years of cloud data with global coverage and can thus easily simulate different optical ground station network topologies for LEO- and GEO-to-ground links. Further parameters, like e.g. limited availability due to sun blinding and atmospheric turbulence, are considered as well. This paper gives an overview about the simulation tool, the cloud database, as well as the modelling behind the simulation scheme. Several scenarios have been investigated: LEO-to-ground links, GEO feeder links, and GEO relay links. The key results of the optical ground station network optimization and throughput estimations will be presented. The implications of key technical parameters, as e.g. memory size aboard the satellite, will be discussed. Finally, potential system designs for LEO- and GEO-systems will be presented.
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Lai, Edward Chia-Cheng; Man, Kenneth K C; Chaiyakunapruk, Nathorn; Cheng, Ching-Lan; Chien, Hsu-Chih; Chui, Celine S L; Dilokthornsakul, Piyameth; Hardy, N Chantelle; Hsieh, Cheng-Yang; Hsu, Chung Y; Kubota, Kiyoshi; Lin, Tzu-Chieh; Liu, Yanfang; Park, Byung Joo; Pratt, Nicole; Roughead, Elizabeth E; Shin, Ju-Young; Watcharathanakij, Sawaeng; Wen, Jin; Wong, Ian C K; Yang, Yea-Huei Kao; Zhang, Yinghong; Setoguchi, Soko
2015-11-01
This study describes the availability and characteristics of databases in Asian-Pacific countries and assesses the feasibility of a distributed network approach in the region. A web-based survey was conducted among investigators using healthcare databases in the Asia-Pacific countries. Potential survey participants were identified through the Asian Pharmacoepidemiology Network. Investigators from a total of 11 databases participated in the survey. Database sources included four nationwide claims databases from Japan, South Korea, and Taiwan; two nationwide electronic health records from Hong Kong and Singapore; a regional electronic health record from western China; two electronic health records from Thailand; and cancer and stroke registries from Taiwan. We identified 11 databases with capabilities for distributed network approaches. Many country-specific coding systems and terminologies have been already converted to international coding systems. The harmonization of health expenditure data is a major obstacle for future investigations attempting to evaluate issues related to medical costs.
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Self-organized neural maps of human protein sequences.
Ferrán, E. A.; Pflugfelder, B.; Ferrara, P.
1994-01-01
We have recently described a method based on artificial neural networks to cluster protein sequences into families. The network was trained with Kohonen's unsupervised learning algorithm using, as inputs, the matrix patterns derived from the dipeptide composition of the proteins. We present here a large-scale application of that method to classify the 1,758 human protein sequences stored in the SwissProt database (release 19.0), whose lengths are greater than 50 amino acids. In the final 2-dimensional topologically ordered map of 15 x 15 neurons, proteins belonging to known families were associated with the same neuron or with neighboring ones. Also, as an attempt to reduce the time-consuming learning procedure, we compared 2 learning protocols: one of 500 epochs (100 SUN CPU-hours [CPU-h]), and another one of 30 epochs (6.7 CPU-h). A further reduction of learning-computing time, by a factor of about 3.3, with similar protein clustering results, was achieved using a matrix of 11 x 11 components to represent the sequences. Although network training is time consuming, the classification of a new protein in the final ordered map is very fast (14.6 CPU-seconds). We also show a comparison between the artificial neural network approach and conventional methods of biosequence analysis. PMID:8019421
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Volcanic observation data and simulation database at NIED, Japan (Invited)
NASA Astrophysics Data System (ADS)
Fujita, E.; Ueda, H.; Kozono, T.
2009-12-01
NIED (Nat’l Res. Inst. for Earth Sci. & Disast. Prev.) has a project to develop two volcanic database systems: (1) volcanic observation database; (2) volcanic simulation database. The volcanic observation database is the data archive center obtained by the geophysical observation networks at Mt. Fuji, Miyake, Izu-Oshima, Iwo-jima and Nasu volcanoes, central Japan. The data consist of seismic (both high-sensitivity and broadband), ground deformation (tiltmeter, GPS) and those from other sensors (e.g., rain gauge, gravimeter, magnetometer, pressure gauge.) These data is originally stored in “WIN format,” the Japanese standard format, which is also at the Hi-net (High sensitivity seismic network Japan, http://www.hinet.bosai.go.jp/). NIED joins to WOVOdat and we have prepared to upload our data, via XML format. Our concept of the XML format is 1)a common format for intermediate files to upload into the WOVOdat DB, 2) for data files downloaded from the WOVOdat DB, 3) for data exchanges between observatories without the WOVOdat DB, 4) for common data files in each observatory, 5) for data communications between systems and softwares and 6)a for softwares. NIED is now preparing for (2) the volcanic simulation database. The objective of this project is to support to develop a “real-time” hazard map, i.e., the system which is effective to evaluate volcanic hazard in case of emergency, including the up-to-date conditions. Our system will include lava flow simulation (LavaSIM) and pyroclastic flow simulation (grvcrt). The database will keep many cases of assumed simulations and we can pick up the most probable case as the first evaluation in case the eruption started. The final goals of the both database will realize the volcanic eruption prediction and forecasting in real time by the combination of monitoring data and numerical simulations.
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Structure, function, and control of the human musculoskeletal network
Murphy, Andrew C.; Muldoon, Sarah F.; Baker, David; Lastowka, Adam; Bennett, Brittany; Yang, Muzhi
2018-01-01
The human body is a complex organism, the gross mechanical properties of which are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Here we address this gap in knowledge by utilizing medical databases and mathematical modeling to reveal the organizational structure, predicted function, and neural control of the musculoskeletal system. We constructed a highly simplified whole-body musculoskeletal network in which single muscles connect to multiple bones via both origin and insertion points. We demonstrated that, using this simplified model, a muscle’s role in this network could offer a theoretical prediction of the susceptibility of surrounding components to secondary injury. Finally, we illustrated that sets of muscles cluster into network communities that mimic the organization of control modules in primary motor cortex. This novel formalism for describing interactions between the muscular and skeletal systems serves as a foundation to develop and test therapeutic responses to injury, inspiring future advances in clinical treatments. PMID:29346370
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Exudate detection in color retinal images for mass screening of diabetic retinopathy.
Zhang, Xiwei; Thibault, Guillaume; Decencière, Etienne; Marcotegui, Beatriz; Laÿ, Bruno; Danno, Ronan; Cazuguel, Guy; Quellec, Gwénolé; Lamard, Mathieu; Massin, Pascale; Chabouis, Agnès; Victor, Zeynep; Erginay, Ali
2014-10-01
The automatic detection of exudates in color eye fundus images is an important task in applications such as diabetic retinopathy screening. The presented work has been undertaken in the framework of the TeleOphta project, whose main objective is to automatically detect normal exams in a tele-ophthalmology network, thus reducing the burden on the readers. A new clinical database, e-ophtha EX, containing precisely manually contoured exudates, is introduced. As opposed to previously available databases, e-ophtha EX is very heterogeneous. It contains images gathered within the OPHDIAT telemedicine network for diabetic retinopathy screening. Image definition, quality, as well as patients condition or the retinograph used for the acquisition, for example, are subject to important changes between different examinations. The proposed exudate detection method has been designed for this complex situation. We propose new preprocessing methods, which perform not only normalization and denoising tasks, but also detect reflections and artifacts in the image. A new candidates segmentation method, based on mathematical morphology, is proposed. These candidates are characterized using classical features, but also novel contextual features. Finally, a random forest algorithm is used to detect the exudates among the candidates. The method has been validated on the e-ophtha EX database, obtaining an AUC of 0.95. It has been also validated on other databases, obtaining an AUC between 0.93 and 0.95, outperforming state-of-the-art methods. Copyright © 2014 Elsevier B.V. All rights reserved.
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ANZA Seismic Network- From Monitoring to Science
NASA Astrophysics Data System (ADS)
Vernon, F.; Eakin, J.; Martynov, V.; Newman, R.; Offield, G.; Hindley, A.; Astiz, L.
2007-05-01
The ANZA Seismic Network (http:eqinfo.ucsd.edu) utilizes broadband and strong motion sensors with 24-bit dataloggers combined with real-time telemetry to monitor local and regional seismicity in southernmost California. The ANZA network provides real-time data to the IRIS DMC, California Integrated Seismic Network (CISN), other regional networks, and the Advanced National Seismic System (ANSS), in addition to providing near real-time information and monitoring to the greater San Diego community. Twelve high dynamic range broadband and strong motion sensors adjacent to the San Jacinto Fault zone contribute data for earthquake source studies and continue the monitoring of the seismic activity of the San Jacinto fault initiated 24 years ago. Five additional stations are located in the San Diego region with one more station on San Clemente Island. The ANZA network uses the advance wireless networking capabilities of the NSF High Performance Wireless Research and Education Network (http:hpwren.ucsd.edu) to provide the communication infrastructure for the real-time telemetry of Anza seismic stations. The ANZA network uses the Antelope data acquisition software. The combination of high quality hardware, communications, and software allow for an annual network uptime in excess of 99.5% with a median annual station real-time data return rate of 99.3%. Approximately 90,000 events, dominantly local sources but including regional and teleseismic events, comprise the ANZA network waveform database. All waveform data and event data are managed using the Datascope relational database. The ANZA network data has been used in a variety of scientific research including detailed structure of the San Jacinto Fault Zone, earthquake source physics, spatial and temporal studies of aftershocks, array studies of teleseismic body waves, and array studies on the source of microseisms. To augment the location, detection, and high frequency observations of the seismic source spectrum from local earthquakes, the ANZA network is receiving real-time data from borehole arrays located at the UCSD Thornton Hospital, and from UCSB's Borrego Valley and Garner Valley Downhole Arrays. Finally the ANZA network is acquiring data from seven PBO sites each with 300 meter deep MEMs accelerometers, passive seismometers, and a borehole strainmeter.
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Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong
2016-02-11
We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods.
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Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong
2016-01-01
We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods. PMID:26864172
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Metabolomics analysis: Finding out metabolic building blocks
2017-01-01
In this paper we propose a new methodology for the analysis of metabolic networks. We use the notion of strongly connected components of a graph, called in this context metabolic building blocks. Every strongly connected component is contracted to a single node in such a way that the resulting graph is a directed acyclic graph, called a metabolic DAG, with a considerably reduced number of nodes. The property of being a directed acyclic graph brings out a background graph topology that reveals the connectivity of the metabolic network, as well as bridges, isolated nodes and cut nodes. Altogether, it becomes a key information for the discovery of functional metabolic relations. Our methodology has been applied to the glycolysis and the purine metabolic pathways for all organisms in the KEGG database, although it is general enough to work on any database. As expected, using the metabolic DAGs formalism, a considerable reduction on the size of the metabolic networks has been obtained, specially in the case of the purine pathway due to its relative larger size. As a proof of concept, from the information captured by a metabolic DAG and its corresponding metabolic building blocks, we obtain the core of the glycolysis pathway and the core of the purine metabolism pathway and detect some essential metabolic building blocks that reveal the key reactions in both pathways. Finally, the application of our methodology to the glycolysis pathway and the purine metabolism pathway reproduce the tree of life for the whole set of the organisms represented in the KEGG database which supports the utility of this research. PMID:28493998
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Foerster, Hartmut; Bombarely, Aureliano; Battey, James N D; Sierro, Nicolas; Ivanov, Nikolai V; Mueller, Lukas A
2018-01-01
Abstract SolCyc is the entry portal to pathway/genome databases (PGDBs) for major species of the Solanaceae family hosted at the Sol Genomics Network. Currently, SolCyc comprises six organism-specific PGDBs for tomato, potato, pepper, petunia, tobacco and one Rubiaceae, coffee. The metabolic networks of those PGDBs have been computationally predicted by the pathologic component of the pathway tools software using the manually curated multi-domain database MetaCyc (http://www.metacyc.org/) as reference. SolCyc has been recently extended by taxon-specific databases, i.e. the family-specific SolanaCyc database, containing only curated data pertinent to species of the nightshade family, and NicotianaCyc, a genus-specific database that stores all relevant metabolic data of the Nicotiana genus. Through manual curation of the published literature, new metabolic pathways have been created in those databases, which are complemented by the continuously updated, relevant species-specific pathways from MetaCyc. At present, SolanaCyc comprises 199 pathways and 29 superpathways and NicotianaCyc accounts for 72 pathways and 13 superpathways. Curator-maintained, taxon-specific databases such as SolanaCyc and NicotianaCyc are characterized by an enrichment of data specific to these taxa and free of falsely predicted pathways. Both databases have been used to update recently created Nicotiana-specific databases for Nicotiana tabacum, Nicotiana benthamiana, Nicotiana sylvestris and Nicotiana tomentosiformis by propagating verifiable data into those PGDBs. In addition, in-depth curation of the pathways in N.tabacum has been carried out which resulted in the elimination of 156 pathways from the 569 pathways predicted by pathway tools. Together, in-depth curation of the predicted pathway network and the supplementation with curated data from taxon-specific databases has substantially improved the curation status of the species–specific N.tabacum PGDB. The implementation of this strategy will significantly advance the curation status of all organism-specific databases in SolCyc resulting in the improvement on database accuracy, data analysis and visualization of biochemical networks in those species. Database URL https://solgenomics.net/tools/solcyc/ PMID:29762652
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Freshwater Biological Traits Database (Final Report)
EPA announced the release of the final report, Freshwater Biological Traits Database. This report discusses the development of a database of freshwater biological traits. The database combines several existing traits databases into an online format. The database is also...
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Mathematical modeling and computational prediction of cancer drug resistance.
Sun, Xiaoqiang; Hu, Bin
2017-06-23
Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Freight Transportation Energy Use : Volume 3. Freight Network and Operations Database.
DOT National Transportation Integrated Search
1979-07-01
The data sources, procedures, and assumptions used to generate the TSC national freight network and operations database are documented. National rail, highway, waterway, and pipeline networks are presented, and estimates of facility capacity, travel ...
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Baseline estimation in flame's spectra by using neural networks and robust statistics
NASA Astrophysics Data System (ADS)
Garces, Hugo; Arias, Luis; Rojas, Alejandro
2014-09-01
This work presents a baseline estimation method in flame spectra based on artificial intelligence structure as a neural network, combining robust statistics with multivariate analysis to automatically discriminate measured wavelengths belonging to continuous feature for model adaptation, surpassing restriction of measuring target baseline for training. The main contributions of this paper are: to analyze a flame spectra database computing Jolliffe statistics from Principal Components Analysis detecting wavelengths not correlated with most of the measured data corresponding to baseline; to systematically determine the optimal number of neurons in hidden layers based on Akaike's Final Prediction Error; to estimate baseline in full wavelength range sampling measured spectra; and to train an artificial intelligence structure as a Neural Network which allows to generalize the relation between measured and baseline spectra. The main application of our research is to compute total radiation with baseline information, allowing to diagnose combustion process state for optimization in early stages.
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Flexible network reconstruction from relational databases with Cytoscape and CytoSQL
2010-01-01
Background Molecular interaction networks can be efficiently studied using network visualization software such as Cytoscape. The relevant nodes, edges and their attributes can be imported in Cytoscape in various file formats, or directly from external databases through specialized third party plugins. However, molecular data are often stored in relational databases with their own specific structure, for which dedicated plugins do not exist. Therefore, a more generic solution is presented. Results A new Cytoscape plugin 'CytoSQL' is developed to connect Cytoscape to any relational database. It allows to launch SQL ('Structured Query Language') queries from within Cytoscape, with the option to inject node or edge features of an existing network as SQL arguments, and to convert the retrieved data to Cytoscape network components. Supported by a set of case studies we demonstrate the flexibility and the power of the CytoSQL plugin in converting specific data subsets into meaningful network representations. Conclusions CytoSQL offers a unified approach to let Cytoscape interact with relational databases. Thanks to the power of the SQL syntax, this tool can rapidly generate and enrich networks according to very complex criteria. The plugin is available at http://www.ptools.ua.ac.be/CytoSQL. PMID:20594316
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Flexible network reconstruction from relational databases with Cytoscape and CytoSQL.
Laukens, Kris; Hollunder, Jens; Dang, Thanh Hai; De Jaeger, Geert; Kuiper, Martin; Witters, Erwin; Verschoren, Alain; Van Leemput, Koenraad
2010-07-01
Molecular interaction networks can be efficiently studied using network visualization software such as Cytoscape. The relevant nodes, edges and their attributes can be imported in Cytoscape in various file formats, or directly from external databases through specialized third party plugins. However, molecular data are often stored in relational databases with their own specific structure, for which dedicated plugins do not exist. Therefore, a more generic solution is presented. A new Cytoscape plugin 'CytoSQL' is developed to connect Cytoscape to any relational database. It allows to launch SQL ('Structured Query Language') queries from within Cytoscape, with the option to inject node or edge features of an existing network as SQL arguments, and to convert the retrieved data to Cytoscape network components. Supported by a set of case studies we demonstrate the flexibility and the power of the CytoSQL plugin in converting specific data subsets into meaningful network representations. CytoSQL offers a unified approach to let Cytoscape interact with relational databases. Thanks to the power of the SQL syntax, this tool can rapidly generate and enrich networks according to very complex criteria. The plugin is available at http://www.ptools.ua.ac.be/CytoSQL.
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The Clear Creek Envirohydrologic Observatory: From Vision Toward Reality
NASA Astrophysics Data System (ADS)
Just, C.; Muste, M.; Kruger, A.
2007-12-01
As the vision of a fully-functional Clear Creek Envirohydrologic Observatory comes closer to reality, the opportunities for significant watershed science advances in the near future become more apparent. As a starting point to approaching this vision, we focused on creating a working example of cyberinfrastructure in the hydrologic and environmental sciences. The system will integrate a broad range of technologies and ideas: wired and wireless sensors, low power wireless communication, embedded microcontrollers, commodity cellular networks, the internet, unattended quality assurance, metadata, relational databases, machine-to-machine communication, interfaces to hydrologic and environmental models, feedback, and external inputs. Hardware: An accomplishment to date is "in-house" developed sensor networking electronics to compliment commercially available communications. The first of these networkable sensors are dielectric soil moisture probes that are arrayed and equipped with wireless connectivity for communications. Commercially available data logging and telemetry-enabled systems deployed at the Clear Creek testbed include a Campbell Scientific CR1000 datalogger, a Redwing 100 cellular modem, a YA Series yagi antenna, a NP12 rechargeable battery, and a BP SX20U solar panel. This networking equipment has been coupled with Hach DS5X water quality sondes, DTS-12 turbidity probes and MicroLAB nutrient analyzers. Software: Our existing data model is an Arc Hydro-based geodatabase customized with applications for extraction and population of the database with third party data. The following third party data are acquired automatically and in real time into the Arc Hydro customized database: 1) geophysical data: 10m DEM and soil grids, soils; 2) land use/land cover data; and 3) eco-hydrological: radar-based rainfall estimates, stream gage, streamlines, and water quality data. A new processing software for data analysis of Acoustic Doppler Current Profilers (ADCP) measurements has been finalized. The software package provides mean flow field and turbulence characteristics obtained by operating the ADCP at fixed points or using the moving-boat approach. Current Work: The current development work is focused on extracting and populating the Clear Creek database with in-situ measurements acquired and transmitted in real time with sensors deployed in the Clear Creek watershed.
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NASA Astrophysics Data System (ADS)
Rangaswamy, T.; Vidhyashankar, S.; Madhusudan, M.; Bharath Shekar, H. R.
2015-04-01
The current trends of engineering follow the basic rule of innovation in mechanical engineering aspects. For the engineers to be efficient, problem solving aspects need to be viewed in a multidimensional perspective. One such methodology implemented is the fusion of technologies from other disciplines in order to solve the problems. This paper mainly deals with the application of Neural Networks in order to analyze the performance parameters of an XD3P Peugeot engine (used in Ministry of Defence). The basic propaganda of the work is divided into two main working stages. In the former stage, experimentation of an IC engine is carried out in order to obtain the primary data. In the latter stage the primary database formed is used to design and implement a predictive neural network in order to analyze the output parameters variation with respect to each other. A mathematical governing equation for the neural network is obtained. The obtained polynomial equation describes the characteristic behavior of the built neural network system. Finally, a comparative study of the results is carried out.
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Conrads, Paul; Roehl, Edwin A.
2007-01-01
The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and water-surface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystem Science provides support for EDEN and the goal of providing quality assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. To increase the accuracy of the water-surface models, 25 real-time water-level gaging stations were added to the network of 253 established water-level gaging stations. To incorporate the data from the newly added stations to the 7-year EDEN database in the greater Everglades, the short-term water-level records (generally less than 1 year) needed to be simulated back in time (hindcasted) to be concurrent with data from the established gaging stations in the database. A three-step modeling approach using artificial neural network models was used to estimate the water levels at the new stations. The artificial neural network models used static variables that represent the gaging station location and percent vegetation in addition to dynamic variables that represent water-level data from the established EDEN gaging stations. The final step of the modeling approach was to simulate the computed error of the initial estimate to increase the accuracy of the final water-level estimate. The three-step modeling approach for estimating water levels at the new EDEN gaging stations produced satisfactory results. The coefficients of determination (R2) for 21 of the 25 estimates were greater than 0.95, and all of the estimates (25 of 25) were greater than 0.82. The model estimates showed good agreement with the measured data. For some new EDEN stations with limited measured data, the record extension (hindcasts) included periods beyond the range of the data used to train the artificial neural network models. The comparison of the hindcasts with long-term water-level data proximal to the new EDEN gaging stations indicated that the water-level estimates were reasonable. The percent model error (root mean square error divided by the range of the measured data) was less than 6 percent, and for the majority of stations (20 of 25), the percent model error was less than 1 percent.
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,
2004-01-01
The Ground-Water Site-Inventory (GWSI) System is a ground-water data storage and retrieval system that is part of the National Water Information System (NWIS) developed by the U.S. Geological Survey (USGS). The NWIS is a distributed water database in which data can be processed over a network of workstations and file servers at USGS offices throughout the United States. This system comprises the GWSI, the Automated Data Processing System (ADAPS), the Water-Quality System (QWDATA), and the Site-Specific Water-Use Data System (SWUDS). The GWSI System provides for entering new sites and updating existing sites within the local database. In addition, the GWSI provides for retrieving and displaying ground-water and sitefile data stored in the local database. Finally, the GWSI provides for routine maintenance of the local and national data records. This manual contains instructions for users of the GWSI and discusses the general operating procedures for the programs found within the GWSI Main Menu.
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,
2005-01-01
The Ground-Water Site-Inventory (GWSI) System is a ground-water data storage and retrieval system that is part of the National Water Information System (NWIS) developed by the U.S. Geological Survey (USGS). The NWIS is a distributed water database in which data can be processed over a network of workstations and file servers at USGS offices throughout the United States. This system comprises the GWSI, the Automated Data Processing System (ADAPS), the Water-Quality System (QWDATA), and the Site- Specific Water-Use Data System (SWUDS). The GWSI System provides for entering new sites and updating existing sites within the local database. In addition, the GWSI provides for retrieving and displaying groundwater and Sitefile data stored in the local database. Finally, the GWSI provides for routine maintenance of the local and national data records. This manual contains instructions for users of the GWSI and discusses the general operating procedures for the programs found within the GWSI Main Menu.
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Spread of hospital-acquired infections: A comparison of healthcare networks
Astagneau, Pascal; Crépey, Pascal
2017-01-01
Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the potential scale of HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. Using an exhaustive database of all hospital discharge summaries in France in 2014, we construct and analyze three patient networks based on the following: transfers of patients with HAI (HAI-specific network); patients with suspected HAI (suspected-HAI network); and all patients (general network). All three networks have heterogeneous patient flow and demonstrate small-world and scale-free characteristics. Patient populations that comprise these networks are also heterogeneous in their movement patterns. Ranking of hospitals by centrality measures and comparing community clustering using community detection algorithms shows that despite the differences in patient population, the HAI-specific and suspected-HAI networks rely on the same underlying structure as that of the general network. As a result, the general network may be more reliable in studying potential spread of HAIs. Finally, we identify transfer patterns at both the French regional and departmental (county) levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies. PMID:28837555
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Network-based drug discovery by integrating systems biology and computational technologies
Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua
2013-01-01
Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768
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Toward the automated generation of genome-scale metabolic networks in the SEED.
DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron
2007-04-26
Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the stage for the automated generation of substantially complete metabolic networks for over 400 complete genome sequences currently in the SEED. With each genome that is processed using our tools, the database of common components grows to cover more of the diversity of metabolic pathways. This increases the likelihood that components of reaction networks for subsequently processed genomes can be retrieved from the database, rather than assembled and verified manually.
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Insertion algorithms for network model database management systems
NASA Astrophysics Data System (ADS)
Mamadolimov, Abdurashid; Khikmat, Saburov
2017-12-01
The network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature is that the schema, viewed as a graph in which object types are nodes and relationship types are arcs, forms partial order. When a database is large and a query comparison is expensive then the efficiency requirement of managing algorithms is minimizing the number of query comparisons. We consider updating operation for network model database management systems. We develop a new sequantial algorithm for updating operation. Also we suggest a distributed version of the algorithm.
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Mashiach, R.; Cohen, S.; Kedem, A.; Baron, A.; Zajicek, M.; Feldman, I.; Seidman, D.; Soriano, D.
2018-01-01
Endometriosis is a disease characterized by the development of endometrial tissue outside the uterus, but its cause remains largely unknown. Numerous genes have been studied and proposed to help explain its pathogenesis. However, the large number of these candidate genes has made functional validation through experimental methodologies nearly impossible. Computational methods could provide a useful alternative for prioritizing those most likely to be susceptibility genes. Using artificial intelligence applied to text mining, this study analyzed the genes involved in the pathogenesis, development, and progression of endometriosis. The data extraction by text mining of the endometriosis-related genes in the PubMed database was based on natural language processing, and the data were filtered to remove false positives. Using data from the text mining and gene network information as input for the web-based tool, 15,207 endometriosis-related genes were ranked according to their score in the database. Characterization of the filtered gene set through gene ontology, pathway, and network analysis provided information about the numerous mechanisms hypothesized to be responsible for the establishment of ectopic endometrial tissue, as well as the migration, implantation, survival, and proliferation of ectopic endometrial cells. Finally, the human genome was scanned through various databases using filtered genes as a seed to determine novel genes that might also be involved in the pathogenesis of endometriosis but which have not yet been characterized. These genes could be promising candidates to serve as useful diagnostic biomarkers and therapeutic targets in the management of endometriosis. PMID:29750165
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Bouaziz, J; Mashiach, R; Cohen, S; Kedem, A; Baron, A; Zajicek, M; Feldman, I; Seidman, D; Soriano, D
2018-01-01
Endometriosis is a disease characterized by the development of endometrial tissue outside the uterus, but its cause remains largely unknown. Numerous genes have been studied and proposed to help explain its pathogenesis. However, the large number of these candidate genes has made functional validation through experimental methodologies nearly impossible. Computational methods could provide a useful alternative for prioritizing those most likely to be susceptibility genes. Using artificial intelligence applied to text mining, this study analyzed the genes involved in the pathogenesis, development, and progression of endometriosis. The data extraction by text mining of the endometriosis-related genes in the PubMed database was based on natural language processing, and the data were filtered to remove false positives. Using data from the text mining and gene network information as input for the web-based tool, 15,207 endometriosis-related genes were ranked according to their score in the database. Characterization of the filtered gene set through gene ontology, pathway, and network analysis provided information about the numerous mechanisms hypothesized to be responsible for the establishment of ectopic endometrial tissue, as well as the migration, implantation, survival, and proliferation of ectopic endometrial cells. Finally, the human genome was scanned through various databases using filtered genes as a seed to determine novel genes that might also be involved in the pathogenesis of endometriosis but which have not yet been characterized. These genes could be promising candidates to serve as useful diagnostic biomarkers and therapeutic targets in the management of endometriosis.
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Cerina, Federica; Zhu, Zhen; Chessa, Alessandro; Riccaboni, Massimo
2015-01-01
Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the global multi-regional input-output (GMRIO) tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION) and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries. PMID:26222389
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Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks
Ronellenfitsch, Henrik; Lasser, Jana; Daly, Douglas C.; Katifori, Eleni
2015-01-01
The leaves of angiosperms contain highly complex venation networks consisting of recursively nested, hierarchically organized loops. We describe a new phenotypic trait of reticulate vascular networks based on the topology of the nested loops. This phenotypic trait encodes information orthogonal to widely used geometric phenotypic traits, and thus constitutes a new dimension in the leaf venation phenotypic space. We apply our metric to a database of 186 leaves and leaflets representing 137 species, predominantly from the Burseraceae family, revealing diverse topological network traits even within this single family. We show that topological information significantly improves identification of leaves from fragments by calculating a “leaf venation fingerprint” from topology and geometry. Further, we present a phenomenological model suggesting that the topological traits can be explained by noise effects unique to specimen during development of each leaf which leave their imprint on the final network. This work opens the path to new quantitative identification techniques for leaves which go beyond simple geometric traits such as vein density and is directly applicable to other planar or sub-planar networks such as blood vessels in the brain. PMID:26700471
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What can graph theory tell us about word learning and lexical retrieval?
Vitevitch, Michael S
2008-04-01
Graph theory and the new science of networks provide a mathematically rigorous approach to examine the development and organization of complex systems. These tools were applied to the mental lexicon to examine the organization of words in the lexicon and to explore how that structure might influence the acquisition and retrieval of phonological word-forms. Pajek, a program for large network analysis and visualization (V. Batagelj & A. Mvrar, 1998), was used to examine several characteristics of a network derived from a computerized database of the adult lexicon. Nodes in the network represented words, and a link connected two nodes if the words were phonological neighbors. The average path length and clustering coefficient suggest that the phonological network exhibits small-world characteristics. The degree distribution was fit better by an exponential rather than a power-law function. Finally, the network exhibited assortative mixing by degree. Some of these structural characteristics were also found in graphs that were formed by 2 simple stochastic processes suggesting that similar processes might influence the development of the lexicon. The graph theoretic perspective may provide novel insights about the mental lexicon and lead to future studies that help us better understand language development and processing.
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Electronic Reference Library: Silverplatter's Database Networking Solution.
ERIC Educational Resources Information Center
Millea, Megan
Silverplatter's Electronic Reference Library (ERL) provides wide area network access to its databases using TCP/IP communications and client-server architecture. ERL has two main components: The ERL clients (retrieval interface) and the ERL server (search engines). ERL clients provide patrons with seamless access to multiple databases on multiple…
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Database Software Selection for the Egyptian National STI Network.
ERIC Educational Resources Information Center
Slamecka, Vladimir
The evaluation and selection of information/data management system software for the Egyptian National Scientific and Technical (STI) Network are described. An overview of the state-of-the-art of database technology elaborates on the differences between information retrieval and database management systems (DBMS). The desirable characteristics of…
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History-Enriched Spaces for Shared Encounters
NASA Astrophysics Data System (ADS)
Konomi, Shin'ichi; Sezaki, Kaoru; Kitsuregawa, Masaru
We discuss "history-enriched spaces" that use historical data to support shared encounters. We first examine our experiences with DeaiExplorer, a social network display that uses RFID and a historical database to support social interactions at academic conferences. This leads to our discussions on three complementary approaches to addressing the issues of supporting social encounters: (1) embedding historical data in embodied interactions, (2) designing for weakly involved interactions such as social navigation, and (3) designing for privacy. Finally, we briefly describe a preliminary prototype of a proxemics-based awareness tool that considers these approaches.
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A Database of Tornado Events as Perceived by the USArray Transportable Array Network
NASA Astrophysics Data System (ADS)
Tytell, J. E.; Vernon, F.; Reyes, J. C.
2015-12-01
Over the course of the deployment of Earthscope's USArray Transportable Array (TA) network there have numerous tornado events that have occurred within the changing footprint of its network. The Array Network Facility based in San Diego, California, has compiled a database of these tornado events based on data provided by the NOAA Storm Prediction Center (SPC). The SPC data itself consists of parameters such as start-end point track data for each event, maximum EF intensities, and maximum track widths. Our database is Antelope driven and combines these data from the SPC with detailed station information from the TA network. We are now able to list all available TA stations during any specific tornado event date and also provide a single calculated "nearest" TA station per individual tornado event. We aim to provide this database as a starting resource for those with an interest in investigating tornado signatures within surface pressure and seismic response data. On a larger scale, the database may be of particular interest to the infrasound research community
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Jin, Shuan; Zhu, Wenhua; Li, Jun
2018-01-01
The purpose of this study was to identify predictive biomarkers used for clinical therapy and prognostic evaluation of high-risk gastrointestinal stromal tumors (GISTs). In this study, microarray data GSE31802 were used to identify differentially expressed genes (DEGs) between high-risk GISTs and low-risk GISTs. Then, enrichment analysis of DEGs was conducted based on the gene ontology and kyoto encyclopedia of genes and genomes pathway database. In addition, the transcription factors and cancer-related genes in DEGs were screened according to the TRANSFAC, TSGene, and TAG database. Finally, protein-protein interaction (PPI) network was constructed and analyzed to look for critical genes involved in high-risk GISTs. A total of forty DEGs were obtained and these genes were mainly involved in four pathways, including melanogenesis, neuroactive ligand-receptor interaction, malaria, and hematopoietic cell lineage. The enriched biological processes were related to the regulation of insulin secretion, integrin activation, and neuropeptide signaling pathway. Transcription factor analysis of DEGs indicated that POU domain, class 2, associating factor 1 (POU2AF1) was significantly downregulated in high-risk GISTs. By constructing the PPI network of DEGs, ten genes with high degrees formed local networks, such as PNOC, P2RY14, and SELP. Four genes as POU2AF1, PNOC, P2RY14, and SELP might be used as biomarkers for prognosis of high-risk GISTs.
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The Network Configuration of an Object Relational Database Management System
NASA Technical Reports Server (NTRS)
Diaz, Philip; Harris, W. C.
2000-01-01
The networking and implementation of the Oracle Database Management System (ODBMS) requires developers to have knowledge of the UNIX operating system as well as all the features of the Oracle Server. The server is an object relational database management system (DBMS). By using distributed processing, processes are split up between the database server and client application programs. The DBMS handles all the responsibilities of the server. The workstations running the database application concentrate on the interpretation and display of data.
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Yu, Guohua; Zhang, Yanqiong; Ren, Weiqiong; Dong, Ling; Li, Junfang; Geng, Ya; Zhang, Yi; Li, Defeng; Xu, Haiyu; Yang, Hongjun
2017-01-01
For decades in China, the Yin-Huang-Qing-Fei capsule (YHQFC) has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness) of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL-5, IL-10, IL-13, FCER1G, CCL11, and EPX) were demonstrated to be associated with the inflammatory process that occurs during the progression of asthma. Finally, a molecular docking simulation was performed and the results exhibited that 17 pairs of chemical components and candidate YHQFC targets involved in asthma pathway had strong binding efficiencies. In conclusion, this network pharmacology-based investigation revealed that YHQFC may attenuate the inflammatory reaction of chronic bronchitis by regulating its candidate targets, which may be implicated in the major pathological processes of the asthma pathway.
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Yu, Guohua; Zhang, Yanqiong; Ren, Weiqiong; Dong, Ling; Li, Junfang; Geng, Ya; Zhang, Yi; Li, Defeng; Xu, Haiyu; Yang, Hongjun
2017-01-01
For decades in China, the Yin–Huang–Qing–Fei capsule (YHQFC) has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness) of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL-5, IL-10, IL-13, FCER1G, CCL11, and EPX) were demonstrated to be associated with the inflammatory process that occurs during the progression of asthma. Finally, a molecular docking simulation was performed and the results exhibited that 17 pairs of chemical components and candidate YHQFC targets involved in asthma pathway had strong binding efficiencies. In conclusion, this network pharmacology-based investigation revealed that YHQFC may attenuate the inflammatory reaction of chronic bronchitis by regulating its candidate targets, which may be implicated in the major pathological processes of the asthma pathway. PMID:28053519
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New model for distributed multimedia databases and its application to networking of museums
NASA Astrophysics Data System (ADS)
Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki
1998-02-01
This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.
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Balancing Your Database Network Licenses against Your Budget.
ERIC Educational Resources Information Center
Bauer, Benjamin F.
1995-01-01
Discussion of choosing database access to satisfy users and budgetary constraints highlights a method to make educated estimates of simultaneous usage levels. Topics include pricing; advances in networks and CD-ROM technology; and two networking scenarios, one in an academic library and one in a corporate research facility. (LRW)
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77 FR 72335 - Proposed Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-05
... computer networks, systems, or databases. The records contain the individual's name; social security number... control and track access to DLA-controlled networks, computer systems, and databases. The records may also...
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Vavougios, Georgios D; Solenov, Evgeniy I; Hatzoglou, Chrissi; Baturina, Galina S; Katkova, Liubov E; Molyvdas, Paschalis Adam; Gourgoulianis, Konstantinos I; Zarogiannis, Sotirios G
2015-10-01
The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients (network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease. Copyright © 2015 the American Physiological Society.
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SoyFN: a knowledge database of soybean functional networks.
Xu, Yungang; Guo, Maozu; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang
2014-01-01
Many databases for soybean genomic analysis have been built and made publicly available, but few of them contain knowledge specifically targeting the omics-level gene-gene, gene-microRNA (miRNA) and miRNA-miRNA interactions. Here, we present SoyFN, a knowledge database of soybean functional gene networks and miRNA functional networks. SoyFN provides user-friendly interfaces to retrieve, visualize, analyze and download the functional networks of soybean genes and miRNAs. In addition, it incorporates much information about KEGG pathways, gene ontology annotations and 3'-UTR sequences as well as many useful tools including SoySearch, ID mapping, Genome Browser, eFP Browser and promoter motif scan. SoyFN is a schema-free database that can be accessed as a Web service from any modern programming language using a simple Hypertext Transfer Protocol call. The Web site is implemented in Java, JavaScript, PHP, HTML and Apache, with all major browsers supported. We anticipate that this database will be useful for members of research communities both in soybean experimental science and bioinformatics. Database URL: http://nclab.hit.edu.cn/SoyFN.
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1985-12-01
RELATIONAL TO NETWORK QUERY TRANSLATOR FOR A DISTRIBUTED DATABASE MANAGEMENT SYSTEM TH ESI S .L Kevin H. Mahoney -- Captain, USAF AFIT/GCS/ENG/85D-7...NETWORK QUERY TRANSLATOR FOR A DISTRIBUTED DATABASE MANAGEMENT SYSTEM - THESIS Presented to the Faculty of the School of Engineering of the Air Force...Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Systems - Kevin H. Mahoney
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NASA Astrophysics Data System (ADS)
Zhang, Lin; Lu, Jian; Zhou, Jialin; Zhu, Jinqing; Li, Yunxuan; Wan, Qian
2018-03-01
Didi Dache is the most popular taxi order mobile app in China, which provides online taxi-hailing service. The obtained big database from this app could be used to analyze the complexities’ day-to-day dynamic evolution of Didi taxi trip network (DTTN) from the level of complex network dynamics. First, this paper proposes the data cleaning and modeling methods for expressing Nanjing’s DTTN as a complex network. Second, the three consecutive weeks’ data are cleaned to establish 21 DTTNs based on the proposed big data processing technology. Then, multiple topology measures that characterize the complexities’ day-to-day dynamic evolution of these networks are provided. Third, these measures of 21 DTTNs are calculated and subsequently explained with actual implications. They are used as a training set for modeling the BP neural network which is designed for predicting DTTN complexities evolution. Finally, the reliability of the designed BP neural network is verified by comparing with the actual data and the results obtained from ARIMA method simultaneously. Because network complexities are the basis for modeling cascading failures and conducting link prediction in complex system, this proposed research framework not only provides a novel perspective for analyzing DTTN from the level of system aggregated behavior, but can also be used to improve the DTTN management level.
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Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang
2017-01-01
Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam's scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals.
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Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang
2017-01-01
Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam’s scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals. PMID:28928958
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BioSYNTHESIS: access to a knowledge network of health sciences databases.
Broering, N C; Hylton, J S; Guttmann, R; Eskridge, D
1991-04-01
Users of the IAIMS Knowledge Network at the Georgetown University Medical Center have access to multiple in-house and external databases from a single point of entry through BioSYNTHESIS. The IAIMS project has developed a rich environment of biomedical information resources that represent a medical decision support system for campus physicians and students. The BioSYNTHESIS system is an information navigator that provides transparent access to a Knowledge Network of over a dozen databases. These multiple health sciences databases consist of bibliographic, informational, diagnostic, and research systems which reside on diverse computers such as DEC VAXs, SUN 490, AT&T 3B2s, Macintoshes, IBM PC/PS2s and the AT&T ISN and SYTEK network systems. Ethernet and TCP/IP protocols are used in the network architecture. BioSYNTHESIS also provides network links to the other campus libraries and to external institutions. As additional knowledge resources and technological advances have become available. BioSYNTHESIS has evolved from a two phase to a three phase program. Major components of the system including recent achievements and future plans are described.
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Innovative Networking Concepts Tested on the Advanced Communications Technology Satellite
NASA Technical Reports Server (NTRS)
Friedman, Daniel; Gupta, Sonjai; Zhang, Chuanguo; Ephremides, Anthony
1996-01-01
This paper describes a program of experiments conducted over the advanced communications technology satellite (ACTS) and the associated TI-VSAT (very small aperture terminal). The experiments were motivated by the commercial potential of low-cost receive only satellite terminals that can operate in a hybrid network environment, and by the desire to demonstrate frame relay technology over satellite networks. The first experiment tested highly adaptive methods of satellite bandwidth allocation in an integrated voice-data service environment. The second involved comparison of forward error correction (FEC) and automatic repeat request (ARQ) methods of error control for satellite communication with emphasis on the advantage that a hybrid architecture provides, especially in the case of multicasts. Finally, the third experiment demonstrated hybrid access to databases and compared the performance of internetworking protocols for interconnecting local area networks (LANs) via satellite. A custom unit termed frame relay access switch (FRACS) was developed by COMSAT Laboratories for these experiments; the preparation and conduct of these experiments involved a total of 20 people from the University of Maryland, the University of Colorado and COMSAT Laboratories, from late 1992 until 1995.
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NASA Astrophysics Data System (ADS)
Guan, Jun; Xu, Xiaoyu; Xing, Lizhi
2018-03-01
The input-output table is comprehensive and detailed in describing national economic systems with abundance of economic relationships depicting information of supply and demand among industrial sectors. This paper focuses on how to quantify the degree of competition on the global value chain (GVC) from the perspective of econophysics. Global Industrial Strongest Relevant Network models are established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output (ICIO) tables and then have them transformed into Global Industrial Resource Competition Network models to analyze the competitive relationships based on bibliographic coupling approach. Three indicators well suited for the weighted and undirected networks with self-loops are introduced here, including unit weight for competitive power, disparity in the weight for competitive amplitude and weighted clustering coefficient for competitive intensity. Finally, these models and indicators were further applied empirically to analyze the function of industrial sectors on the basis of the latest World Input-Output Database (WIOD) in order to reveal inter-sector competitive status during the economic globalization.
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ERIC Educational Resources Information Center
Liu, Xia; Liu, Lai C.; Koong, Kai S.; Lu, June
2003-01-01
Analysis of 300 information technology job postings in two Internet databases identified the following skill categories: programming languages (Java, C/C++, and Visual Basic were most frequent); website development (57% sought SQL and HTML skills); databases (nearly 50% required Oracle); networks (only Windows NT or wide-area/local-area networks);…
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Experience in running relational databases on clustered storage
NASA Astrophysics Data System (ADS)
Gaspar Aparicio, Ruben; Potocky, Miroslav
2015-12-01
For past eight years, CERN IT Database group has based its backend storage on NAS (Network-Attached Storage) architecture, providing database access via NFS (Network File System) protocol. In last two and half years, our storage has evolved from a scale-up architecture to a scale-out one. This paper describes our setup and a set of functionalities providing key features to other services like Database on Demand [1] or CERN Oracle backup and recovery service. It also outlines possible trend of evolution that, storage for databases could follow.
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2017-01-01
The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization. PMID:28873432
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Xing, Lizhi
2017-01-01
The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization.
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Neural Network Modeling of UH-60A Pilot Vibration
NASA Technical Reports Server (NTRS)
Kottapalli, Sesi
2003-01-01
Full-scale flight-test pilot floor vibration is modeled using neural networks and full-scale wind tunnel test data for low speed level flight conditions. Neural network connections between the wind tunnel test data and the tlxee flight test pilot vibration components (vertical, lateral, and longitudinal) are studied. Two full-scale UH-60A Black Hawk databases are used. The first database is the NASMArmy UH-60A Airloads Program flight test database. The second database is the UH-60A rotor-only wind tunnel database that was acquired in the NASA Ames SO- by 120- Foot Wind Tunnel with the Large Rotor Test Apparatus (LRTA). Using neural networks, the flight-test pilot vibration is modeled using the wind tunnel rotating system hub accelerations, and separately, using the hub loads. The results show that the wind tunnel rotating system hub accelerations and the operating parameters can represent the flight test pilot vibration. The six components of the wind tunnel N/rev balance-system hub loads and the operating parameters can also represent the flight test pilot vibration. The present neural network connections can significandy increase the value of wind tunnel testing.
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From Saccharomyces cerevisiae to human: The important gene co-expression modules.
Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin
2017-08-01
Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.
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Random Deep Belief Networks for Recognizing Emotions from Speech Signals.
Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang
2017-01-01
Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.
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Random Deep Belief Networks for Recognizing Emotions from Speech Signals
Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang
2017-01-01
Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition. PMID:28356908
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A study of the Immune Epitope Database for some fungi species using network topological indices.
Vázquez-Prieto, Severo; Paniagua, Esperanza; Solana, Hugo; Ubeira, Florencio M; González-Díaz, Humberto
2017-08-01
In the last years, the encryption of system structure information with different network topological indices has been a very active field of research. In the present study, we assembled for the first time a complex network using data obtained from the Immune Epitope Database for fungi species, and we then considered the general topology, the node degree distribution, and the local structure of this network. We also calculated eight node centrality measures for the observed network and compared it with three theoretical models. In view of the results obtained, we may expect that the present approach can become a valuable tool to explore the complexity of this database, as well as for the storage, manipulation, comparison, and retrieval of information contained therein.
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An approach to efficient mobility management in intelligent networks
NASA Technical Reports Server (NTRS)
Murthy, K. M. S.
1995-01-01
Providing personal communication systems supporting full mobility require intelligent networks for tracking mobile users and facilitating outgoing and incoming calls over different physical and network environments. In realizing the intelligent network functionalities, databases play a major role. Currently proposed network architectures envision using the SS7-based signaling network for linking these DB's and also for interconnecting DB's with switches. If the network has to support ubiquitous, seamless mobile services, then it has to support additionally mobile application parts, viz., mobile origination calls, mobile destination calls, mobile location updates and inter-switch handovers. These functions will generate significant amount of data and require them to be transferred between databases (HLR, VLR) and switches (MSC's) very efficiently. In the future, the users (fixed or mobile) may use and communicate with sophisticated CPE's (e.g. multimedia, multipoint and multisession calls) which may require complex signaling functions. This will generate volumness service handling data and require efficient transfer of these message between databases and switches. Consequently, the network providers would be able to add new services and capabilities to their networks incrementally, quickly and cost-effectively.
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Zhu, Zhen; Puliga, Michelangelo; Cerina, Federica; Chessa, Alessandro; Riccaboni, Massimo
2015-01-01
The fragmentation of production across countries has become an important feature of the globalization in recent decades and is often conceptualized by the term “global value chains” (GVCs). When empirically investigating the GVCs, previous studies are mainly interested in knowing how global the GVCs are rather than how the GVCs look like. From a complex networks perspective, we use the World Input-Output Database (WIOD) to study the evolution of the global production system. We find that the industry-level GVCs are indeed not chain-like but are better characterized by the tree topology. Hence, we compute the global value trees (GVTs) for all the industries available in the WIOD. Moreover, we compute an industry importance measure based on the GVTs and compare it with other network centrality measures. Finally, we discuss some future applications of the GVTs. PMID:25978067
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What Can Graph Theory Tell Us About Word Learning and Lexical Retrieval?
Vitevitch, Michael S.
2008-01-01
Purpose Graph theory and the new science of networks provide a mathematically rigorous approach to examine the development and organization of complex systems. These tools were applied to the mental lexicon to examine the organization of words in the lexicon and to explore how that structure might influence the acquisition and retrieval of phonological word-forms. Method Pajek, a program for large network analysis and visualization (V. Batagelj & A. Mvrar, 1998), was used to examine several characteristics of a network derived from a computerized database of the adult lexicon. Nodes in the network represented words, and a link connected two nodes if the words were phonological neighbors. Results The average path length and clustering coefficient suggest that the phonological network exhibits small-world characteristics. The degree distribution was fit better by an exponential rather than a power-law function. Finally, the network exhibited assortative mixing by degree. Some of these structural characteristics were also found in graphs that were formed by 2 simple stochastic processes suggesting that similar processes might influence the development of the lexicon. Conclusions The graph theoretic perspective may provide novel insights about the mental lexicon and lead to future studies that help us better understand language development and processing. PMID:18367686
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Telepathology Impacts and Implementation Challenges: A Scoping Review.
Meyer, Julien; Paré, Guy
2015-12-01
Telepathology is a particular form of telemedicine that fundamentally alters the way pathology services are delivered. Prior reviews in this area have mostly focused on 2 themes, namely technical feasibility issues and diagnosis accuracy. To synthesize the literature on telepathology implementation challenges and broader organizational and societal impacts and to propose a research agenda to guide future efforts in this domain. Two complementary databases were systematically searched: MEDLINE (PubMed) and ABI/INFORM (ProQuest). Peer-reviewed articles and conference proceedings were considered. The final sample consisted of 159 papers published between 1992 and 2013. This review highlights the diversity of telepathology networks and the importance of considering these distinctions when interpreting research findings. Various network structures are associated with different benefits. Although the dominant rationale in single-site projects is financial, larger centralized and decentralized telepathology networks are targeting a more diverse set of benefits, including extending access to pathology to a whole region, achieving substantial economies of scale in workforce and equipment, and improving quality by standardizing care. Importantly, our synthesis reveals that the nature and scale of encountered implementation challenges also varies depending on the network structure. In smaller telepathology networks, organizational concerns are less prominent, and implementers are more focused on usability issues. As the network scope widens, organizational and legal issues gain prominence.
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Locating faces in color photographs using neural networks
NASA Astrophysics Data System (ADS)
Brown, Joe R.; Talley, Jim
1994-03-01
This paper summarizes a research effort in finding the locations and sizes of faces in color images (photographs, video stills, etc.) if, in fact, faces are presented. Scenarios for using such a system include serving as the means of localizing skin for automatic color balancing during photo processing or it could be used as a front-end in a customs port of energy context for a system which identified persona non grata given a database of known faces. The approach presented here is a hybrid system including: a neural pre-processor, some conventional image processing steps, and a neural classifier as the final face/non-face discriminator. Neither the training (containing 17,655 faces) nor the test (containing 1829 faces) imagery databases were constrained in their content or quality. The results for the pilot system are reported along with a discussion for improving the current system.
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Le, Duc-Hau; Verbeke, Lieven; Son, Le Hoang; Chu, Dinh-Toi; Pham, Van-Huy
2017-11-14
MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model. Instead of constructing homogeneous miRNA networks, we built heterogeneous miRNA networks consisting of both miRNAs and their target genes, using databases of known miRNA-target gene interactions. In addition, as recent studies demonstrated reciprocal regulatory relations between miRNAs and their target genes, we considered these heterogeneous miRNA networks to be undirected, assuming mutual miRNA-target interactions. Next, we introduced a novel method (RWRMTN) operating on these mutual heterogeneous miRNA networks to rank candidate disease-related miRNAs using a random walk with restart (RWR) based algorithm. Using both known disease-associated miRNAs and their target genes as seed nodes, the method can identify additional miRNAs involved in the disease phenotype. Experiments indicated that RWRMTN outperformed two existing state-of-the-art methods: RWRMDA, a network-based method that also uses a RWR on homogeneous (rather than heterogeneous) miRNA networks, and RLSMDA, a machine learning-based method. Interestingly, we could relate this performance gain to the emergence of "disease modules" in the heterogeneous miRNA networks used as input for the algorithm. Moreover, we could demonstrate that RWRMTN is stable, performing well when using both experimentally validated and predicted miRNA-target gene interaction data for network construction. Finally, using RWRMTN, we identified 76 novel miRNAs associated with 23 disease phenotypes which were present in a recent database of known disease-miRNA associations. Summarizing, using random walks on mutual miRNA-target networks improves the prediction of novel disease-associated miRNAs because of the existence of "disease modules" in these networks.
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Novel Method of Storing and Reconstructing Events at Fermilab E-906/SeaQuest Using a MySQL Database
NASA Astrophysics Data System (ADS)
Hague, Tyler
2010-11-01
Fermilab E-906/SeaQuest is a fixed target experiment at Fermi National Accelerator Laboratory. We are investigating the antiquark asymmetry in the nucleon sea. By examining the ratio of the Drell- Yan cross sections of proton-proton and proton-deuterium collisions we can determine the asymmetry ratio. An essential feature in the development of the analysis software is to update the event reconstruction to modern software tools. We are doing this in a unique way by doing a majority of the calculations within an SQL database. Using a MySQL database allows us to take advantage of off-the-shelf software without sacrificing ROOT compatibility and avoid network bottlenecks with server-side data selection. Using our raw data we create stubs, or partial tracks, at each station which are pieced together to create full tracks. Our reconstruction process uses dynamically created SQL statements to analyze the data. These SQL statements create tables that contain the final reconstructed tracks as well as intermediate values. This poster will explain the reconstruction process and how it is being implemented.
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ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.
Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y
2008-08-12
New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network. The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.
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National Transportation Atlas Databases : 1999
DOT National Transportation Integrated Search
1999-01-01
The National Transportation Atlas Databases -- 1999 (NTAD99) is a set of national : geographic databases of transportation facilities. These databases include geospatial : information for transportation modal networks and intermodal terminals, and re...
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National Transportation Atlas Databases : 2001
DOT National Transportation Integrated Search
2001-01-01
The National Transportation Atlas Databases-2001 (NTAD-2001) is a set of national geographic databases of transportation facilities. These databases include geospatial information for transportation modal networks and intermodal terminals and related...
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National Transportation Atlas Databases : 1996
DOT National Transportation Integrated Search
1996-01-01
The National Transportation Atlas Databases -- 1996 (NTAD96) is a set of national : geographic databases of transportation facilities. These databases include geospatial : information for transportation modal networks and intermodal terminals, and re...
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National Transportation Atlas Databases : 2000
DOT National Transportation Integrated Search
2000-01-01
The National Transportation Atlas Databases-2000 (NTAD-2000) is a set of national geographic databases of transportation facilities. These databases include geospatial information for transportation modal networks and intermodal terminals and related...
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National Transportation Atlas Databases : 1997
DOT National Transportation Integrated Search
1997-01-01
The National Transportation Atlas Databases -- 1997 (NTAD97) is a set of national : geographic databases of transportation facilities. These databases include geospatial : information for transportation modal networks and intermodal terminals, and re...
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RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG
2015-01-01
The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425
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NASA Astrophysics Data System (ADS)
Shanafield, Harold; Shamblin, Stephanie; Devarakonda, Ranjeet; McMurry, Ben; Walker Beaty, Tammy; Wilson, Bruce; Cook, Robert B.
2011-02-01
The FLUXNET global network of regional flux tower networks serves to coordinate the regional and global analysis of eddy covariance based CO2, water vapor and energy flux measurements taken at more than 500 sites in continuous long-term operation. The FLUXNET database presently contains information about the location, characteristics, and data availability of each of these sites. To facilitate the coordination and distribution of this information, we redesigned the underlying database and associated web site. We chose the PostgreSQL database as a platform based on its performance, stability and GIS extensions. PostreSQL allows us to enhance our search and presentation capabilities, which will in turn provide increased functionality for users seeking to understand the FLUXNET data. The redesigned database will also significantly decrease the burden of managing such highly varied data. The website is being developed using the Drupal content management system, which provides many community-developed modules and a robust framework for custom feature development. In parallel, we are working with the regional networks to ensure that the information in the FLUXNET database is identical to that in the regional networks. Going forward, we also plan to develop an automated way to synchronize information with the regional networks.
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Integrating In Silico Resources to Map a Signaling Network
Liu, Hanqing; Beck, Tim N.; Golemis, Erica A.; Serebriiskii, Ilya G.
2013-01-01
The abundance of publicly available life science databases offer a wealth of information that can support interpretation of experimentally derived data and greatly enhance hypothesis generation. Protein interaction and functional networks are not simply new renditions of existing data: they provide the opportunity to gain insights into the specific physical and functional role a protein plays as part of the biological system. In this chapter, we describe different in silico tools that can quickly and conveniently retrieve data from existing data repositories and discuss how the available tools are best utilized for different purposes. While emphasizing protein-protein interaction databases (e.g., BioGrid and IntAct), we also introduce metasearch platforms such as STRING and GeneMANIA, pathway databases (e.g., BioCarta and Pathway Commons), text mining approaches (e.g., PubMed and Chilibot), and resources for drug-protein interactions, genetic information for model organisms and gene expression information based on microarray data mining. Furthermore, we provide a simple step-by-step protocol to building customized protein-protein interaction networks in Cytoscape, a powerful network assembly and visualization program, integrating data retrieved from these various databases. As we illustrate, generation of composite interaction networks enables investigators to extract significantly more information about a given biological system than utilization of a single database or sole reliance on primary literature. PMID:24233784
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Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias; Salanti, Georgia
2018-02-28
To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) ("living" network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided strong evidence against the null hypothesis (P=0.002). The median time to strong evidence against the null hypothesis was 19 years with living network meta-analysis and 23 years with living pairwise meta-analysis (hazard ratio 2.78, 95% confidence interval 1.00 to 7.72, P=0.05). Studies directly comparing the treatments of interest continued to be published for eight comparisons after strong evidence had become evident in network meta-analysis. In comparative effectiveness research, prospectively planned living network meta-analyses produced strong evidence against the null hypothesis more often and earlier than conventional, pairwise meta-analyses. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias
2018-01-01
Abstract Objective To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) (“living” network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Design Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Data sources Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Eligibility criteria for study selection Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Outcomes and analysis Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. Results 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided strong evidence against the null hypothesis (P=0.002). The median time to strong evidence against the null hypothesis was 19 years with living network meta-analysis and 23 years with living pairwise meta-analysis (hazard ratio 2.78, 95% confidence interval 1.00 to 7.72, P=0.05). Studies directly comparing the treatments of interest continued to be published for eight comparisons after strong evidence had become evident in network meta-analysis. Conclusions In comparative effectiveness research, prospectively planned living network meta-analyses produced strong evidence against the null hypothesis more often and earlier than conventional, pairwise meta-analyses. PMID:29490922
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A Solution on Identification and Rearing Files Insmallhold Pig Farming
NASA Astrophysics Data System (ADS)
Xiong, Benhai; Fu, Runting; Lin, Zhaohui; Luo, Qingyao; Yang, Liang
In order to meet government supervision of pork production safety as well as consumeŕs right to know what they buy, this study adopts animal identification, mobile PDA reader, GPRS and other information technologies, and put forward a data collection method to set up rearing files of pig in smallhold pig farming, and designs related metadata structures and its mobile database, and develops a mobile PDA embedded system to collect individual information of pig and uploading into the remote central database, and finally realizes mobile links to the a specific website. The embedded PDA can identify both a special pig bar ear tag appointed by the Ministry of Agricultural and a general data matrix bar ear tag designed by this study by mobile reader, and can record all kinds of inputs data including bacterins, feed additives, animal drugs and even some forbidden medicines and submitted them to the center database through GPRS. At the same time, the remote center database can be maintained by mobile PDA and GPRS, and finally reached pork tracking from its origin to consumption and its tracing through turn-over direction. This study has suggested a feasible technology solution how to set up network pig electronic rearing files involved smallhold pig farming based on farmer and the solution is proved practical through its application in the Tianjińs pork quality traceability system construction. Although some individual techniques have some adverse effects on the system running such as GPRS transmitting speed now, these will be resolved with the development of communication technology. The full implementation of the solution around China will supply technical supports in guaranteeing the quality and safety of pork production supervision and meet consumer demand.
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Critical assessment of human metabolic pathway databases: a stepping stone for future integration
2011-01-01
Background Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to their use as a reference repository. However, so far the various human metabolic networks described by these databases have not been systematically compared and contrasted, nor has the extent to which they differ been quantified. For a researcher using these databases for particular analyses of human metabolism, it is crucial to know the extent of the differences in content and their underlying causes. Moreover, the outcomes of such a comparison are important for ongoing integration efforts. Results We compared the genes, EC numbers and reactions of five frequently used human metabolic pathway databases. The overlap is surprisingly low, especially on reaction level, where the databases agree on 3% of the 6968 reactions they have combined. Even for the well-established tricarboxylic acid cycle the databases agree on only 5 out of the 30 reactions in total. We identified the main causes for the lack of overlap. Importantly, the databases are partly complementary. Other explanations include the number of steps a conversion is described in and the number of possible alternative substrates listed. Missing metabolite identifiers and ambiguous names for metabolites also affect the comparison. Conclusions Our results show that each of the five networks compared provides us with a valuable piece of the puzzle of the complete reconstruction of the human metabolic network. To enable integration of the networks, next to a need for standardizing the metabolite names and identifiers, the conceptual differences between the databases should be resolved. Considerable manual intervention is required to reach the ultimate goal of a unified and biologically accurate model for studying the systems biology of human metabolism. Our comparison provides a stepping stone for such an endeavor. PMID:21999653
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Li, Cheng-Wei; Wang, Wen-Hsin; Chen, Bor-Sen
2016-01-01
Aging is an inevitable part of life for humans, and slowing down the aging process has become a main focus of human endeavor. Here, we applied a systems biology approach to construct protein-protein interaction networks, gene regulatory networks, and epigenetic networks, i.e. genetic and epigenetic networks (GENs), of elderly individuals and young controls. We then compared these GENs to extract aging mechanisms using microarray data in peripheral blood mononuclear cells, microRNA (miRNA) data, and database mining. The core GENs of elderly individuals and young controls were obtained by applying principal network projection to GENs based on Principal Component Analysis. By comparing the core networks, we identified that to overcome the accumulated mutation of genes in the aging process the transcription factor JUN can be activated by stress signals, including the MAPK signaling, T-cell receptor signaling, and neurotrophin signaling pathways through DNA methylation of BTG3, G0S2, and AP2B1 and the regulations of mir-223 let-7d, and mir-130a. We also address the aging mechanisms in old men and women. Furthermore, we proposed that drugs designed to target these DNA methylated genes or miRNAs may delay aging. A multiple drug combination comprising phenylalanine, cholesterol, and palbociclib was finally designed for delaying the aging process. PMID:26895224
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Meta-connectomics: human brain network and connectivity meta-analyses.
Crossley, N A; Fox, P T; Bullmore, E T
2016-04-01
Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.
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Screening the molecular targets of ovarian cancer based on bioinformatics analysis.
Du, Lei; Qian, Xiaolei; Dai, Chenyang; Wang, Lihua; Huang, Ding; Wang, Shuying; Shen, Xiaowei
2015-01-01
Ovarian cancer (OC) is the most lethal gynecologic malignancy. This study aims to explore the molecular mechanisms of OC and identify potential molecular targets for OC treatment. Microarray gene expression data (GSE14407) including 12 normal ovarian surface epithelia samples and 12 OC epithelia samples were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) between 2 kinds of ovarian tissue were identified by using limma package in R language (|log2 fold change| gt;1 and false discovery rate [FDR] lt;0.05). Protein-protein interactions (PPIs) and known OC-related genes were screened from COXPRESdb and GenBank database, respectively. Furthermore, PPI network of top 10 upregulated DEGs and top 10 downregulated DEGs was constructed and visualized through Cytoscape software. Finally, for the genes involved in PPI network, functional enrichment analysis was performed by using DAVID (FDR lt;0.05). In total, 1136 DEGs were identified, including 544 downregulated and 592 upregulated DEGs. Then, PPI network was constructed, and DEGs CDKN2A, MUC1, OGN, ZIC1, SOX17, and TFAP2A interacted with known OC-related genes CDK4, EGFR/JUN, SRC, CLI1, CTNNB1, and TP53, respectively. Moreover, functions about oxygen transport and embryonic development were enriched by the genes involved in the network of downregulated DEGs. We propose that 4 DEGs (OGN, ZIC1, SOX17, and TFAP2A) and 2 functions (oxygen transport and embryonic development) might play a role in the development of OC. These 4 DEGs and known OC-related genes might serve as therapeutic targets for OC. Further studies are required to validate these predictions.
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Designs on a National Research Network.
ERIC Educational Resources Information Center
Walsh, John
1988-01-01
Discusses the addition of the National Aeronautics and Space Administration database to the National Science Foundation's NSFnet data communication network. Outlines the history of databases in the United States and enumerates proposed upgrades from a new Office of Science and Technology policy report. (TW)
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RISE: a database of RNA interactome from sequencing experiments
Gong, Jing; Shao, Di; Xu, Kui
2018-01-01
Abstract We present RISE (http://rise.zhanglab.net), a database of RNA Interactome from Sequencing Experiments. RNA-RNA interactions (RRIs) are essential for RNA regulation and function. RISE provides a comprehensive collection of RRIs that mainly come from recent transcriptome-wide sequencing-based experiments like PARIS, SPLASH, LIGR-seq, and MARIO, as well as targeted studies like RIA-seq, RAP-RNA and CLASH. It also includes interactions aggregated from other primary databases and publications. The RISE database currently contains 328,811 RNA-RNA interactions mainly in human, mouse and yeast. While most existing RNA databases mainly contain interactions of miRNA targeting, notably, more than half of the RRIs in RISE are among mRNA and long non-coding RNAs. We compared different RRI datasets in RISE and found limited overlaps in interactions resolved by different techniques and in different cell lines. It may suggest technology preference and also dynamic natures of RRIs. We also analyzed the basic features of the human and mouse RRI networks and found that they tend to be scale-free, small-world, hierarchical and modular. The analysis may nominate important RNAs or RRIs for further investigation. Finally, RISE provides a Circos plot and several table views for integrative visualization, with extensive molecular and functional annotations to facilitate exploration of biological functions for any RRI of interest. PMID:29040625
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Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K.; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C.; Hoeng, Julia
2015-01-01
With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com PMID:25887162
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Development and Implementation of Kumamoto Technopolis Regional Database T-KIND
NASA Astrophysics Data System (ADS)
Onoue, Noriaki
T-KIND (Techno-Kumamoto Information Network for Data-Base) is a system for effectively searching information of technology, human resources and industries which are necessary to realize Kumamoto Technopolis. It is composed of coded database, image database and LAN inside technoresearch park which is the center of R & D in the Technopolis. It constructs on-line system by networking general-purposed computers, minicomputers, optical disk file systems and so on, and provides the service through public telephone line. Two databases are now available on enterprise information and human resource information. The former covers about 4,000 enterprises, and the latter does about 2,000 persons.
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NASA Astrophysics Data System (ADS)
Possetti, Gustavo Rafael Collere; Coradin, Francelli Klemba; Côcco, Lílian Cristina; Yamamoto, Carlos Itsuo; de Arruda, Lucia Valéria Ramos; Falate, Rosane; Muller, Marcia; Fabris, José Luís
2008-04-01
The liquid fuel quality control is an important issue that brings benefits for the State, for the consumers and for the environment. The conformity analysis, in special for gasoline, demands a rigorous sampling technique among gas stations and other economic agencies, followed by a series of standard physicochemical tests. Such procedures are commonly expensive and time demanding and, moreover, a specialist is often required to carry out the tasks. Such drawbacks make the development of alternative analysis tools an important research field. The fuel refractive index is an additional parameter to help the fuel conformity analysis, besides the prospective optical fiber sensors, which operate like transducers with singular properties. When this parameter is correlated with the sample density, it becomes possible to determine conformity zones that cannot be analytically defined. This work presents an application of artificial neural networks based on Radial Basis Function to determine these zones. A set of 45 gasoline samples, collected in several gas stations and previously analyzed according to the rules of Agência Nacional do Petróleo, Gás Natural e Biocombustíveis, a Brazilian regulatory agency, constituted the database to build two neural networks. The input variables of first network are the samples refractive indices, measured with an Abbe refractometer, and the density of the samples measured with a digital densimeter. For the second network the input variables included, besides the samples densities, the wavelength response of a long-period grating to the samples refractive indices. The used grating was written in an optical fiber using the point-to-point technique by submitting the fiber to consecutive electrical arcs from a splice machine. The output variables of both Radial Basis Function Networks are represented by the conformity status of each sample, according to report of tests carried out following the American Society for Testing and Materials and/or Brazilian Association of Technical Rules standards. A subset of 35 samples, randomly chosen from the database, was used to design and calibrate (train) both networks. The two networks topologies (numbers of Radial Basis Function neurons of the hidden layer and function radius) were built in order to minimize the root mean square error. The subset composed by the other 10 samples was used to validate the final networks architectures. The obtained results have demonstrated that both networks reach a good predictive capability.
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LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET
NASA Astrophysics Data System (ADS)
Amiridis, V.; Marinou, E.; Tsekeri, A.; Wandinger, U.; Schwarz, A.; Giannakaki, E.; Mamouri, R.; Kokkalis, P.; Binietoglou, I.; Solomos, S.; Herekakis, T.; Kazadzis, S.; Gerasopoulos, E.; Proestakis, E.; Kottas, M.; Balis, D.; Papayannis, A.; Kontoes, C.; Kourtidis, K.; Papagiannopoulos, N.; Mona, L.; Pappalardo, G.; Le Rille, O.; Ansmann, A.
2015-07-01
We present LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies), a 3-D multi-wavelength global aerosol and cloud optical database, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. The LIVAS database provides averaged profiles of aerosol optical properties for the potential spaceborne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global database is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent backscatter- and extinction-related Ångström exponents, derived from EARLINET (European Aerosol Research Lidar Network) ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversions are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO backscatter and extinction data corresponding to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud optical database based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for spaceborne lidar performance assessments. The final global data set includes 4-year (1 January 2008-31 December 2011) time-averaged CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) data on a uniform grid of 1° × 1° with the original high vertical resolution of CALIPSO in order to ensure realistic simulations of the atmospheric variability in lidar end-to-end simulations.
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Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.
Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin
2017-06-01
To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.
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A Bayesian network approach to the database search problem in criminal proceedings
2012-01-01
Background The ‘database search problem’, that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method’s graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication. PMID:22849390
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Resource Purpose:The Watershed Information Network is a set of about 30 web pages that are organized by topic. These pages access existing databases like the American Heritage Rivers Services database and Surf Your Watershed. WIN in itself has no data or data sets.
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Extracting patterns of database and software usage from the bioinformatics literature
Duck, Geraint; Nenadic, Goran; Brass, Andy; Robertson, David L.; Stevens, Robert
2014-01-01
Motivation: As a natural consequence of being a computer-based discipline, bioinformatics has a strong focus on database and software development, but the volume and variety of resources are growing at unprecedented rates. An audit of database and software usage patterns could help provide an overview of developments in bioinformatics and community common practice, and comparing the links between resources through time could demonstrate both the persistence of existing software and the emergence of new tools. Results: We study the connections between bioinformatics resources and construct networks of database and software usage patterns, based on resource co-occurrence, that correspond to snapshots of common practice in the bioinformatics community. We apply our approach to pairings of phylogenetics software reported in the literature and argue that these could provide a stepping stone into the identification of scientific best practice. Availability and implementation: The extracted resource data, the scripts used for network generation and the resulting networks are available at http://bionerds.sourceforge.net/networks/ Contact: robert.stevens@manchester.ac.uk PMID:25161253
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Deng, Chen-Hui; Zhang, Guan-Min; Bi, Shan-Shan; Zhou, Tian-Yan; Lu, Wei
2011-07-01
This study is to develop a therapeutic drug monitoring (TDM) network server of tacrolimus for Chinese renal transplant patients, which can facilitate doctor to manage patients' information and provide three levels of predictions. Database management system MySQL was employed to build and manage the database of patients and doctors' information, and hypertext mark-up language (HTML) and Java server pages (JSP) technology were employed to construct network server for database management. Based on the population pharmacokinetic model of tacrolimus for Chinese renal transplant patients, above program languages were used to construct the population prediction and subpopulation prediction modules. Based on Bayesian principle and maximization of the posterior probability function, an objective function was established, and minimized by an optimization algorithm to estimate patient's individual pharmacokinetic parameters. It is proved that the network server has the basic functions for database management and three levels of prediction to aid doctor to optimize the regimen of tacrolimus for Chinese renal transplant patients.
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Diabetic retinopathy screening using deep neural network.
Ramachandran, Nishanthan; Hong, Sheng Chiong; Sime, Mary J; Wilson, Graham A
2017-09-07
There is a burgeoning interest in the use of deep neural network in diabetic retinal screening. To determine whether a deep neural network could satisfactorily detect diabetic retinopathy that requires referral to an ophthalmologist from a local diabetic retinal screening programme and an international database. Retrospective audit. Diabetic retinal photos from Otago database photographed during October 2016 (485 photos), and 1200 photos from Messidor international database. Receiver operating characteristic curve to illustrate the ability of a deep neural network to identify referable diabetic retinopathy (moderate or worse diabetic retinopathy or exudates within one disc diameter of the fovea). Area under the receiver operating characteristic curve, sensitivity and specificity. For detecting referable diabetic retinopathy, the deep neural network had an area under receiver operating characteristic curve of 0.901 (95% confidence interval 0.807-0.995), with 84.6% sensitivity and 79.7% specificity for Otago and 0.980 (95% confidence interval 0.973-0.986), with 96.0% sensitivity and 90.0% specificity for Messidor. This study has shown that a deep neural network can detect referable diabetic retinopathy with sensitivities and specificities close to or better than 80% from both an international and a domestic (New Zealand) database. We believe that deep neural networks can be integrated into community screening once they can successfully detect both diabetic retinopathy and diabetic macular oedema. © 2017 Royal Australian and New Zealand College of Ophthalmologists.
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A search map for organic additives and solvents applicable in high-voltage rechargeable batteries.
Park, Min Sik; Park, Insun; Kang, Yoon-Sok; Im, Dongmin; Doo, Seok-Gwang
2016-09-29
Chemical databases store information such as molecular formulas, chemical structures, and the physical and chemical properties of compounds. Although the massive databases of organic compounds exist, the search of target materials is constrained by a lack of physical and chemical properties necessary for specific applications. With increasing interest in the development of energy storage systems such as high-voltage rechargeable batteries, it is critical to find new electrolytes efficiently. Here we build a search map to screen organic additives and solvents with novel core and functional groups, and thus establish a database of electrolytes to identify the most promising electrolyte for high-voltage rechargeable batteries. This search map is generated from MAssive Molecular Map BUilder (MAMMBU) by combining a high-throughput quantum chemical simulation with an artificial neural network algorithm. MAMMBU is designed for predicting the oxidation and reduction potentials of organic compounds existing in the massive organic compound database, PubChem. We develop a search map composed of ∼1 000 000 redox potentials and elucidate the quantitative relationship between the redox potentials and functional groups. Finally, we screen a quinoxaline compound for an anode additive and apply it to electrolytes and improve the capacity retention from 64.3% to 80.8% near 200 cycles for a lithium ion battery in experiments.
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Inoue, J
1991-12-01
When occupational health personnel, especially occupational physicians search bibliographies, they usually have to search bibliographies by themselves. Also, if a library is not available because of the location of their work place, they might have to rely on online databases. Although there are many commercial databases in the world, people who seldom use them, will have problems with on-line searching, such as user-computer interface, keywords, and so on. The present study surveyed the best bibliographic searching system in the field of occupational medicine by questionnaire through the use of DIALOG OnDisc MEDLINE as a commercial database. In order to ascertain the problems involved in determining the best bibliographic searching system, a prototype bibliographic searching system was constructed and then evaluated. Finally, solutions for the problems were discussed. These led to the following conclusions: to construct the best bibliographic searching system at the present time, 1) a concept of micro-to-mainframe links (MML) is needed for the computer hardware network; 2) multi-lingual font standards and an excellent common user-computer interface are needed for the computer software; 3) a short course and education of database management systems, and support of personal information processing for retrieved data are necessary for the practical use of the system.
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Gioutlakis, Aris; Klapa, Maria I.
2017-01-01
It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes. PMID:29023571
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NASA Technical Reports Server (NTRS)
Dobinson, E.
1982-01-01
General requirements for an information management system for the deep space network (DSN) are examined. A concise review of available database management system technology is presented. It is recommended that a federation of logically decentralized databases be implemented for the Network Information Management System of the DSN. Overall characteristics of the federation are specified, as well as reasons for adopting this approach.
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Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.
Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong
2015-01-01
In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.
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ODIN. Online Database Information Network: ODIN Policy & Procedure Manual.
ERIC Educational Resources Information Center
Townley, Charles T.; And Others
Policies and procedures are outlined for the Online Database Information Network (ODIN), a cooperative of libraries in south-central Pennsylvania, which was organized to improve library services through technology. The first section covers organization and goals, members, and responsibilities of the administrative council and libraries. Patrons…
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An online database for informing ecological network models: http://kelpforest.ucsc.edu.
Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H; Tinker, Martin T; Black, August; Caselle, Jennifer E; Hoban, Michael; Malone, Dan; Iles, Alison
2014-01-01
Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).
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An Online Database for Informing Ecological Network Models: http://kelpforest.ucsc.edu
Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H.; Tinker, Martin T.; Black, August; Caselle, Jennifer E.; Hoban, Michael; Malone, Dan; Iles, Alison
2014-01-01
Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui). PMID:25343723
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An online database for informing ecological network models: http://kelpforest.ucsc.edu
Beas-Luna, Rodrigo; Tinker, M. Tim; Novak, Mark; Carr, Mark H.; Black, August; Caselle, Jennifer E.; Hoban, Michael; Malone, Dan; Iles, Alison C.
2014-01-01
Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).
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Vehicle-network defensive aids suite
NASA Astrophysics Data System (ADS)
Rapanotti, John
2005-05-01
Defensive Aids Suites (DAS) developed for vehicles can be extended to the vehicle network level. The vehicle network, typically comprising four platoon vehicles, will benefit from improved communications and automation based on low latency response to threats from a flexible, dynamic, self-healing network environment. Improved DAS performance and reliability relies on four complementary sensor technologies including: acoustics, visible and infrared optics, laser detection and radar. Long-range passive threat detection and avoidance is based on dual-purpose optics, primarily designed for manoeuvring, targeting and surveillance, combined with dazzling, obscuration and countermanoeuvres. Short-range active armour is based on search and track radar and intercepting grenades to defeat the threat. Acoustic threat detection increases the overall robustness of the DAS and extends the detection range to include small calibers. Finally, detection of active targeting systems is carried out with laser and radar warning receivers. Synthetic scene generation will provide the integrated environment needed to investigate, develop and validate these new capabilities. Computer generated imagery, based on validated models and an acceptable set of benchmark vignettes, can be used to investigate and develop fieldable sensors driven by real-time algorithms and countermeasure strategies. The synthetic scene environment will be suitable for sensor and countermeasure development in hardware-in-the-loop simulation. The research effort focuses on two key technical areas: a) computing aspects of the synthetic scene generation and b) and development of adapted models and databases. OneSAF is being developed for research and development, in addition to the original requirement of Simulation and Modelling for Acquisition, Rehearsal, Requirements and Training (SMARRT), and is becoming useful as a means for transferring technology to other users, researchers and contractors. This procedure eliminates the need to construct ad hoc models and databases. The vehicle network can be modelled phenomenologically until more information is available. These concepts and approach will be discussed in the paper.
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Proteome reference map and regulation network of neonatal rat cardiomyocyte
Li, Zi-jian; Liu, Ning; Han, Qi-de; Zhang, You-yi
2011-01-01
Aim: To study and establish a proteome reference map and regulation network of neonatal rat cardiomyocyte. Methods: Cultured cardiomyocytes of neonatal rats were used. All proteins expressed in the cardiomyocytes were separated and identified by two-dimensional polyacrylamide gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). Biological networks and pathways of the neonatal rat cardiomyocytes were analyzed using the Ingenuity Pathway Analysis (IPA) program (www.ingenuity.com). A 2-DE database was made accessible on-line by Make2ddb package on a web server. Results: More than 1000 proteins were separated on 2D gels, and 148 proteins were identified. The identified proteins were used for the construction of an extensible markup language-based database. Biological networks and pathways were constructed to analyze the functions associate with cardiomyocyte proteins in the database. The 2-DE database of rat cardiomyocyte proteins can be accessed at http://2d.bjmu.edu.cn. Conclusion: A proteome reference map and regulation network of the neonatal rat cardiomyocytes have been established, which may serve as an international platform for storage, analysis and visualization of cardiomyocyte proteomic data. PMID:21841810
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PathCase-SB architecture and database design
2011-01-01
Background Integration of metabolic pathways resources and regulatory metabolic network models, and deploying new tools on the integrated platform can help perform more effective and more efficient systems biology research on understanding the regulation in metabolic networks. Therefore, the tasks of (a) integrating under a single database environment regulatory metabolic networks and existing models, and (b) building tools to help with modeling and analysis are desirable and intellectually challenging computational tasks. Description PathCase Systems Biology (PathCase-SB) is built and released. The PathCase-SB database provides data and API for multiple user interfaces and software tools. The current PathCase-SB system provides a database-enabled framework and web-based computational tools towards facilitating the development of kinetic models for biological systems. PathCase-SB aims to integrate data of selected biological data sources on the web (currently, BioModels database and KEGG), and to provide more powerful and/or new capabilities via the new web-based integrative framework. This paper describes architecture and database design issues encountered in PathCase-SB's design and implementation, and presents the current design of PathCase-SB's architecture and database. Conclusions PathCase-SB architecture and database provide a highly extensible and scalable environment with easy and fast (real-time) access to the data in the database. PathCase-SB itself is already being used by researchers across the world. PMID:22070889
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ERIC Educational Resources Information Center
Williamson, Ben
2015-01-01
This article examines the emergence of "digital governance" in public education in England. Drawing on and combining concepts from software studies, policy and political studies, it identifies some specific approaches to digital governance facilitated by network-based communications and database-driven information processing software…
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National Transportation Atlas Databases : 2002
DOT National Transportation Integrated Search
2002-01-01
The National Transportation Atlas Databases 2002 (NTAD2002) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2010
DOT National Transportation Integrated Search
2010-01-01
The National Transportation Atlas Databases 2010 (NTAD2010) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2006
DOT National Transportation Integrated Search
2006-01-01
The National Transportation Atlas Databases 2006 (NTAD2006) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2005
DOT National Transportation Integrated Search
2005-01-01
The National Transportation Atlas Databases 2005 (NTAD2005) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2008
DOT National Transportation Integrated Search
2008-01-01
The National Transportation Atlas Databases 2008 (NTAD2008) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2003
DOT National Transportation Integrated Search
2003-01-01
The National Transportation Atlas Databases 2003 (NTAD2003) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2004
DOT National Transportation Integrated Search
2004-01-01
The National Transportation Atlas Databases 2004 (NTAD2004) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2009
DOT National Transportation Integrated Search
2009-01-01
The National Transportation Atlas Databases 2009 (NTAD2009) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2007
DOT National Transportation Integrated Search
2007-01-01
The National Transportation Atlas Databases 2007 (NTAD2007) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2012
DOT National Transportation Integrated Search
2012-01-01
The National Transportation Atlas Databases 2012 (NTAD2012) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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National Transportation Atlas Databases : 2011
DOT National Transportation Integrated Search
2011-01-01
The National Transportation Atlas Databases 2011 (NTAD2011) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...
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Ensemble Deep Learning for Biomedical Time Series Classification
2016-01-01
Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost. PMID:27725828
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Palmprint verification using Lagrangian decomposition and invariant interest points
NASA Astrophysics Data System (ADS)
Gupta, P.; Rattani, A.; Kisku, D. R.; Hwang, C. J.; Sing, J. K.
2011-06-01
This paper presents a palmprint based verification system using SIFT features and Lagrangian network graph technique. We employ SIFT for feature extraction from palmprint images whereas the region of interest (ROI) which has been extracted from wide palm texture at the preprocessing stage, is considered for invariant points extraction. Finally, identity is established by finding permutation matrix for a pair of reference and probe palm graphs drawn on extracted SIFT features. Permutation matrix is used to minimize the distance between two graphs. The propsed system has been tested on CASIA and IITK palmprint databases and experimental results reveal the effectiveness and robustness of the system.
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Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia
2015-01-01
With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.
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A pre-trained convolutional neural network based method for thyroid nodule diagnosis.
Ma, Jinlian; Wu, Fa; Zhu, Jiang; Xu, Dong; Kong, Dexing
2017-01-01
In ultrasound images, most thyroid nodules are in heterogeneous appearances with various internal components and also have vague boundaries, so it is difficult for physicians to discriminate malignant thyroid nodules from benign ones. In this study, we propose a hybrid method for thyroid nodule diagnosis, which is a fusion of two pre-trained convolutional neural networks (CNNs) with different convolutional layers and fully-connected layers. Firstly, the two networks pre-trained with ImageNet database are separately trained. Secondly, we fuse feature maps learned by trained convolutional filters, pooling and normalization operations of the two CNNs. Finally, with the fused feature maps, a softmax classifier is used to diagnose thyroid nodules. The proposed method is validated on 15,000 ultrasound images collected from two local hospitals. Experiment results show that the proposed CNN based methods can accurately and effectively diagnose thyroid nodules. In addition, the fusion of the two CNN based models lead to significant performance improvement, with an accuracy of 83.02%±0.72%. These demonstrate the potential clinical applications of this method. Copyright © 2016 Elsevier B.V. All rights reserved.
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Virtual reality or real virtuality: the space of flows and nursing practice.
Barnes, Lynne; Rudge, Trudy
2005-12-01
The use of virtual environments for the provision of health-care is on the increase, and with each new development brings debates about their impact on care, nursing and nursing practice. Such environments offer opportunities for extending care and improvements in communication. Others believe these developments threaten aspects of nursing they hold sacrosanct. This paper explores the development of an assemblage of computer networks, databases, information systems, software programs and management systems that together work to manage health-care in Australia, namely casemix. We contend that spatial theories on network society show how this assemblage co-ordinates and operates to manage care. We discuss how this assemblage affects care and suggest that changes in organisation may be a part of the shift in how bodily organisation occurs more generally, but more specifically in health-care. We also suggest how nurses are enrolled in and by such networks, leading to transformation in nurses' practices. Finally, we argue that using spatial forms of analysis allows an interpretation of such assemblages that may account for their strengths and their shortcomings.
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Network portal: a database for storage, analysis and visualization of biological networks
Turkarslan, Serdar; Wurtmann, Elisabeth J.; Wu, Wei-Ju; Jiang, Ning; Bare, J. Christopher; Foley, Karen; Reiss, David J.; Novichkov, Pavel; Baliga, Nitin S.
2014-01-01
The ease of generating high-throughput data has enabled investigations into organismal complexity at the systems level through the inference of networks of interactions among the various cellular components (genes, RNAs, proteins and metabolites). The wider scientific community, however, currently has limited access to tools for network inference, visualization and analysis because these tasks often require advanced computational knowledge and expensive computing resources. We have designed the network portal (http://networks.systemsbiology.net) to serve as a modular database for the integration of user uploaded and public data, with inference algorithms and tools for the storage, visualization and analysis of biological networks. The portal is fully integrated into the Gaggle framework to seamlessly exchange data with desktop and web applications and to allow the user to create, save and modify workspaces, and it includes social networking capabilities for collaborative projects. While the current release of the database contains networks for 13 prokaryotic organisms from diverse phylogenetic clades (4678 co-regulated gene modules, 3466 regulators and 9291 cis-regulatory motifs), it will be rapidly populated with prokaryotic and eukaryotic organisms as relevant data become available in public repositories and through user input. The modular architecture, simple data formats and open API support community development of the portal. PMID:24271392
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[Research on Zhejiang blood information network and management system].
Yan, Li-Xing; Xu, Yan; Meng, Zhong-Hua; Kong, Chang-Hong; Wang, Jian-Min; Jin, Zhen-Liang; Wu, Shi-Ding; Chen, Chang-Shui; Luo, Ling-Fei
2007-02-01
This research was aimed to develop the first level blood information centralized database and real time communication network at a province area in China. Multiple technology like local area network database separate operation, real time data concentration and distribution mechanism, allopatric backup, and optical fiber virtual private network (VPN) were used. As a result, the blood information centralized database and management system were successfully constructed, which covers all the Zhejiang province, and the real time exchange of blood data was realised. In conclusion, its implementation promote volunteer blood donation and ensure the blood safety in Zhejiang, especially strengthen the quick response to public health emergency. This project lays the first stone of centralized test and allotment among blood banks in Zhejiang, and can serve as a reference of contemporary blood bank information systems in China.
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bioDBnet - Biological Database Network
bioDBnet is a comprehensive resource of most of the biological databases available from different sites like NCBI, Uniprot, EMBL, Ensembl, Affymetrix. It provides a queryable interface to all the databases available, converts identifiers from one database into another and generates comprehensive reports.
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Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.
Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui
2017-01-01
The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.
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How to maintain blood supply during computer network breakdown: a manual backup system.
Zeiler, T; Slonka, J; Bürgi, H R; Kretschmer, V
2000-12-01
Electronic data management systems using computer network systems and client/server architecture are increasingly used in laboratories and transfusion services. Severe problems arise if there is no network access to the database server and critical functions are not available. We describe a manual backup system (MBS) developed to maintain the delivery of blood products to patients in a hospital transfusion service in case of a computer network breakdown. All data are kept on a central SQL database connected to peripheral workstations in a local area network (LAN). Request entry from wards is performed via machine-readable request forms containing self-adhesive specimen labels with barcodes for test tubes. Data entry occurs on-line by bidirectional automated systems or off-line manually. One of the workstations in the laboratory contains a second SQL database which is frequently and incrementally updated. This workstation is run as a stand-alone, read-only database if the central SQL database is not available. In case of a network breakdown, the time-graded MBS is launched. Patient data, requesting ward and ordered tests/requests, are photocopied through a template from the request forms on special MBS worksheets serving as laboratory journal for manual processing and result report (a copy is left in the laboratory). As soon as the network is running again the data from the off-line period are entered into the primary SQL server. The MBS was successfully used at several occasions. The documentation of a 90-min breakdown period is presented in detail. Additional work resulted from the copy work and the belated manual data entry after restoration of the system. There was no delay in issue of blood products or result reporting. The backup system described has been proven to be simple, quick and safe to maintain urgent blood supply and distribution of laboratory results in case of unexpected network breakdown.
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The Fragment Network: A Chemistry Recommendation Engine Built Using a Graph Database.
Hall, Richard J; Murray, Christopher W; Verdonk, Marcel L
2017-07-27
The hit validation stage of a fragment-based drug discovery campaign involves probing the SAR around one or more fragment hits. This often requires a search for similar compounds in a corporate collection or from commercial suppliers. The Fragment Network is a graph database that allows a user to efficiently search chemical space around a compound of interest. The result set is chemically intuitive, naturally grouped by substitution pattern and meaningfully sorted according to the number of observations of each transformation in medicinal chemistry databases. This paper describes the algorithms used to construct and search the Fragment Network and provides examples of how it may be used in a drug discovery context.
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CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks
Baumbach, Jan
2007-01-01
Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to predict putative contradictions or further gene regulatory interactions. Furthermore, it integrates protein clusters by means of heuristically solving the weighted graph cluster editing problem. In addition, it provides Web Service based access to up to date gene annotation data from GenDB. Conclusion The release 4.0 of CoryneRegNet is a comprehensive system for the integrated analysis of procaryotic gene regulatory networks. It is a versatile systems biology platform to support the efficient and large-scale analysis of transcriptional regulation of gene expression in microorganisms. It is publicly available at . PMID:17986320
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NASA Astrophysics Data System (ADS)
Brantley, S.; Pollak, J.
2016-12-01
The Shale Network's extensive database of water quality observations in the Marcellus Shale region enables educational experiences about the potential impacts of resource extraction and energy production with real data. Through tools that are open source and free to use, interested parties can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. With these tools and data, the Shale Network team has engaged high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in educational settings, and the resources available to learn more.
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Semantic encoding of relational databases in wireless networks
NASA Astrophysics Data System (ADS)
Benjamin, David P.; Walker, Adrian
2005-03-01
Semantic Encoding is a new, patented technology that greatly increases the speed of transmission of distributed databases over networks, especially over ad hoc wireless networks, while providing a novel method of data security. It reduces bandwidth consumption and storage requirements, while speeding up query processing, encryption and computation of digital signatures. We describe the application of Semantic Encoding in a wireless setting and provide an example of its operation in which a compression of 290:1 would be achieved.
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International Soil Carbon Network (ISCN) Database v3-1
Nave, Luke [University of Michigan] (ORCID:0000000182588335); Johnson, Kris [USDA-Forest Service; van Ingen, Catharine [Microsoft Research; Agarwal, Deborah [Lawrence Berkeley National Laboratory] (ORCID:0000000150452396); Humphrey, Marty [University of Virginia; Beekwilder, Norman [University of Virginia
2016-01-01
The ISCN is an international scientific community devoted to the advancement of soil carbon research. The ISCN manages an open-access, community-driven soil carbon database. This is version 3-1 of the ISCN Database, released in December 2015. It gathers 38 separate dataset contributions, totalling 67,112 sites with data from 71,198 soil profiles and 431,324 soil layers. For more information about the ISCN, its scientific community and resources, data policies and partner networks visit: http://iscn.fluxdata.org/.
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Disease gene classification with metagraph representations.
Kircali Ata, Sezin; Fang, Yuan; Wu, Min; Li, Xiao-Li; Xiao, Xiaokui
2017-12-01
Protein-protein interaction (PPI) networks play an important role in studying the functional roles of proteins, including their association with diseases. However, protein interaction networks are not sufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To complement and enrich PPI networks, we propose to exploit biological properties of individual proteins. More specifically, we integrate keywords describing protein properties into the PPI network, and construct a novel PPI-Keywords (PPIK) network consisting of both proteins and keywords as two different types of nodes. As disease proteins tend to have a similar topological characteristics on the PPIK network, we further propose to represent proteins with metagraphs. Different from a traditional network motif or subgraph, a metagraph can capture a particular topological arrangement involving the interactions/associations between both proteins and keywords. Based on the novel metagraph representations for proteins, we further build classifiers for disease protein classification through supervised learning. Our experiments on three different PPI databases demonstrate that the proposed method consistently improves disease protein prediction across various classifiers, by 15.3% in AUC on average. It outperforms the baselines including the diffusion-based methods (e.g., RWR) and the module-based methods by 13.8-32.9% for overall disease protein prediction. For predicting breast cancer genes, it outperforms RWR, PRINCE and the module-based baselines by 6.6-14.2%. Finally, our predictions also turn out to have better correlations with literature findings from PubMed. Copyright © 2017 Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Brantley, S.; Brazil, L.
2017-12-01
The Shale Network's extensive database of water quality observations enables educational experiences about the potential impacts of resource extraction with real data. Through tools that are open source and free to use, researchers, educators, and citizens can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. Thus far, these tools and data have been used to engage high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in developing lesson plans, and the resources available to learn more.
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The NASA Fireball Network Database
NASA Technical Reports Server (NTRS)
Moser, Danielle E.
2011-01-01
The NASA Meteoroid Environment Office (MEO) has been operating an automated video fireball network since late-2008. Since that time, over 1,700 multi-station fireballs have been observed. A database containing orbital data and trajectory information on all these events has recently been compiled and is currently being mined for information. Preliminary results are presented here.
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Distributed Structure-Searchable Toxicity (DSSTox) Database Network: Making Public Toxicity Data Resources More Accessible and U sable for Data Exploration and SAR Development
Many sources of public toxicity data are not currently linked to chemical structure, are not ... -
PharmDB-K: Integrated Bio-Pharmacological Network Database for Traditional Korean Medicine
Lee, Ji-Hyun; Park, Kyoung Mii; Han, Dong-Jin; Bang, Nam Young; Kim, Do-Hee; Na, Hyeongjin; Lim, Semi; Kim, Tae Bum; Kim, Dae Gyu; Kim, Hyun-Jung; Chung, Yeonseok; Sung, Sang Hyun; Surh, Young-Joon; Kim, Sunghoon; Han, Byung Woo
2015-01-01
Despite the growing attention given to Traditional Medicine (TM) worldwide, there is no well-known, publicly available, integrated bio-pharmacological Traditional Korean Medicine (TKM) database for researchers in drug discovery. In this study, we have constructed PharmDB-K, which offers comprehensive information relating to TKM-associated drugs (compound), disease indication, and protein relationships. To explore the underlying molecular interaction of TKM, we integrated fourteen different databases, six Pharmacopoeias, and literature, and established a massive bio-pharmacological network for TKM and experimentally validated some cases predicted from the PharmDB-K analyses. Currently, PharmDB-K contains information about 262 TKMs, 7,815 drugs, 3,721 diseases, 32,373 proteins, and 1,887 side effects. One of the unique sets of information in PharmDB-K includes 400 indicator compounds used for standardization of herbal medicine. Furthermore, we are operating PharmDB-K via phExplorer (a network visualization software) and BioMart (a data federation framework) for convenient search and analysis of the TKM network. Database URL: http://pharmdb-k.org, http://biomart.i-pharm.org. PMID:26555441
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NASA Technical Reports Server (NTRS)
Brunstrom, Anna; Leutenegger, Scott T.; Simha, Rahul
1995-01-01
Traditionally, allocation of data in distributed database management systems has been determined by off-line analysis and optimization. This technique works well for static database access patterns, but is often inadequate for frequently changing workloads. In this paper we address how to dynamically reallocate data for partionable distributed databases with changing access patterns. Rather than complicated and expensive optimization algorithms, a simple heuristic is presented and shown, via an implementation study, to improve system throughput by 30 percent in a local area network based system. Based on artificial wide area network delays, we show that dynamic reallocation can improve system throughput by a factor of two and a half for wide area networks. We also show that individual site load must be taken into consideration when reallocating data, and provide a simple policy that incorporates load in the reallocation decision.
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Consensus and conflict cards for metabolic pathway databases
2013-01-01
Background The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. Results We introduce the concept of Consensus and Conflict Cards (C2Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C2CardsHuman, as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. Conclusions C2Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C2Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement. PMID:23803311
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Consensus and conflict cards for metabolic pathway databases.
Stobbe, Miranda D; Swertz, Morris A; Thiele, Ines; Rengaw, Trebor; van Kampen, Antoine H C; Moerland, Perry D
2013-06-26
The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. We introduce the concept of Consensus and Conflict Cards (C₂Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C₂Cards(Human), as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. C₂Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C₂Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement.
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A proposal of fuzzy connective with learning function and its application to fuzzy retrieval system
NASA Technical Reports Server (NTRS)
Hayashi, Isao; Naito, Eiichi; Ozawa, Jun; Wakami, Noboru
1993-01-01
A new fuzzy connective and a structure of network constructed by fuzzy connectives are proposed to overcome a drawback of conventional fuzzy retrieval systems. This network represents a retrieval query and the fuzzy connectives in networks have a learning function to adjust its parameters by data from a database and outputs of a user. The fuzzy retrieval systems employing this network are also constructed. Users can retrieve results even with a query whose attributes do not exist in a database schema and can get satisfactory results for variety of thinkings by learning function.
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Xia, Kai; Dong, Dong; Han, Jing-Dong J
2006-01-01
Background Although protein-protein interaction (PPI) networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking. Results By applying a probabilistic model, we integrated 27 heterogeneous genomic, proteomic and functional annotation datasets to predict PPI networks in human. In addition to previously studied data types, we show that phenotypic distances and genetic interactions can also be integrated to predict PPIs. We further built an easy-to-use, updatable integrated PPI database, the Integrated Network Database (IntNetDB) online, to provide automatic prediction and visualization of PPI network among genes of interest. The networks can be visualized in SVG (Scalable Vector Graphics) format for zooming in or out. IntNetDB also provides a tool to extract topologically highly connected network neighborhoods from a specific network for further exploration and research. Using the MCODE (Molecular Complex Detections) algorithm, 190 such neighborhoods were detected among all the predicted interactions. The predicted PPIs can also be mapped to worm, fly and mouse interologs. Conclusion IntNetDB includes 180,010 predicted protein-protein interactions among 9,901 human proteins and represents a useful resource for the research community. Our study has increased prediction coverage by five-fold. IntNetDB also provides easy-to-use network visualization and analysis tools that allow biological researchers unfamiliar with computational biology to access and analyze data over the internet. The web interface of IntNetDB is freely accessible at . Visualization requires Mozilla version 1.8 (or higher) or Internet Explorer with installation of SVGviewer. PMID:17112386
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Design of special purpose database for credit cooperation bank business processing network system
NASA Astrophysics Data System (ADS)
Yu, Yongling; Zong, Sisheng; Shi, Jinfa
2011-12-01
With the popularization of e-finance in the city, the construction of e-finance is transfering to the vast rural market, and quickly to develop in depth. Developing the business processing network system suitable for the rural credit cooperative Banks can make business processing conveniently, and have a good application prospect. In this paper, We analyse the necessity of adopting special purpose distributed database in Credit Cooperation Band System, give corresponding distributed database system structure , design the specical purpose database and interface technology . The application in Tongbai Rural Credit Cooperatives has shown that system has better performance and higher efficiency.
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User's Manual for the New England Water-Use Data System (NEWUDS)
Horn, Marilee A.
2003-01-01
Water is used in a variety of ways that need to be understood for effective management of water resources. Water-use activities need to be categorized and included in a database management system to understand current water uses and to provide information to water-resource management policy decisionmakers. The New England Water-Use Data System (NEWUDS) is a complex database developed to store water-use information that allows water to be tracked from a point of water-use activity (called a 'Site'), such as withdrawal from a resource (reservoir or aquifer), to a second Site, such as distribution to a user (business or irrigator). NEWUDS conceptual model consists of 10 core entities: system, owner, address, location, site, data source, resource, conveyance, transaction/rate, and alias, with tables available to store user-defined details. Three components--site (with both a From Site and a To Site), a conveyance that connects them, and a transaction/rate associated with the movement of water over a specific time interval form the core of the basic NEWUDS network model. The most important step in correctly translating real-world water-use activities into a storable format in NEWUDS depends on choosing the appropriate sites and linking them correctly in a network to model the flow of water from the initial From Site to the final To Site. Ten water-use networks representing real-world activities are described--three withdrawal networks, three return networks, two user networks, two complex community-system networks. Ten case studies of water use, one for each network, also are included in this manual to illustrate how to compile, store, and retrieve the appropriate data. The sequence of data entry into tables is critical because there are many foreign keys. The recommended core entity sequence is (1) system, (2) owner, (3) address, (4) location, (5) site, (6) data source, (7) resource, (8) conveyance, (9) transaction, and (10) rate; with (11) alias and (12) user-defined detail subject areas populated as needed. After each step in data entry, quality-assurance queries should be run to ensure the data are correctly entered so that it can be retrieved accurately. The point of data storage is retrieval. Several retrieval queries that focus on retrieving only relevant data to specific questions are presented in this manual as examples for the NEWUDS user.
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The Data Base and Decision Making in Public Schools.
ERIC Educational Resources Information Center
Hedges, William D.
1984-01-01
Describes generic types of databases--file management systems, relational database management systems, and network/hierarchical database management systems--with their respective strengths and weaknesses; discusses factors to be considered in determining whether a database is desirable; and provides evaluative criteria for use in choosing…
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A Hybrid Data Mining Approach for Credit Card Usage Behavior Analysis
NASA Astrophysics Data System (ADS)
Tsai, Chieh-Yuan
Credit card is one of the most popular e-payment approaches in current online e-commerce. To consolidate valuable customers, card issuers invest a lot of money to maintain good relationship with their customers. Although several efforts have been done in studying card usage motivation, few researches emphasize on credit card usage behavior analysis when time periods change from t to t+1. To address this issue, an integrated data mining approach is proposed in this paper. First, the customer profile and their transaction data at time period t are retrieved from databases. Second, a LabelSOM neural network groups customers into segments and identify critical characteristics for each group. Third, a fuzzy decision tree algorithm is used to construct usage behavior rules of interesting customer groups. Finally, these rules are used to analysis the behavior changes between time periods t and t+1. An implementation case using a practical credit card database provided by a commercial bank in Taiwan is illustrated to show the benefits of the proposed framework.
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Web interfaces to relational databases
NASA Technical Reports Server (NTRS)
Carlisle, W. H.
1996-01-01
This reports on a project to extend the capabilities of a Virtual Research Center (VRC) for NASA's Advanced Concepts Office. The work was performed as part of NASA's 1995 Summer Faculty Fellowship program and involved the development of a prototype component of the VRC - a database system that provides data creation and access services within a room of the VRC. In support of VRC development, NASA has assembled a laboratory containing the variety of equipment expected to be used by scientists within the VRC. This laboratory consists of the major hardware platforms, SUN, Intel, and Motorola processors and their most common operating systems UNIX, Windows NT, Windows for Workgroups, and Macintosh. The SPARC 20 runs SUN Solaris 2.4, an Intel Pentium runs Windows NT and is installed on a different network from the other machines in the laboratory, a Pentium PC runs Windows for Workgroups, two Intel 386 machines run Windows 3.1, and finally, a PowerMacintosh and a Macintosh IIsi run MacOS.
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Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J; Wurtele, Eve Syrkin
2013-04-01
Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.
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Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J.
2013-01-01
Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publically available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these dataset with transcriptomic data to create hypotheses concerning specialized metabolism that generates the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software. PMID:23447050
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ERIC Educational Resources Information Center
RESNA: Association for the Advancement of Rehabilitation Technology, Washington, DC.
This resource directory provides a selective listing of electronic networks, online databases, and bulletin boards that highlight technology-related services and products. For each resource, the following information is provided: name, address, and telephone number; description; target audience; hardware/software needs to access the system;…
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ERIC Educational Resources Information Center
Jukic, Nenad; Gray, Paul
2008-01-01
This paper describes the value that information systems faculty and students in classes dealing with database management, data warehousing, decision support systems, and related topics, could derive from the use of the Teradata University Network (TUN), a free comprehensive web-portal. A detailed overview of TUN functionalities and content is…
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Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks
Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui
2017-01-01
The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways. PMID:29049295
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47 CFR 52.101 - General definitions.
Code of Federal Regulations, 2013 CFR
2013-10-01
... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...
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47 CFR 52.101 - General definitions.
Code of Federal Regulations, 2011 CFR
2011-10-01
... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...
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47 CFR 52.101 - General definitions.
Code of Federal Regulations, 2014 CFR
2014-10-01
... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...
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47 CFR 52.101 - General definitions.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...
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47 CFR 52.101 - General definitions.
Code of Federal Regulations, 2012 CFR
2012-10-01
... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...
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Carranza, Noemí; Ramos, Victoria; Lizana, Francisca G; García, Jorge; del Pozo, Alejando; Monteagudo, José Luis
2010-09-01
The objective of this study was to determine already reported cases of transmission/reception failure and interferences to evaluate the safety and security of the new mobile home telemedicine systems. The literature published in the last 10 years (1998-2009) has been reviewed, by searching in several databases. Searches on transmission effectiveness and electromagnetic compatibility were made manually through journals, conference proceedings, and also the healthcare technology assessment agencies' Web pages. Search strategies developed through electronic databases and manual search identified a total of 886 references, with 44 finally being included in the results. They have been divided by technology in the transmission/reception effectiveness studies, and according to the type of medical device in the case of electromagnetic interferences studies. The study reveals that there are numerous publications on telemedicine and home-monitoring systems using wireless networks. However, literature on effectiveness in terms of connectivity and transmission problems and electromagnetic interferences is limited. From the collected studies, it can be concluded that there are transmission failures, low-coverage areas, errors in the transmission of packets, and so on. Moreover, cases of serious interferences in medical instruments have also been reported. These facts highlight the lack of studies and specific recommendations to be followed in the implementation of biomonitoring systems in domestic environments using wireless networks.
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CycADS: an annotation database system to ease the development and update of BioCyc databases
Vellozo, Augusto F.; Véron, Amélie S.; Baa-Puyoulet, Patrice; Huerta-Cepas, Jaime; Cottret, Ludovic; Febvay, Gérard; Calevro, Federica; Rahbé, Yvan; Douglas, Angela E.; Gabaldón, Toni; Sagot, Marie-France; Charles, Hubert; Colella, Stefano
2011-01-01
In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http://www.cycadsys.org PMID:21474551
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BrainMap VBM: An environment for structural meta-analysis.
Vanasse, Thomas J; Fox, P Mickle; Barron, Daniel S; Robertson, Michaela; Eickhoff, Simon B; Lancaster, Jack L; Fox, Peter T
2018-05-02
The BrainMap database is a community resource that curates peer-reviewed, coordinate-based human neuroimaging literature. By pairing the results of neuroimaging studies with their relevant meta-data, BrainMap facilitates coordinate-based meta-analysis (CBMA) of the neuroimaging literature en masse or at the level of experimental paradigm, clinical disease, or anatomic location. Initially dedicated to the functional, task-activation literature, BrainMap is now expanding to include voxel-based morphometry (VBM) studies in a separate sector, titled: BrainMap VBM. VBM is a whole-brain, voxel-wise method that measures significant structural differences between or within groups which are reported as standardized, peak x-y-z coordinates. Here we describe BrainMap VBM, including the meta-data structure, current data volume, and automated reverse inference functions (region-to-disease profile) of this new community resource. CBMA offers a robust methodology for retaining true-positive and excluding false-positive findings across studies in the VBM literature. As with BrainMap's functional database, BrainMap VBM may be synthesized en masse or at the level of clinical disease or anatomic location. As a use-case scenario for BrainMap VBM, we illustrate a trans-diagnostic data-mining procedure wherein we explore the underlying network structure of 2,002 experiments representing over 53,000 subjects through independent components analysis (ICA). To reduce data-redundancy effects inherent to any database, we demonstrate two data-filtering approaches that proved helpful to ICA. Finally, we apply hierarchical clustering analysis (HCA) to measure network- and disease-specificity. This procedure distinguished psychiatric from neurological diseases. We invite the neuroscientific community to further exploit BrainMap VBM with other modeling approaches. © 2018 Wiley Periodicals, Inc.
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The ESID Online Database network.
Guzman, D; Veit, D; Knerr, V; Kindle, G; Gathmann, B; Eades-Perner, A M; Grimbacher, B
2007-03-01
Primary immunodeficiencies (PIDs) belong to the group of rare diseases. The European Society for Immunodeficiencies (ESID), is establishing an innovative European patient and research database network for continuous long-term documentation of patients, in order to improve the diagnosis, classification, prognosis and therapy of PIDs. The ESID Online Database is a web-based system aimed at data storage, data entry, reporting and the import of pre-existing data sources in an enterprise business-to-business integration (B2B). The online database is based on Java 2 Enterprise System (J2EE) with high-standard security features, which comply with data protection laws and the demands of a modern research platform. The ESID Online Database is accessible via the official website (http://www.esid.org/). Supplementary data are available at Bioinformatics online.
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Li, Wan; Chen, Lina; Li, Xia; Jia, Xu; Feng, Chenchen; Zhang, Liangcai; He, Weiming; Lv, Junjie; He, Yuehan; Li, Weiguo; Qu, Xiaoli; Zhou, Yanyan; Shi, Yuchen
2013-12-01
Network motifs in central positions are considered to not only have more in-coming and out-going connections but are also localized in an area where more paths reach the networks. These central motifs have been extensively investigated to determine their consistent functions or associations with specific function categories. However, their functional potentials in the maintenance of cross-talk between different functional communities are unclear. In this paper, we constructed an integrated human signaling network from the Pathway Interaction Database. We identified 39 essential cancer-related motifs in central roles, which we called cancer-related marketing centrality motifs, using combined centrality indices on the system level. Our results demonstrated that these cancer-related marketing centrality motifs were pivotal units in the signaling network, and could mediate cross-talk between 61 biological pathways (25 could be mediated by one motif on average), most of which were cancer-related pathways. Further analysis showed that molecules of most marketing centrality motifs were in the same or adjacent subcellular localizations, such as the motif containing PI3K, PDK1 and AKT1 in the plasma membrane, to mediate signal transduction between 32 cancer-related pathways. Finally, we analyzed the pivotal roles of cancer genes in these marketing centrality motifs in the pathogenesis of cancers, and found that non-cancer genes were potential cancer-related genes.
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Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.
Tuo, Youlin; An, Ning; Zhang, Ming
2018-03-01
The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of P<0.05. Based on the protein‑protein interactions (PPIs) in the Biological General Repository for Interaction Datasets, Human Protein Reference Database and Biomolecular Interaction Network Database, the PPI network of the feature genes was constructed. The feature genes identified by topological characteristics were then used for support vector machine (SVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an independent dataset (35 metastatic samples and 143 non‑metastatic samples) revealed an accuracy of 94.38% and AUROC of 0.958. Cell cycle associated functions and pathways were the most significant terms of the 30 feature genes. A SVM classifier was constructed to assess the possibility of breast cancer metastasis, which presented high accuracy in several independent datasets. CDK2, CDKN1A, E2F1 and MYC were indicated as the potential feature genes in metastatic breast cancer.
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WLN's Database: New Directions.
ERIC Educational Resources Information Center
Ziegman, Bruce N.
1988-01-01
Describes features of the Western Library Network's database, including the database structure, authority control, contents, quality control, and distribution methods. The discussion covers changes in distribution necessitated by increasing telecommunications costs and the development of optical data disk products. (CLB)
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NASA Technical Reports Server (NTRS)
Baldwin, John; Zendejas, Silvino; Gutheinz, Sandy; Borden, Chester; Wang, Yeou-Fang
2009-01-01
Mission and Assets Database (MADB) Version 1.0 is an SQL database system with a Web user interface to centralize information. The database stores flight project support resource requirements, view periods, antenna information, schedule, and forecast results for use in mid-range and long-term planning of Deep Space Network (DSN) assets.
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Guo, Liyuan; Wang, Jing
2018-01-04
Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
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2018-01-01
Abstract Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element–target gene pairs (E–G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. PMID:29140525
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Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I
2014-01-01
Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.
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NASA Astrophysics Data System (ADS)
Grimes, J.; Mahoney, A. R.; Heinrichs, T. A.; Eicken, H.
2012-12-01
Sensor data can be highly variable in nature and also varied depending on the physical quantity being observed, sensor hardware and sampling parameters. The sea ice mass balance site (MBS) operated in Barrow by the University of Alaska Fairbanks (http://seaice.alaska.edu/gi/observatories/barrow_sealevel) is a multisensor platform consisting of a thermistor string, air and water temperature sensors, acoustic altimeters above and below the ice and a humidity sensor. Each sensor has a unique specification and configuration. The data from multiple sensors are combined to generate sea ice data products. For example, ice thickness is calculated from the positions of the upper and lower ice surfaces, which are determined using data from downward-looking and upward-looking acoustic altimeters above and below the ice, respectively. As a data clearinghouse, the Geographic Information Network of Alaska (GINA) processes real time data from many sources, including the Barrow MBS. Doing so requires a system that is easy to use, yet also offers the flexibility to handle data from multisensor observing platforms. In the case of the Barrow MBS, the metadata system needs to accommodate the addition of new and retirement of old sensors from year to year as well as instrument configuration changes caused by, for example, spring melt or inquisitive polar bears. We also require ease of use for both administrators and end users. Here we present the data and processing steps of using sensor data system powered by the NoSQL storage engine, MongoDB. The system has been developed to ingest, process, disseminate and archive data from the Barrow MBS. Storing sensor data in a generalized format, from many different sources, is a challenging task, especially for traditional SQL databases with a set schema. MongoDB is a NoSQL (not only SQL) database that does not require a fixed schema. There are several advantages using this model over the traditional relational database management system (RDBMS) model databases. The lack of a required schema allows flexibility in how the data can be ingested into the database. For example, MongoDB imposes no restrictions on field names. For researchers using the system, this means that the name they have chosen for the sensor is carried through the database, any processing, and to the final output helping to preserve data integrity. Also, MongoDB allows the data to be pushed to it dynamically meaning that field attributes can be defined at the point of ingestion. This allows any sensor data to be ingested as a document and for this functionality to be transferred to the user interface, allowing greater adaptability to different use-case scenarios. In presenting the MondoDB data system being developed for the Barrow MBS, we demonstrate the versatility of this approach and its suitability as the foundation of a Barrow node of the Arctic Observing Network. Authors Jason Grimes - Geographic Information Network of Alaska - jason@gina.alaska.edu Andy Mahony - Geophysical Institute - mahoney@gi.alaska.edu Hajo Eiken - Geophysical Institute - Hajo.Eicken@gi.alaska.edu Tom Heinrichs - Geographic Information Network of Alaska - Tom.Heinrichs@alaska.edu
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A National Virtual Specimen Database for Early Cancer Detection
NASA Technical Reports Server (NTRS)
Crichton, Daniel; Kincaid, Heather; Kelly, Sean; Thornquist, Mark; Johnsey, Donald; Winget, Marcy
2003-01-01
Access to biospecimens is essential for enabling cancer biomarker discovery. The National Cancer Institute's (NCI) Early Detection Research Network (EDRN) comprises and integrates a large number of laboratories into a network in order to establish a collaborative scientific environment to discover and validate disease markers. The diversity of both the institutions and the collaborative focus has created the need for establishing cross-disciplinary teams focused on integrating expertise in biomedical research, computational and biostatistics, and computer science. Given the collaborative design of the network, the EDRN needed an informatics infrastructure. The Fred Hutchinson Cancer Research Center, the National Cancer Institute,and NASA's Jet Propulsion Laboratory (JPL) teamed up to build an informatics infrastructure creating a collaborative, science-driven research environment despite the geographic and morphology differences of the information systems that existed within the diverse network. EDRN investigators identified the need to share biospecimen data captured across the country managed in disparate databases. As a result, the informatics team initiated an effort to create a virtual tissue database whereby scientists could search and locate details about specimens located at collaborating laboratories. Each database, however, was locally implemented and integrated into collection processes and methods unique to each institution. This meant that efforts to integrate databases needed to be done in a manner that did not require redesign or re-implementation of existing system
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Driver fatigue and road safety on Poland's national roads.
Jamroz, Kazimierz; Smolarek, Leszek
2013-01-01
This paper presents an overview of factors causing driver fatigue as described in the literature. Next, a traffic crash database for 2003-2007 is used to identify the causes, circumstances and consequences of accidents caused by driver fatigue on Poland's national roads. The results of the study were used to build a model showing the relationship between the concentration of road accidents and casualties, and the time of day. Finally, the level of relative accident risk at night-time versus daytime is defined. A map shows the risk of death and severe injury on the network of Poland's national roads. The paper suggests to road authorities steps to reduce fatigue-related road accidents in Poland.
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Development of multi-mission satellite data systems at the German Remote Sensing Data Centre
NASA Astrophysics Data System (ADS)
Lotz-Iwen, H. J.; Markwitz, W.; Schreier, G.
1998-11-01
This paper focuses on conceptual aspects of the access to multi-mission remote sensing data by online catalogue and information systems. The system ISIS of the German Remote Sensing Data Centre is described as an example of a user interface to earth observation data. ISIS has been designed to support international scientific research as well as operational applications by offering online access to the database via public networks. It provides catalogue retrieval, visualisation and transfer of image data, and is integrated in international activities dedicated to catalogue and archive interoperability. Finally, an outlook is given on international projects dealing with access to remote sensing data in distributed archives.
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Massive Scale Cyber Traffic Analysis: A Driver for Graph Database Research
DOE Office of Scientific and Technical Information (OSTI.GOV)
Joslyn, Cliff A.; Choudhury, S.; Haglin, David J.
2013-06-19
We describe the significance and prominence of network traffic analysis (TA) as a graph- and network-theoretical domain for advancing research in graph database systems. TA involves observing and analyzing the connections between clients, servers, hosts, and actors within IP networks, both at particular times and as extended over times. Towards that end, NetFlow (or more generically, IPFLOW) data are available from routers and servers which summarize coherent groups of IP packets flowing through the network. IPFLOW databases are routinely interrogated statistically and visualized for suspicious patterns. But the ability to cast IPFLOW data as a massive graph and query itmore » interactively, in order to e.g.\\ identify connectivity patterns, is less well advanced, due to a number of factors including scaling, and their hybrid nature combining graph connectivity and quantitative attributes. In this paper, we outline requirements and opportunities for graph-structured IPFLOW analytics based on our experience with real IPFLOW databases. Specifically, we describe real use cases from the security domain, cast them as graph patterns, show how to express them in two graph-oriented query languages SPARQL and Datalog, and use these examples to motivate a new class of "hybrid" graph-relational systems.« less
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Moving BASISplus and TECHLIBplus from VAX/VMS to UNIX
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dominiak, R.
1993-12-31
BASISplus is used at the Laboratory by the Technical Information Services (TIS) Department which is part of the Information and Publishing Division at ARGONNE. TIS operates the Argonne Information Management System (AIM). The AIM System consists of the ANL Libraries On-Line Database (a TECHLIBplus database), the Current Journals Database (IDI`s current contents search), the ANL Publications Tracking Database (a TECHLIBplus database), the Powder Diffraction File Database, and several CD-ROM databases available through a Novell network. The AIM System is available from the desktop of ANL staff through modem and network connections, as well as from the 10 science libraries atmore » ARGONNE. TIS has been a BASISplus and TECHLIBplus site from the start, and never migrated from BASIS K. The decision to migrate from the VAX/VMS platform to a UNIX platform. Migrating a product from one platform to another involves many decisions and considerations. These justifications, decisions, and considerations are explored in this report.« less
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Gao, Ji; Li, Hongyan; Liu, Lei; Song, Lide; Lv, Yanting; Han, Yuping
2017-12-01
The aim of the present study was to investigate risk-related microRNAs (miRs) for bladder urothelial carcinoma (BUC) prognosis. Clinical and microRNA expression data downloaded from the Cancer Genome Atlas were utilized for survival analysis. Risk factor estimation was performed using Cox's proportional regression analysis. A microRNA-regulated target gene network was constructed and presented using Cytoscape. In addition, the Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment, followed by protein-protein interaction (PPI) network analysis. Finally, the K-clique method was applied to analyze sub-pathways. A total of 16 significant microRNAs, including hsa-miR-3622a and hsa-miR-29a, were identified (P<0.05). Following Cox's proportional regression analysis, hsa-miR-29a was screened as a prognostic marker of BUC risk (P=0.0449). A regulation network of hsa-miR-29a comprising 417 target genes was constructed. These target genes were primarily enriched in GO terms, including collagen fibril organization, extracellular matrix (ECM) organization and pathways, such as focal adhesion (P<0.05). A PPI network including 197 genes and 510 interactions, was constructed. The top 21 genes in the network module were enriched in GO terms, including collagen fibril organization and pathways, such as ECM receptor interaction (P<0.05). Finally, 4 sub-pathways of cysteine and methionine metabolism, including paths 00270_4, 00270_1, 00270_2 and 00270_5, were obtained (P<0.01) and identified to be enriched through DNA (cytosine-5)-methyltransferase ( DNMT)3A, DNMT3B , methionine adenosyltransferase 2α ( MAT2A ) and spermine synthase ( SMS ). The identified microRNAs, particularly hsa-miR-29a and its 4 associated target genes DNMT3A, DNMT3B, MAT2A and SMS , may participate in the prognostic risk mechanism of BUC.
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Neural networks related to dysfunctional face processing in autism spectrum disorder
Nickl-Jockschat, Thomas; Rottschy, Claudia; Thommes, Johanna; Schneider, Frank; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.
2016-01-01
One of the most consistent neuropsychological findings in autism spectrum disorders (ASD) is a reduced interest in and impaired processing of human faces. We conducted an activation likelihood estimation meta-analysis on 14 functional imaging studies on neural correlates of face processing enrolling a total of 164 ASD patients. Subsequently, normative whole-brain functional connectivity maps for the identified regions of significant convergence were computed for the task-independent (resting-state) and task-dependent (co-activations) state in healthy subjects. Quantitative functional decoding was performed by reference to the BrainMap database. Finally, we examined the overlap of the delineated network with the results of a previous meta-analysis on structural abnormalities in ASD as well as with brain regions involved in human action observation/imitation. We found a single cluster in the left fusiform gyrus showing significantly reduced activation during face processing in ASD across all studies. Both task-dependent and task-independent analyses indicated significant functional connectivity of this region with the temporo-occipital and lateral occipital cortex, the inferior frontal and parietal cortices, the thalamus and the amygdala. Quantitative reverse inference then indicated an association of these regions mainly with face processing, affective processing, and language-related tasks. Moreover, we found that the cortex in the region of right area V5 displaying structural changes in ASD patients showed consistent connectivity with the region showing aberrant responses in the context of face processing. Finally, this network was also implicated in the human action observation/imitation network. In summary, our findings thus suggest a functionally and structurally disturbed network of occipital regions related primarily to face (but potentially also language) processing, which interact with inferior frontal as well as limbic regions and may be the core of aberrant face processing and reduced interest in faces in ASD. PMID:24869925
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Implementation of medical monitor system based on networks
NASA Astrophysics Data System (ADS)
Yu, Hui; Cao, Yuzhen; Zhang, Lixin; Ding, Mingshi
2006-11-01
In this paper, the development trend of medical monitor system is analyzed and portable trend and network function become more and more popular among all kinds of medical monitor devices. The architecture of medical network monitor system solution is provided and design and implementation details of medical monitor terminal, monitor center software, distributed medical database and two kind of medical information terminal are especially discussed. Rabbit3000 system is used in medical monitor terminal to implement security administration of data transfer on network, human-machine interface, power management and DSP interface while DSP chip TMS5402 is used in signal analysis and data compression. Distributed medical database is designed for hospital center according to DICOM information model and HL7 standard. Pocket medical information terminal based on ARM9 embedded platform is also developed to interactive with center database on networks. Two kernels based on WINCE are customized and corresponding terminal software are developed for nurse's routine care and doctor's auxiliary diagnosis. Now invention patent of the monitor terminal is approved and manufacture and clinic test plans are scheduled. Applications for invention patent are also arranged for two medical information terminals.
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Challenges of the information age: the impact of false discovery on pathway identification.
Rog, Colin J; Chekuri, Srinivasa C; Edgerton, Mary E
2012-11-21
Pathways with members that have known relevance to a disease are used to support hypotheses generated from analyses of gene expression and proteomic studies. Using cancer as an example, the pitfalls of searching pathways databases as support for genes and proteins that could represent false discoveries are explored. The frequency with which networks could be generated from 100 instances each of randomly selected five and ten genes sets as input to MetaCore, a commercial pathways database, was measured. A PubMed search enumerated cancer-related literature published for any gene in the networks. Using three, two, and one maximum intervening step between input genes to populate the network, networks were generated with frequencies of 97%, 77%, and 7% using ten gene sets and 73%, 27%, and 1% using five gene sets. PubMed reported an average of 4225 cancer-related articles per network gene. This can be attributed to the richly populated pathways databases and the interest in the molecular basis of cancer. As information sources become enriched, they are more likely to generate plausible mechanisms for false discoveries.
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NASA Astrophysics Data System (ADS)
Brazil, L.
2017-12-01
The Shale Network's extensive database of water quality observations enables educational experiences about the potential impacts of resource extraction with real data. Through open source tools that are developed and maintained by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), researchers, educators, and citizens can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through collection efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. Thus far, CUAHSI-supported data tools have been used to engage high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in developing educational material, and the resources available to learn more.
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Towards a Global Operational Altimeter Service: RADS
NASA Astrophysics Data System (ADS)
Naeije, M.; Schrama, E.; Mathers, L.; Scharroo, R.
2001-12-01
DEOS' anticipation of the need for global altimeter services started the Radar Altimeter Database System (RADS) project. Embedded in the Netherlands Earth Observation NETwork (NEONET), this project is supported by the Dutch government. After defining the database content, collecting altimeter and ancillary data from all available altimeter missions and combining them with the latest (correction) models, we have arrived at an (inter)nationally appreciated validated, calibrated and consistent altimeter data set, comprising over 15 years of valuable sea level, wave height and wind data. Whenever new data or knowledge arrives the database is updated. Major assets of RADS are the upgraded ERS orbits and the flexible data organization. This paper presents an overview of the work involved in establishing RADS: the I/O, enhancements, screening, formatting, harmonization, and CAL/VAL. The aim is to improve the algorithms for converting satellite data to the final geophysical products. Global altimeter data from various satellites are inter-compared or compared to external data, like tide gauges, wind speed measurements, etc. This has been used to establish the data's quality and to enhance algorithms for deriving the geophysical parameters. Also: ironing out inconsistencies in significant wave height, sea state, inverse barometer, wet troposphere corrections, orbits, biases, drifts, and time tagging. Access to the database at level~1 level is provided for by a web portal (\\tt http://www.deos.tudelft.nl/altim/rads). Here also status, higher level products, software, and literature can be obtained. Finally, examples are given of putting in RADS in research and education. We fully automated the Gulf Stream and El Niño web pages: Hovmuller diagrams and eddy kinetic energy plots are refreshed regularly. Furthermore, RADS has been successfully used at Delft Hydraulics in a data assimilation scheme for improving tides and storm surge predictions, showing the importance of near real-time observations, and at the Dutch Meteorological Office KNMI for ENSO studies.
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Hermjakob, Henning; Montecchi-Palazzi, Luisa; Bader, Gary; Wojcik, Jérôme; Salwinski, Lukasz; Ceol, Arnaud; Moore, Susan; Orchard, Sandra; Sarkans, Ugis; von Mering, Christian; Roechert, Bernd; Poux, Sylvain; Jung, Eva; Mersch, Henning; Kersey, Paul; Lappe, Michael; Li, Yixue; Zeng, Rong; Rana, Debashis; Nikolski, Macha; Husi, Holger; Brun, Christine; Shanker, K; Grant, Seth G N; Sander, Chris; Bork, Peer; Zhu, Weimin; Pandey, Akhilesh; Brazma, Alvis; Jacq, Bernard; Vidal, Marc; Sherman, David; Legrain, Pierre; Cesareni, Gianni; Xenarios, Ioannis; Eisenberg, David; Steipe, Boris; Hogue, Chris; Apweiler, Rolf
2004-02-01
A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).
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The Biomolecular Interaction Network Database and related tools 2005 update
Alfarano, C.; Andrade, C. E.; Anthony, K.; Bahroos, N.; Bajec, M.; Bantoft, K.; Betel, D.; Bobechko, B.; Boutilier, K.; Burgess, E.; Buzadzija, K.; Cavero, R.; D'Abreo, C.; Donaldson, I.; Dorairajoo, D.; Dumontier, M. J.; Dumontier, M. R.; Earles, V.; Farrall, R.; Feldman, H.; Garderman, E.; Gong, Y.; Gonzaga, R.; Grytsan, V.; Gryz, E.; Gu, V.; Haldorsen, E.; Halupa, A.; Haw, R.; Hrvojic, A.; Hurrell, L.; Isserlin, R.; Jack, F.; Juma, F.; Khan, A.; Kon, T.; Konopinsky, S.; Le, V.; Lee, E.; Ling, S.; Magidin, M.; Moniakis, J.; Montojo, J.; Moore, S.; Muskat, B.; Ng, I.; Paraiso, J. P.; Parker, B.; Pintilie, G.; Pirone, R.; Salama, J. J.; Sgro, S.; Shan, T.; Shu, Y.; Siew, J.; Skinner, D.; Snyder, K.; Stasiuk, R.; Strumpf, D.; Tuekam, B.; Tao, S.; Wang, Z.; White, M.; Willis, R.; Wolting, C.; Wong, S.; Wrong, A.; Xin, C.; Yao, R.; Yates, B.; Zhang, S.; Zheng, K.; Pawson, T.; Ouellette, B. F. F.; Hogue, C. W. V.
2005-01-01
The Biomolecular Interaction Network Database (BIND) (http://bind.ca) archives biomolecular interaction, reaction, complex and pathway information. Our aim is to curate the details about molecular interactions that arise from published experimental research and to provide this information, as well as tools to enable data analysis, freely to researchers worldwide. BIND data are curated into a comprehensive machine-readable archive of computable information and provides users with methods to discover interactions and molecular mechanisms. BIND has worked to develop new methods for visualization that amplify the underlying annotation of genes and proteins to facilitate the study of molecular interaction networks. BIND has maintained an open database policy since its inception in 1999. Data growth has proceeded at a tremendous rate, approaching over 100 000 records. New services provided include a new BIND Query and Submission interface, a Standard Object Access Protocol service and the Small Molecule Interaction Database (http://smid.blueprint.org) that allows users to determine probable small molecule binding sites of new sequences and examine conserved binding residues. PMID:15608229
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Teaching Structured Design of Network Algorithms in Enhanced Versions of SQL
ERIC Educational Resources Information Center
de Brock, Bert
2004-01-01
From time to time developers of (database) applications will encounter, explicitly or implicitly, structures such as trees, graphs, and networks. Such applications can, for instance, relate to bills of material, organization charts, networks of (rail)roads, networks of conduit pipes (e.g., plumbing, electricity), telecom networks, and data…
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Wang, Yumei; Yin, Xiaoling; Yang, Fang
2018-02-01
Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.
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NASA Astrophysics Data System (ADS)
McGuire, M. P.; Welty, C.; Gangopadhyay, A.; Karabatis, G.; Chen, Z.
2006-05-01
The urban environment is formed by complex interactions between natural and human dominated systems, the study of which requires the collection and analysis of very large datasets that span many disciplines. Recent advances in sensor technology and automated data collection have improved the ability to monitor urban environmental systems and are making the idea of an urban environmental observatory a reality. This in turn has created a number of potential challenges in data management and analysis. We present the design of an end-to-end system to store, analyze, and visualize data from a prototype urban environmental observatory based at the Baltimore Ecosystem Study, a National Science Foundation Long Term Ecological Research site (BES LTER). We first present an object-relational design of an operational database to store high resolution spatial datasets as well as data from sensor networks, archived data from the BES LTER, data from external sources such as USGS NWIS, EPA Storet, and metadata. The second component of the system design includes a spatiotemporal data warehouse consisting of a data staging plan and a multidimensional data model designed for the spatiotemporal analysis of monitoring data. The system design also includes applications for multi-resolution exploratory data analysis, multi-resolution data mining, and spatiotemporal visualization based on the spatiotemporal data warehouse. Also the system design includes interfaces with water quality models such as HSPF, SWMM, and SWAT, and applications for real-time sensor network visualization, data discovery, data download, QA/QC, and backup and recovery, all of which are based on the operational database. The system design includes both internet and workstation-based interfaces. Finally we present the design of a laboratory for spatiotemporal analysis and visualization as well as real-time monitoring of the sensor network.
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Tschmelak, Jens; Proll, Guenther; Riedt, Johannes; Kaiser, Joachim; Kraemmer, Peter; Bárzaga, Luis; Wilkinson, James S; Hua, Ping; Hole, J Patrick; Nudd, Richard; Jackson, Michael; Abuknesha, Ram; Barceló, Damià; Rodriguez-Mozaz, Sara; de Alda, Maria J López; Sacher, Frank; Stien, Jan; Slobodník, Jaroslav; Oswald, Peter; Kozmenko, Helena; Korenková, Eva; Tóthová, Lívia; Krascsenits, Zoltan; Gauglitz, Guenter
2005-02-15
A novel analytical system AWACSS (automated water analyser computer-supported system) based on immunochemical technology has been developed that can measure several organic pollutants at low nanogram per litre level in a single few-minutes analysis without any prior sample pre-concentration nor pre-treatment steps. Having in mind actual needs of water-sector managers related to the implementation of the Drinking Water Directive (DWD) (98/83/EC, 1998) and Water Framework Directive WFD (2000/60/EC, 2000), drinking, ground, surface, and waste waters were major media used for the evaluation of the system performance. The instrument was equipped with remote control and surveillance facilities. The system's software allows for the internet-based networking between the measurement and control stations, global management, trend analysis, and early-warning applications. The experience of water laboratories has been utilised at the design of the instrument's hardware and software in order to make the system rugged and user-friendly. Several market surveys were conducted during the project to assess the applicability of the final system. A web-based AWACSS database was created for automated evaluation and storage of the obtained data in a format compatible with major databases of environmental organic pollutants in Europe. This first part article gives the reader an overview of the aims and scope of the AWACSS project as well as details about basic technology, immunoassays, software, and networking developed and utilised within the research project. The second part article reports on the system performance, first real sample measurements, and an international collaborative trial (inter-laboratory tests) to compare the biosensor with conventional anayltical methods.
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Microsensors for border patrol applications
NASA Astrophysics Data System (ADS)
Falkofske, Dwight; Krantz, Brian; Shimazu, Ron; Berglund, Victor
2005-05-01
A top concern in homeland security efforts is the lack of ability to monitor the thousands of miles of open border with our neighbors. It is not currently feasible to continually monitor the borders for illegal intrusions. The MicroSensor System (MSS) seeks to achieve a low-cost monitoring solution that can be efficiently deployed for border patrol applications. The modifications and issues regarding the unique requirements of this application will be discussed and presented. The MicroSensor System was developed by the Defense Microelectronics Activity (DMEA) for military applications, but border patrol applications, with their unique sensor requirements, demand careful adaptation and modification from the military application. Adaptation of the existing sensor design for border applications has been initiated. Coverage issues, communications needs, and other requirements need to be explored for the border patrol application. Currently, border patrol has a number of deficiencies that can be addressed with a microsensor network. First, a distributed networked sensor field could mitigate the porous border intruder detection problem. Second, a unified database needs to be available to identify aliens attempting to cross into the United States. This database needs to take unique characteristics (e.g. biometrics, fingerprints) recovered from a specialized field unit to reliably identify intruders. Finally, this sensor network needs to provide a communication ability to allow border patrol officers to have quick access to intrusion information as well as equipment tracking and voice communication. MSS already addresses the sensing portion of the solution, including detection of acoustic, infrared, magnetic, and seismic events. MSS also includes a low-power networking protocol to lengthen the battery life. In addition to current military requirements, MSS needs a solar panel solution to extend its battery life to 5 years, and an additional backbone communication link. Expanding the capabilities of MSS will go a long way to improving the security of the nation's porous borders.
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Therapist effects on dropout from a college counseling center practice research network.
Xiao, Henry; Castonguay, Louis G; Janis, Rebecca A; Youn, Soo Jeong; Hayes, Jeffrey A; Locke, Benjamin D
2017-07-01
Dropout has been a pervasive and costly problem in psychotherapy, particularly for college counseling centers. The present study examined potential predictors of dropout using a large data set (N = 10,147 clients, 481 therapists) that was gathered through a college counseling center practice research network as a replication and extension of recent findings regarding therapist effects on dropout. The final model resulted in a dropout rate of 15.9% and a therapist effect of 9.51% on dropout variance. Therapist demographic variables were investigated, though none were found to be significant. Variables found to be predictive of increased likelihood of dropping out included higher levels of general presenting concerns, alcohol-related distress, and current financial stress. Ultimately, this study showed that therapists may play an important role in the likelihood of client dropout, and that additional research should be conducted to identify additional predictors, particularly at the therapist and center level. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Gutiérrez, Miguel F; Cajiao, Alejandro; Hidalgo, José A; Cerón, Jesús D; López, Diego M; Quintero, Víctor M; Rendón, Alvaro
2014-01-01
This article presents the development process of an acquisition and data storage system managing clinical variables through a cloud storage service and a Personal Health Record (PHR) System. First, the paper explains how a Wireless Body Area Network (WBAN) that captures data from two sensors corresponding to arterial pressure and heart rate is designed. Second, this paper illustrates how data collected by the WBAN are transmitted to a cloud storage service. It is worth mentioning that this cloud service allows the data to be stored in a persistent way on an online database system. Finally, the paper describes, how the data stored in the cloud service are sent to the Indivo PHR System, where they are registered and charted for future revision by health professionals. The research demonstrated the feasibility of implementing WBAN networks for the acquisition of clinical data, and particularly for the use of Web technologies and standards to provide interoperability with PHR Systems at technical and syntactic levels.
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The EMBL nucleotide sequence database
Stoesser, Guenter; Baker, Wendy; van den Broek, Alexandra; Camon, Evelyn; Garcia-Pastor, Maria; Kanz, Carola; Kulikova, Tamara; Lombard, Vincent; Lopez, Rodrigo; Parkinson, Helen; Redaschi, Nicole; Sterk, Peter; Stoehr, Peter; Tuli, Mary Ann
2001-01-01
The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/) is maintained at the European Bioinformatics Institute (EBI) in an international collaboration with the DNA Data Bank of Japan (DDBJ) and GenBank at the NCBI (USA). Data is exchanged amongst the collaborating databases on a daily basis. The major contributors to the EMBL database are individual authors and genome project groups. Webin is the preferred web-based submission system for individual submitters, whilst automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via ftp, email and World Wide Web interfaces. EBI’s Sequence Retrieval System (SRS), a network browser for databanks in molecular biology, integrates and links the main nucleotide and protein databases plus many specialized databases. For sequence similarity searching a variety of tools (e.g. Blitz, Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT. PMID:11125039
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Arruda, A G; Friendship, R; Carpenter, J; Hand, K; Ojkic, D; Poljak, Z
2017-02-01
The main goal of this study was to investigate the occurrence of porcine reproductive and respiratory syndrome virus (PRRSV)-specific genotypes in swine sites in Ontario (Canada) using molecular, spatial and network data from a porcine reproductive and respiratory syndrome (PRRS) regional control project. For each site, location, animal movement service provider (truck companies), PRRSV status and sequencing data of the open reading frame 5 (ORF5) were obtained. Three-kilometre buffers were created to evaluate neighbourhood characteristics for each site. Social network analysis was conducted on swine sites and trucking companies to assemble the network and define network components. Three different PRRSV genotypes were used as outcomes for statistical analysis based on the region's phylogenetic tree of the ORF5. Multivariable exact logistic regression was conducted to investigate the association between being positive for a specific genotype and two main exposures of interest: (i) having at least one neighbour within three km also positive for the same genotype outside the production system and (ii) having at least one positive site for the same genotype in the same truck network component outside the production system. Results showed that the importance of area spread and truck network on PRRSV occurrence differed according to genotype. Additionally, the Ontario PRRS database appears suitable for conducting regional disease investigations. Finally, the use of relatively new tools available for network, spatial and molecular analysis could be useful in investigation, control and prevention of endemic infectious diseases in animal populations. © 2015 Blackwell Verlag GmbH.
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The EXOSAT database and archive
NASA Technical Reports Server (NTRS)
Reynolds, A. P.; Parmar, A. N.
1992-01-01
The EXOSAT database provides on-line access to the results and data products (spectra, images, and lightcurves) from the EXOSAT mission as well as access to data and logs from a number of other missions (such as EINSTEIN, COS-B, ROSAT, and IRAS). In addition, a number of familiar optical, infrared, and x ray catalogs, including the Hubble Space Telescope (HST) guide star catalog are available. The complete database is located at the EXOSAT observatory at ESTEC in the Netherlands and is accessible remotely via a captive account. The database management system was specifically developed to efficiently access the database and to allow the user to perform statistical studies on large samples of astronomical objects as well as to retrieve scientific and bibliographic information on single sources. The system was designed to be mission independent and includes timing, image processing, and spectral analysis packages as well as software to allow the easy transfer of analysis results and products to the user's own institute. The archive at ESTEC comprises a subset of the EXOSAT observations, stored on magnetic tape. Observations of particular interest were copied in compressed format to an optical jukebox, allowing users to retrieve and analyze selected raw data entirely from their terminals. Such analysis may be necessary if the user's needs are not accommodated by the products contained in the database (in terms of time resolution, spectral range, and the finesse of the background subtraction, for instance). Long-term archiving of the full final observation data is taking place at ESRIN in Italy as part of the ESIS program, again using optical media, and ESRIN have now assumed responsibility for distributing the data to the community. Tests showed that raw observational data (typically several tens of megabytes for a single target) can be transferred via the existing networks in reasonable time.
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Database integration in a multimedia-modeling environment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dorow, Kevin E.
2002-09-02
Integration of data from disparate remote sources has direct applicability to modeling, which can support Brownfield assessments. To accomplish this task, a data integration framework needs to be established. A key element in this framework is the metadata that creates the relationship between the pieces of information that are important in the multimedia modeling environment and the information that is stored in the remote data source. The design philosophy is to allow modelers and database owners to collaborate by defining this metadata in such a way that allows interaction between their components. The main parts of this framework include toolsmore » to facilitate metadata definition, database extraction plan creation, automated extraction plan execution / data retrieval, and a central clearing house for metadata and modeling / database resources. Cross-platform compatibility (using Java) and standard communications protocols (http / https) allow these parts to run in a wide variety of computing environments (Local Area Networks, Internet, etc.), and, therefore, this framework provides many benefits. Because of the specific data relationships described in the metadata, the amount of data that have to be transferred is kept to a minimum (only the data that fulfill a specific request are provided as opposed to transferring the complete contents of a data source). This allows for real-time data extraction from the actual source. Also, the framework sets up collaborative responsibilities such that the different types of participants have control over the areas in which they have domain knowledge-the modelers are responsible for defining the data relevant to their models, while the database owners are responsible for mapping the contents of the database using the metadata definitions. Finally, the data extraction mechanism allows for the ability to control access to the data and what data are made available.« less
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A strong-motion database from the Central American subduction zone
NASA Astrophysics Data System (ADS)
Arango, Maria Cristina; Strasser, Fleur O.; Bommer, Julian J.; Hernández, Douglas A.; Cepeda, Jose M.
2011-04-01
Subduction earthquakes along the Pacific Coast of Central America generate considerable seismic risk in the region. The quantification of the hazard due to these events requires the development of appropriate ground-motion prediction equations, for which purpose a database of recordings from subduction events in the region is indispensable. This paper describes the compilation of a comprehensive database of strong ground-motion recordings obtained during subduction-zone events in Central America, focusing on the region from 8 to 14° N and 83 to 92° W, including Guatemala, El Salvador, Nicaragua and Costa Rica. More than 400 accelerograms recorded by the networks operating across Central America during the last decades have been added to data collected by NORSAR in two regional projects for the reduction of natural disasters. The final database consists of 554 triaxial ground-motion recordings from events of moment magnitudes between 5.0 and 7.7, including 22 interface and 58 intraslab-type events for the time period 1976-2006. Although the database presented in this study is not sufficiently complete in terms of magnitude-distance distribution to serve as a basis for the derivation of predictive equations for interface and intraslab events in Central America, it considerably expands the Central American subduction data compiled in previous studies and used in early ground-motion modelling studies for subduction events in this region. Additionally, the compiled database will allow the assessment of the existing predictive models for subduction-type events in terms of their applicability for the Central American region, which is essential for an adequate estimation of the hazard due to subduction earthquakes in this region.
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Migration of legacy mumps applications to relational database servers.
O'Kane, K C
2001-07-01
An extended implementation of the Mumps language is described that facilitates vendor neutral migration of legacy Mumps applications to SQL-based relational database servers. Implemented as a compiler, this system translates Mumps programs to operating system independent, standard C code for subsequent compilation to fully stand-alone, binary executables. Added built-in functions and support modules extend the native hierarchical Mumps database with access to industry standard, networked, relational database management servers (RDBMS) thus freeing Mumps applications from dependence upon vendor specific, proprietary, unstandardized database models. Unlike Mumps systems that have added captive, proprietary RDMBS access, the programs generated by this development environment can be used with any RDBMS system that supports common network access protocols. Additional features include a built-in web server interface and the ability to interoperate directly with programs and functions written in other languages.
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Dietzel, Matthias; Baltzer, Pascal A T; Dietzel, Andreas; Zoubi, Ramy; Gröschel, Tobias; Burmeister, Hartmut P; Bogdan, Martin; Kaiser, Werner A
2012-07-01
Differential diagnosis of lesions in MR-Mammography (MRM) remains a complex task. The aim of this MRM study was to design and to test robustness of Artificial Neural Network architectures to predict malignancy using a large clinical database. For this IRB-approved investigation standardized protocols and study design were applied (T1w-FLASH; 0.1 mmol/kgBW Gd-DTPA; T2w-TSE; histological verification after MRM). All lesions were evaluated by two experienced (>500 MRM) radiologists in consensus. In every lesion, 18 previously published descriptors were assessed and documented in the database. An Artificial Neural Network (ANN) was developed to process this database (The-MathWorks/Inc., feed-forward-architecture/resilient back-propagation-algorithm). All 18 descriptors were set as input variables, whereas histological results (malignant vs. benign) was defined as classification variable. Initially, the ANN was optimized in terms of "Training Epochs" (TE), "Hidden Layers" (HL), "Learning Rate" (LR) and "Neurons" (N). Robustness of the ANN was addressed by repeated evaluation cycles (n: 9) with receiver operating characteristics (ROC) analysis of the results applying 4-fold Cross Validation. The best network architecture was identified comparing the corresponding Area under the ROC curve (AUC). Histopathology revealed 436 benign and 648 malignant lesions. Enhancing the level of complexity could not increase diagnostic accuracy of the network (P: n.s.). The optimized ANN architecture (TE: 20, HL: 1, N: 5, LR: 1.2) was accurate (mean-AUC 0.888; P: <0.001) and robust (CI: 0.885-0.892; range: 0.880-0.898). The optimized neural network showed robust performance and high diagnostic accuracy for prediction of malignancy on unknown data. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
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RECENT DEVELOPMENTS IN HYDROWEB DATABASE Water level time series on lakes and reservoirs (Invited)
NASA Astrophysics Data System (ADS)
Cretaux, J.; Arsen, A.; Calmant, S.
2013-12-01
We present the current state of the Hydroweb database as well as developments in progress. It provides offline water level time series on rivers, reservoirs and lakes based on altimetry data from several satellites (Topex/Poseidon, ERS, Jason-1&2, GFO and ENVISAT). The major developments in Hydroweb concerns the development of an operational data centre with automatic acquisition and processing of IGDR data for updating time series in near real time (both for lakes & rivers) and also use of additional remote sensing data, like satellite imagery allowing the calculation of lake's surfaces. A lake data centre is under development at the Legos in coordination with Hydrolare Project leaded by SHI (State Hydrological Institute of the Russian Academy of Science). It will provide the level-surface-volume variations of about 230 lakes and reservoirs, calculated through combination of various satellite images (Modis, Asar, Landsat, Cbers) and radar altimetry (Topex / Poseidon, Jason-1 & 2, GFO, Envisat, ERS2, AltiKa). The final objective is to propose a data centre fully based on remote sensing technique and controlled by in situ infrastructure for the Global Terrestrial Network for Lakes (GTN-L) under the supervision of WMO and GCOS. In a longer perspective, the Hydroweb database will integrate data from future missions (Jason-3, Jason-CS, Sentinel-3A/B) and finally will serve for the design of the SWOT mission. The products of hydroweb will be used as input data for simulation of the SWOT products (water height and surface variations of lakes and rivers). In the future, the SWOT mission will allow to monitor on a sub-monthly basis the worldwide lakes and reservoirs bigger than 250 * 250 m and Hydroweb will host water level and extent products from this
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Gramatzki, Dorothee; Herrmann, Caroline; Happold, Caroline; Becker, Katrin Anne; Gulbins, Erich; Weller, Michael; Tabatabai, Ghazaleh
2013-01-01
Background/Aims Resistance to genotoxic therapy is a characteristic feature of glioma cells. Acid sphingomyelinase (ASM) hydrolyzes sphingomyelin to ceramide and glucosylceramide synthase (GCS) catalyzes ceramide metabolism. Increased ceramide levels have been suggested to enhance chemotherapy-induced death of cancer cells. Methods Microarray and clinical data for ASM and GCS in astrocytomas WHO grade II–IV were acquired from the Rembrandt database. Moreover, the glioblastoma database of the Cancer Genome Atlas network (TCGA) was used for survival data of glioblastoma patients. For in vitro studies, increases in ceramide levels were achieved either by ASM overexpression or by the GCS inhibitor DL-threo-1-phenyl-2-palmitoylamino-3-morpholino-1-propanol (PPMP) in human glioma cell lines. Combinations of alkylating chemotherapy or irradiation and ASM overexpression, PPMP or exogenous ceramide were applied in parental cells. The anti-glioma effects were investigated by assessing proliferation, metabolic activity, viability and clonogenicity. Finally, viability and clonogenicity were assessed in temozolomide (TMZ)-resistant cells upon treatment with PPMP, exogenous ceramide, alkylating chemotherapy, irradiation or their combinations. Results Interrogations from the Rembrandt and TCGA database showed a better survival of glioblastoma patients with low expression of ASM or GCS. ASM overexpression or PPMP treatment alone led to ceramide accumulation but did not enhance the anti-glioma activity of alkylating chemotherapy or irradiation. PPMP or exogenous ceramide induced acute cytotoxicity in glioblastoma cells. Combined treatments with chemotherapy or irradiation led to additive, but not synergistic effects. Finally, no synergy was found when TMZ-resistant cells were treated with exogenous ceramide or PPMP alone or in combination with TMZ or irradiation. Conclusion Modulation of intrinsic glioma cell ceramide levels by ASM overexpression or GCS inhibition does not enhance the anti-glioma activity of alkylating chemotherapy or irradiation. PMID:23667632
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Maritime Operations in Disconnected, Intermittent, and Low-Bandwidth Environments
2013-06-01
of a Dynamic Distributed Database ( DDD ) is a core element enabling the distributed operation of networks and applications, as described in this...document. The DDD is a database containing all the relevant information required to reconfigure the applications, routing, and other network services...optimize application configuration. Figure 5 gives a snapshot of entries in the DDD . In current testing, the DDD is replicated using Domino
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Providing Access to CD-ROM Databases in a Campus Setting. Part II: Networking CD-ROMs via a LAN.
ERIC Educational Resources Information Center
Koren, Judy
1992-01-01
The second part of a report on CD-ROM networking in libraries describes LAN (local area network) technology; networking software and towers; gateway software for connecting to campuswide networks; Macintosh LANs; and network licenses. Several product and software reviews are included, and a sidebar lists vendor addresses. (NRP)
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Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information.
Jang, Haeran; An, Ji-Young
2014-07-01
Utilizing social network analysis, this study aimed to analyze the main keywords in the literature regarding the health literacy of and the use of online health information by aged persons over 65. Medical Subject Heading keywords were extracted from articles on the PubMed database of the National Library of Medicine. For health literacy, 110 articles out of 361 were initially extracted. Seventy-one keywords out of 1,021 were finally selected after removing repeated keywords and applying pruning. Regarding the use of online health information, 19 articles out of 26 were selected. One hundred forty-four keywords were initially extracted. After removing the repeated keywords, 74 keywords were finally selected. Health literacy was found to be strongly connected with 'Health knowledge, attitudes, practices' and 'Patient education as topic.' 'Computer literacy' had strong connections with 'Internet' and 'Attitude towards computers.' 'Computer literacy' was connected to 'Health literacy,' and was studied according to the parameters 'Attitude towards health' and 'Patient education as topic.' The use of online health information was strongly connected with 'Health knowledge, attitudes, practices,' 'Consumer health information,' 'Patient education as topic,' etc. In the network, 'Computer literacy' was connected with 'Health education,' 'Patient satisfaction,' 'Self-efficacy,' 'Attitude to computer,' etc. Research on older citizens' health literacy and their use of online health information was conducted together with study of computer literacy, patient education, attitude towards health, health education, patient satisfaction, etc. In particular, self-efficacy was noted as an important keyword. Further research should be conducted to identify the effective outcomes of self-efficacy in the area of interest.
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Statistically validated network of portfolio overlaps and systemic risk.
Gualdi, Stanislao; Cimini, Giulio; Primicerio, Kevin; Di Clemente, Riccardo; Challet, Damien
2016-12-21
Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007-2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains).
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Statistically validated network of portfolio overlaps and systemic risk
Gualdi, Stanislao; Cimini, Giulio; Primicerio, Kevin; Di Clemente, Riccardo; Challet, Damien
2016-01-01
Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007–2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains). PMID:28000764
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An Update of the Bodeker Scientific Vertically Resolved, Global, Gap-Free Ozone Database
NASA Astrophysics Data System (ADS)
Kremser, S.; Bodeker, G. E.; Lewis, J.; Hassler, B.
2016-12-01
High vertical resolution ozone measurements from multiple satellite-based instruments have been merged with measurements from the global ozonesonde network to calculate monthly mean ozone values in 5º latitude zones. Ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km) and on 70 pressure levels spaced approximately 1 km apart (878.4 hPa to 0.046 hPa). These data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to these data and then evaluated globally. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. This presentation reports on updates to an earlier version of the vertically resolved ozone database, including the incorporation of new ozone measurements and new techniques for combining the data. Compared to previous versions of the database, particular attention is paid to avoiding spatial and temporal sampling biases and tracing uncertainties through to the final product. This updated database, developed within the New Zealand Deep South National Science Challenge, is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not treat stratospheric chemistry interactively.
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Utilizing semantic networks to database and retrieve generalized stochastic colored Petri nets
NASA Technical Reports Server (NTRS)
Farah, Jeffrey J.; Kelley, Robert B.
1992-01-01
Previous work has introduced the Planning Coordinator (PCOORD), a coordinator functioning within the hierarchy of the Intelligent Machine Mode. Within the structure of the Planning Coordinator resides the Primitive Structure Database (PSDB) functioning to provide the primitive structures utilized by the Planning Coordinator in the establishing of error recovery or on-line path plans. This report further explores the Primitive Structure Database and establishes the potential of utilizing semantic networks as a means of efficiently storing and retrieving the Generalized Stochastic Colored Petri Nets from which the error recovery plans are derived.
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Prakash, Peralam Yegneswaran; Irinyi, Laszlo; Halliday, Catriona; Chen, Sharon; Robert, Vincent
2017-01-01
ABSTRACT The increase in public online databases dedicated to fungal identification is noteworthy. This can be attributed to improved access to molecular approaches to characterize fungi, as well as to delineate species within specific fungal groups in the last 2 decades, leading to an ever-increasing complexity of taxonomic assortments and nomenclatural reassignments. Thus, well-curated fungal databases with substantial accurate sequence data play a pivotal role for further research and diagnostics in the field of mycology. This minireview aims to provide an overview of currently available online databases for the taxonomy and identification of human and animal-pathogenic fungi and calls for the establishment of a cloud-based dynamic data network platform. PMID:28179406
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MetNetAPI: A flexible method to access and manipulate biological network data from MetNet
2010-01-01
Background Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at http://www.metnetonline.org/api. PMID:21083943
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Ke, Tao; Yu, Jingyin; Dong, Caihua; Mao, Han; Hua, Wei; Liu, Shengyi
2015-01-21
Oil crop seeds are important sources of fatty acids (FAs) for human and animal nutrition. Despite their importance, there is a lack of an essential bioinformatics resource on gene transcription of oil crops from a comparative perspective. In this study, we developed ocsESTdb, the first database of expressed sequence tag (EST) information on seeds of four large-scale oil crops with an emphasis on global metabolic networks and oil accumulation metabolism that target the involved unigenes. A total of 248,522 ESTs and 106,835 unigenes were collected from the cDNA libraries of rapeseed (Brassica napus), soybean (Glycine max), sesame (Sesamum indicum) and peanut (Arachis hypogaea). These unigenes were annotated by a sequence similarity search against databases including TAIR, NR protein database, Gene Ontology, COG, Swiss-Prot, TrEMBL and Kyoto Encyclopedia of Genes and Genomes (KEGG). Five genome-scale metabolic networks that contain different numbers of metabolites and gene-enzyme reaction-association entries were analysed and constructed using Cytoscape and yEd programs. Details of unigene entries, deduced amino acid sequences and putative annotation are available from our database to browse, search and download. Intuitive and graphical representations of EST/unigene sequences, functional annotations, metabolic pathways and metabolic networks are also available. ocsESTdb will be updated regularly and can be freely accessed at http://ocri-genomics.org/ocsESTdb/ . ocsESTdb may serve as a valuable and unique resource for comparative analysis of acyl lipid synthesis and metabolism in oilseed plants. It also may provide vital insights into improving oil content in seeds of oil crop species by transcriptional reconstruction of the metabolic network.
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Scott, J; Botsis, T; Ball, R
2014-01-01
Spontaneous Reporting Systems [SRS] are critical tools in the post-licensure evaluation of medical product safety. Regulatory authorities use a variety of data mining techniques to detect potential safety signals in SRS databases. Assessing the performance of such signal detection procedures requires simulated SRS databases, but simulation strategies proposed to date each have limitations. We sought to develop a novel SRS simulation strategy based on plausible mechanisms for the growth of databases over time. We developed a simulation strategy based on the network principle of preferential attachment. We demonstrated how this strategy can be used to create simulations based on specific databases of interest, and provided an example of using such simulations to compare signal detection thresholds for a popular data mining algorithm. The preferential attachment simulations were generally structurally similar to our targeted SRS database, although they had fewer nodes of very high degree. The approach was able to generate signal-free SRS simulations, as well as mimicking specific known true signals. Explorations of different reporting thresholds for the FDA Vaccine Adverse Event Reporting System suggested that using proportional reporting ratio [PRR] > 3.0 may yield better signal detection operating characteristics than the more commonly used PRR > 2.0 threshold. The network analytic approach to SRS simulation based on the principle of preferential attachment provides an attractive framework for exploring the performance of safety signal detection algorithms. This approach is potentially more principled and versatile than existing simulation approaches. The utility of network-based SRS simulations needs to be further explored by evaluating other types of simulated signals with a broader range of data mining approaches, and comparing network-based simulations with other simulation strategies where applicable.
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BNDB - the Biochemical Network Database.
Küntzer, Jan; Backes, Christina; Blum, Torsten; Gerasch, Andreas; Kaufmann, Michael; Kohlbacher, Oliver; Lenhof, Hans-Peter
2007-10-02
Technological advances in high-throughput techniques and efficient data acquisition methods have resulted in a massive amount of life science data. The data is stored in numerous databases that have been established over the last decades and are essential resources for scientists nowadays. However, the diversity of the databases and the underlying data models make it difficult to combine this information for solving complex problems in systems biology. Currently, researchers typically have to browse several, often highly focused, databases to obtain the required information. Hence, there is a pressing need for more efficient systems for integrating, analyzing, and interpreting these data. The standardization and virtual consolidation of the databases is a major challenge resulting in a unified access to a variety of data sources. We present the Biochemical Network Database (BNDB), a powerful relational database platform, allowing a complete semantic integration of an extensive collection of external databases. BNDB is built upon a comprehensive and extensible object model called BioCore, which is powerful enough to model most known biochemical processes and at the same time easily extensible to be adapted to new biological concepts. Besides a web interface for the search and curation of the data, a Java-based viewer (BiNA) provides a powerful platform-independent visualization and navigation of the data. BiNA uses sophisticated graph layout algorithms for an interactive visualization and navigation of BNDB. BNDB allows a simple, unified access to a variety of external data sources. Its tight integration with the biochemical network library BN++ offers the possibility for import, integration, analysis, and visualization of the data. BNDB is freely accessible at http://www.bndb.org.
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ERIC Educational Resources Information Center
Irwin, Gretchen; Wessel, Lark; Blackman, Harvey
2012-01-01
This case describes a database redesign project for the United States Department of Agriculture's National Animal Germplasm Program (NAGP). The case provides a valuable context for teaching and practicing database analysis, design, and implementation skills, and can be used as the basis for a semester-long team project. The case demonstrates the…
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Guo, Nan; Zhang, Nan; Yan, Liqiu; Lian, Zheng; Wang, Jiawang; Lv, Fengfeng; Wang, Yunfei; Cao, Xufen
2018-06-14
Acute myocardial infarction induces ventricular remodeling, which is implicated in dilated heart and heart failure. The pathogenical mechanism of myocardium remodeling remains to be elucidated. The aim of the present study was to identify key genes and networks for myocardium remodeling following ischemia‑reperfusion (IR). First, the mRNA expression data from the National Center for Biotechnology Information database were downloaded to identify differences in mRNA expression of the IR heart at days 2 and 7. Then, weighted gene co‑expression network analysis, hierarchical clustering, protein‑protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to identify key genes and networks for the heart remodeling process following IR. A total of 3,321 differentially expressed genes were identified during the heart remodeling process. A total of 6 modules were identified through gene co‑expression network analysis. GO and KEGG analysis results suggested that each module represented a different biological function and was associated with different pathways. Finally, hub genes of each module were identified by PPI network construction. The present study revealed that heart remodeling following IR is a complicated process, involving extracellular matrix organization, neural development, apoptosis and energy metabolism. The dysregulated genes, including SRC proto‑oncogene, non‑receptor tyrosine kinase, discs large MAGUK scaffold protein 1, ATP citrate lyase, RAN, member RAS oncogene family, tumor protein p53, and polo like kinase 2, may be essential for heart remodeling following IR and may be used as potential targets for the inhibition of heart remodeling following acute myocardial infarction.
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DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions
Arjunan, Selvam; Sastri, Narayan P.; Chandra, Nagasuma
2016-01-01
Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue–human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue–human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/). PMID:27618709
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DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.
Karyala, Prashanthi; Metri, Rahul; Bathula, Christopher; Yelamanchi, Syam K; Sahoo, Lipika; Arjunan, Selvam; Sastri, Narayan P; Chandra, Nagasuma
2016-09-01
Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/).
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IAS telecommunication infrastructure and value added network services provided by IASNET
NASA Astrophysics Data System (ADS)
Smirnov, Oleg L.; Marchenko, Sergei
The topology of a packet switching network for the Soviet National Centre for Automated Data Exchange with Foreign Computer Networks and Databanks (NCADE) based on a design by the Institute for Automated Systems (IAS) is discussed. NCADE has partners all over the world: it is linked to East European countries via telephone lines while satellites are used for communication with remote partners, such as Cuba, Mongolia, and Vietnam. Moreover, there is a connection to the Austrian, British, Canadian, Finnish, French, U.S. and other western networks through which users can have access to databases on each network. At the same time, NCADE provides western customers with access to more than 70 Soviet databases. Software and hardware of IASNET use data exchange recommendations agreed with the International Standard Organization (ISO) and International Telegraph and Telephone Consultative Committee (CCITT). Technical parameters of IASNET are compatible with the majority of foreign networks such as DATAPAK, TRANSPAC, TELENET, and others. By means of IASNET, the NCADE provides connection of Soviet and foreign users to information and computer centers around the world on the basis of the CCITT X.25 and X.75 recommendations. Any information resources of IASNET and value added network services, such as computer teleconferences, E-mail, information retrieval system, intelligent support of access to databanks and databases, and others are discussed. The topology of the ACADEMNET connected to IASNET over an X.25 gateway is also discussed.
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Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi
2016-11-01
Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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DOT National Transportation Integrated Search
2012-03-01
This project initiated the development of a computerized database of ITS facilities, including conduits, junction : boxes, cameras, connections, etc. The current system consists of a database of conduit sections of various lengths. : Over the length ...
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Partial Updating of TSCA Inventory DataBase; Production and Site Reports; Final Rule
A partial updating of the TSCA inventory database. The final rule requires manufacturers and importers of certain chemical substances included on the TSCA Chemical Substances Inventory to report current data on the production volume, plant site, etc.
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Wootton, Richard; Bonnardot, Laurent; Geissbuhler, Antoine; Jethwani, Kamal; Kovarik, Carrie; McGoey, Suzanne; Person, Donald A; Vladzymyrskyy, Anton; Zolfo, Maria
2012-10-09
Telemedicine networks, which deliver humanitarian services, sometimes need to share expertise to find particular experts in other networks. It has been suggested that a mechanism for sharing expertise between networks (a 'clearing house') might be useful. To propose a mechanism for implementing the clearing house concept for sharing expertise, and to confirm its feasibility in terms of acceptability to the relevant networks. We conducted a needs analysis among eight telemedicine networks delivering humanitarian services. A small proportion of consultations (5-10%) suggested that networks may experience difficulties in finding the right specialists from within their own resources. With the assistance of key stakeholders, many of whom were network coordinators, various methods of implementing a clearing house were considered. One simple solution is to establish a central database holding information about consultants who have agreed to provide help to other networks; this database could be made available to network coordinators who need a specialist when none was available in their own network. The proposed solution was examined in a desktop simulation exercise, which confirmed its feasibility and probable value. This analysis informs full-scale implementation of a clearing house, and an associated examination of its costs and benefits.
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Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors
Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung
2017-01-01
Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods. PMID:28587269
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Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors.
Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung
2017-06-06
Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods.
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A new feature constituting approach to detection of vocal fold pathology
NASA Astrophysics Data System (ADS)
Hariharan, M.; Polat, Kemal; Yaacob, Sazali
2014-08-01
In the last two decades, non-invasive methods through acoustic analysis of voice signal have been proved to be excellent and reliable tool to diagnose vocal fold pathologies. This paper proposes a new feature vector based on the wavelet packet transform and singular value decomposition for the detection of vocal fold pathology. k-means clustering based feature weighting is proposed to increase the distinguishing performance of the proposed features. In this work, two databases Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database and MAPACI speech pathology database are used. Four different supervised classifiers such as k-nearest neighbour (k-NN), least-square support vector machine, probabilistic neural network and general regression neural network are employed for testing the proposed features. The experimental results uncover that the proposed features give very promising classification accuracy of 100% for both MEEI database and MAPACI speech pathology database.
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NASA Astrophysics Data System (ADS)
Graham, Jim; Jarnevich, Catherine S.; Simpson, Annie; Newman, Gregory J.; Stohlgren, Thomas J.
2011-06-01
Invasive species are a universal global problem, but the information to identify them, manage them, and prevent invasions is stored around the globe in a variety of formats. The Global Invasive Species Information Network is a consortium of organizations working toward providing seamless access to these disparate databases via the Internet. A distributed network of databases can be created using the Internet and a standard web service protocol. There are two options to provide this integration. First, federated searches are being proposed to allow users to search "deep" web documents such as databases for invasive species. A second method is to create a cache of data from the databases for searching. We compare these two methods, and show that federated searches will not provide the performance and flexibility required from users and a central cache of the datum are required to improve performance.
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Graham, Jim; Jarnevich, Catherine S.; Simpson, Annie; Newman, Gregory J.; Stohlgren, Thomas J.
2011-01-01
Invasive species are a universal global problem, but the information to identify them, manage them, and prevent invasions is stored around the globe in a variety of formats. The Global Invasive Species Information Network is a consortium of organizations working toward providing seamless access to these disparate databases via the Internet. A distributed network of databases can be created using the Internet and a standard web service protocol. There are two options to provide this integration. First, federated searches are being proposed to allow users to search “deep” web documents such as databases for invasive species. A second method is to create a cache of data from the databases for searching. We compare these two methods, and show that federated searches will not provide the performance and flexibility required from users and a central cache of the datum are required to improve performance.
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JNDMS Task Authorization 2 Report
2013-10-01
uses Barnyard to store alarms from all DREnet Snort sensors in a MySQL database. Barnyard is an open source tool designed to work with Snort to take...Technology ITI Information Technology Infrastructure J2EE Java 2 Enterprise Edition JAR Java Archive. This is an archive file format defined by Java ...standards. JDBC Java Database Connectivity JDW JNDMS Data Warehouse JNDMS Joint Network and Defence Management System JNDMS Joint Network Defence and
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Synthesis, Interdiction, and Protection of Layered Networks
2009-09-01
152 4.7 Al Qaeda Network from Sageman Database . . . . . . . . . . 157 4.8 Interdiction Resources versus Closeness Centrality . . . . . . 159...where S may be a polyhedron , a set with discrete variables, a set with nonlin- earities, or so on); and partitions it into two mutually exclusive subsets...p. vii]. However, this database is based on Dr. Sagemans’s 2004 publication and may be dated. Therefore, the analysis in this section is to
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VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).
Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M
2013-12-16
Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.
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NASA Astrophysics Data System (ADS)
Boulanger, Damien; Gautron, Benoit; Schultz, Martin; Brötz, Björn; Rauthe-Schöch, Armin; Thouret, Valérie
2015-04-01
IAGOS (In-service Aircraft for a Global Observing System) aims at the provision of long-term, frequent, regular, accurate, and spatially resolved in situ observations of the atmospheric composition. IAGOS observation systems are deployed on a fleet of commercial aircraft. The IAGOS database is an essential part of the global atmospheric monitoring network. Data access is handled by open access policy based on the submission of research requests which are reviewed by the PIs. The IAGOS database (http://www.iagos.fr, damien.boulanger@obs-mip.fr) is part of the French atmospheric chemistry data centre Ether (CNES and CNRS). In the framework of the IGAS project (IAGOS for Copernicus Atmospheric Service) interoperability with international portals or other databases is implemented in order to improve IAGOS data discovery. The IGAS data network is composed of three data centres: the IAGOS database in Toulouse including IAGOS-core data and IAGOS-CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container) data since January 2015; the HALO research aircraft database at DLR (https://halo-db.pa.op.dlr.de); and the MACC data centre in Jülich (http://join.iek.fz-juelich.de). The MACC (Monitoring Atmospheric Composition and Climate) project is a prominent user of the IGAS data network. In June 2015 a new version of the IAGOS database will be released providing improved services such as download in NetCDF or NASA Ames formats; graphical tools (maps, scatter plots, etc.); standardized metadata (ISO 19115) and a better users management. The link with the MACC data centre, through JOIN (Jülich OWS Interface), will allow to combine model outputs with IAGOS data for intercomparison. The interoperability within the IGAS data network, implemented thanks to many web services, will improve the functionalities of the web interfaces of each data centre.
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Accuracy of blood transfusion in postpartum hemorrhage to assess maternal morbidity.
Sagot, P; Mourtialon, P; Benzenine, E; Bardou, M; Ferdynus, C; Morel, P; Quantin, C
2012-06-01
To measure the accuracy of blood transfusion (timing and number of blood units) in postpartum hemorrhage (PPH) in a perinatal network. (1) The ANONYMAT software system was used for anonymization and linkage of two large stand-alone databases, the Burgundy Perinatal Network (BPN) and the National Blood Centre (EFS) databases, which contain, respectively, clinical data from hospital discharges and information concerning any blood transfusion in France (considered as the gold standard database for identifying any transfusion). (2) Identification of prescriptions of at least one red blood cell (RBC) unit at the day of delivery (≥22 weeks) and up to 42 days, with manual reviewing of medical records in case of discordant recording. (3) Assessing the sensitivity and positive predictive value of data from the BPN database. Among the 9736 women receiving at least one blood product dispensed between 01/01/2006 and 12/31/2007 and the 35,779 women who delivered, 233 women (0.65% of deliveries) received at least one RBC unit for post partum hemorrhage. In the BPN database according to the type of hospital stay in our perinatal network (delivery stay only, delivery and post-delivery stays), sensitivity and positive predictive value for RBC transfusion ranged from 61.4% (55.1-67.6) to 67.8% (61.8-73.8) and 82.2% (76.5-87.9) to 83.2% (77.8-88.5), respectively. Linkage of both BPN and EFS databases allowed accurate recording of all but one RBC transfusion. Our approach allowed 100% electronic recording of PPH requiring blood transfusion, making it an important sentinel event of maternal morbidity to assess the perinatal network. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
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HBVPathDB: a database of HBV infection-related molecular interaction network.
Zhang, Yi; Bo, Xiao-Chen; Yang, Jing; Wang, Sheng-Qi
2005-03-21
To describe molecules or genes interaction between hepatitis B viruses (HBV) and host, for understanding how virus' and host's genes and molecules are networked to form a biological system and for perceiving mechanism of HBV infection. The knowledge of HBV infection-related reactions was organized into various kinds of pathways with carefully drawn graphs in HBVPathDB. Pathway information is stored with relational database management system (DBMS), which is currently the most efficient way to manage large amounts of data and query is implemented with powerful Structured Query Language (SQL). The search engine is written using Personal Home Page (PHP) with SQL embedded and web retrieval interface is developed for searching with Hypertext Markup Language (HTML). We present the first version of HBVPathDB, which is a HBV infection-related molecular interaction network database composed of 306 pathways with 1 050 molecules involved. With carefully drawn graphs, pathway information stored in HBVPathDB can be browsed in an intuitive way. We develop an easy-to-use interface for flexible accesses to the details of database. Convenient software is implemented to query and browse the pathway information of HBVPathDB. Four search page layout options-category search, gene search, description search, unitized search-are supported by the search engine of the database. The database is freely available at http://www.bio-inf.net/HBVPathDB/HBV/. The conventional perspective HBVPathDB have already contained a considerable amount of pathway information with HBV infection related, which is suitable for in-depth analysis of molecular interaction network of virus and host. HBVPathDB integrates pathway data-sets with convenient software for query, browsing, visualization, that provides users more opportunity to identify regulatory key molecules as potential drug targets and to explore the possible mechanism of HBV infection based on gene expression datasets.
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SIMS: addressing the problem of heterogeneity in databases
NASA Astrophysics Data System (ADS)
Arens, Yigal
1997-02-01
The heterogeneity of remotely accessible databases -- with respect to contents, query language, semantics, organization, etc. -- presents serious obstacles to convenient querying. The SIMS (single interface to multiple sources) system addresses this global integration problem. It does so by defining a single language for describing the domain about which information is stored in the databases and using this language as the query language. Each database to which SIMS is to provide access is modeled using this language. The model describes a database's contents, organization, and other relevant features. SIMS uses these models, together with a planning system drawing on techniques from artificial intelligence, to decompose a given user's high-level query into a series of queries against the databases and other data manipulation steps. The retrieval plan is constructed so as to minimize data movement over the network and maximize parallelism to increase execution speed. SIMS can recover from network failures during plan execution by obtaining data from alternate sources, when possible. SIMS has been demonstrated in the domains of medical informatics and logistics, using real databases.
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Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar
2015-04-01
The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.
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National Transportation Atlas Databases : 2014
DOT National Transportation Integrated Search
2014-01-01
The National Transportation Atlas Databases 2014 : (NTAD2014) is a set of nationwide geographic datasets of : transportation facilities, transportation networks, associated : infrastructure, and other political and administrative entities. : These da...
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National Transportation Atlas Databases : 2015
DOT National Transportation Integrated Search
2015-01-01
The National Transportation Atlas Databases 2015 : (NTAD2015) is a set of nationwide geographic datasets of : transportation facilities, transportation networks, associated : infrastructure, and other political and administrative entities. : These da...
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Improving CD-ROM Management through Networking.
ERIC Educational Resources Information Center
Rutherford, John
1990-01-01
Summarizes advantages, components, and manufacturers of CD-ROM networks based on experiences at the Central Connecticut State University library. Three configurations are described, and the steps in installing a network where a large number of databases are shared by a number of microcomputers are detailed. Licensing and network performance issues…
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Questions to Answer before You Branch out on a CD-ROM Network.
ERIC Educational Resources Information Center
Simpson, Carol Mann
1992-01-01
Examines issues that librarians must address when purchasing databases on CD-ROM for networking. Highlights include network licenses; costs; restrictions on network rights; ownership of CD-ROMs; hardware requirements; fees for upgrading software; CD-ROM servers; pricing options; training materials; and disk drives. (LRW)
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Networking the Light Fantastic--CD-ROMs on LANs.
ERIC Educational Resources Information Center
Kittle, Paul W.
1992-01-01
Describes the development of a local area network (LAN) at Loma Linda University that allows remote access for both IBM and Macintosh microcomputers to CD-ROMs. Topics discussed include types of networks; fiber optic technology; networking CD-ROM drives; remote access; modems; CD-ROM databases; memory management; interface software; and future…
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Airport take-off noise assessment aimed at identify responsible aircraft classes.
Sanchez-Perez, Luis A; Sanchez-Fernandez, Luis P; Shaout, Adnan; Suarez-Guerra, Sergio
2016-01-15
Assessment of aircraft noise is an important task of nowadays airports in order to fight environmental noise pollution given the recent discoveries on the exposure negative effects on human health. Noise monitoring and estimation around airports mostly use aircraft noise signals only for computing statistical indicators and depends on additional data sources so as to determine required inputs such as the aircraft class responsible for noise pollution. In this sense, the noise monitoring and estimation systems have been tried to improve by creating methods for obtaining more information from aircraft noise signals, especially real-time aircraft class recognition. Consequently, this paper proposes a multilayer neural-fuzzy model for aircraft class recognition based on take-off noise signal segmentation. It uses a fuzzy inference system to build a final response for each class p based on the aggregation of K parallel neural networks outputs Op(k) with respect to Linear Predictive Coding (LPC) features extracted from K adjacent signal segments. Based on extensive experiments over two databases with real-time take-off noise measurements, the proposed model performs better than other methods in literature, particularly when aircraft classes are strongly correlated to each other. A new strictly cross-checked database is introduced including more complex classes and real-time take-off noise measurements from modern aircrafts. The new model is at least 5% more accurate with respect to previous database and successfully classifies 87% of measurements in the new database. Copyright © 2015 Elsevier B.V. All rights reserved.
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An Adaptive Database Intrusion Detection System
ERIC Educational Resources Information Center
Barrios, Rita M.
2011-01-01
Intrusion detection is difficult to accomplish when attempting to employ current methodologies when considering the database and the authorized entity. It is a common understanding that current methodologies focus on the network architecture rather than the database, which is not an adequate solution when considering the insider threat. Recent…
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Freshwater Biological Traits Database (Data Sources)
When EPA release the final report, Freshwater Biological Traits Database, it referenced numerous data sources that are included below. The Traits Database report covers the development of a database of freshwater biological traits with additional traits that are relevan...
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An end-to-end workflow for engineering of biological networks from high-level specifications.
Beal, Jacob; Weiss, Ron; Densmore, Douglas; Adler, Aaron; Appleton, Evan; Babb, Jonathan; Bhatia, Swapnil; Davidsohn, Noah; Haddock, Traci; Loyall, Joseph; Schantz, Richard; Vasilev, Viktor; Yaman, Fusun
2012-08-17
We present a workflow for the design and production of biological networks from high-level program specifications. The workflow is based on a sequence of intermediate models that incrementally translate high-level specifications into DNA samples that implement them. We identify algorithms for translating between adjacent models and implement them as a set of software tools, organized into a four-stage toolchain: Specification, Compilation, Part Assignment, and Assembly. The specification stage begins with a Boolean logic computation specified in the Proto programming language. The compilation stage uses a library of network motifs and cellular platforms, also specified in Proto, to transform the program into an optimized Abstract Genetic Regulatory Network (AGRN) that implements the programmed behavior. The part assignment stage assigns DNA parts to the AGRN, drawing the parts from a database for the target cellular platform, to create a DNA sequence implementing the AGRN. Finally, the assembly stage computes an optimized assembly plan to create the DNA sequence from available part samples, yielding a protocol for producing a sample of engineered plasmids with robotics assistance. Our workflow is the first to automate the production of biological networks from a high-level program specification. Furthermore, the workflow's modular design allows the same program to be realized on different cellular platforms simply by swapping workflow configurations. We validated our workflow by specifying a small-molecule sensor-reporter program and verifying the resulting plasmids in both HEK 293 mammalian cells and in E. coli bacterial cells.
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Shea, S; Sengupta, S; Crosswell, A; Clayton, P D
1992-01-01
The developing Integrated Academic Information System (IAIMS) at Columbia-Presbyterian Medical Center provides data sharing links between two separate corporate entities, namely Columbia University Medical School and The Presbyterian Hospital, using a network-based architecture. Multiple database servers with heterogeneous user authentication protocols are linked to this network. "One-stop information shopping" implies one log-on procedure per session, not separate log-on and log-off procedures for each server or application used during a session. These circumstances provide challenges at the policy and technical levels to data security at the network level and insuring smooth information access for end users of these network-based services. Five activities being conducted as part of our security project are described: (1) policy development; (2) an authentication server for the network; (3) Kerberos as a tool for providing mutual authentication, encryption, and time stamping of authentication messages; (4) a prototype interface using Kerberos services to authenticate users accessing a network database server; and (5) a Kerberized electronic signature.
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Classification of ion mobility spectra by functional groups using neural networks
NASA Technical Reports Server (NTRS)
Bell, S.; Nazarov, E.; Wang, Y. F.; Eiceman, G. A.
1999-01-01
Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.
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NASA Astrophysics Data System (ADS)
Çebi, A.; Akdoğan, E.; Celen, A.; Dalkilic, A. S.
2017-02-01
An artificial neural network (ANN) model of friction factor in smooth and microfin tubes under heating, cooling and isothermal conditions was developed in this study. Data used in ANN was taken from a vertically positioned heat exchanger experimental setup. Multi-layered feed-forward neural network with backpropagation algorithm, radial basis function networks and hybrid PSO-neural network algorithm were applied to the database. Inputs were the ratio of cross sectional flow area to hydraulic diameter, experimental condition number depending on isothermal, heating, or cooling conditions and mass flow rate while the friction factor was the output of the constructed system. It was observed that such neural network based system could effectively predict the friction factor values of the flows regardless of their tube types. A dependency analysis to determine the strongest parameter that affected the network and database was also performed and tube geometry was found to be the strongest parameter of all as a result of analysis.
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National Transportation Atlas Databases : 2013
DOT National Transportation Integrated Search
2013-01-01
The National Transportation Atlas Databases 2013 (NTAD2013) is a set of nationwide geographic datasets of transportation facilities, transportation networks, associated infrastructure, and other political and administrative entities. These datasets i...
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Prakash, Peralam Yegneswaran; Irinyi, Laszlo; Halliday, Catriona; Chen, Sharon; Robert, Vincent; Meyer, Wieland
2017-04-01
The increase in public online databases dedicated to fungal identification is noteworthy. This can be attributed to improved access to molecular approaches to characterize fungi, as well as to delineate species within specific fungal groups in the last 2 decades, leading to an ever-increasing complexity of taxonomic assortments and nomenclatural reassignments. Thus, well-curated fungal databases with substantial accurate sequence data play a pivotal role for further research and diagnostics in the field of mycology. This minireview aims to provide an overview of currently available online databases for the taxonomy and identification of human and animal-pathogenic fungi and calls for the establishment of a cloud-based dynamic data network platform. Copyright © 2017 American Society for Microbiology.
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PlantNATsDB: a comprehensive database of plant natural antisense transcripts.
Chen, Dijun; Yuan, Chunhui; Zhang, Jian; Zhang, Zhao; Bai, Lin; Meng, Yijun; Chen, Ling-Ling; Chen, Ming
2012-01-01
Natural antisense transcripts (NATs), as one type of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and pathological processes. Although their important biological functions have been reported widely, a comprehensive database is lacking up to now. Consequently, we constructed a plant NAT database (PlantNATsDB) involving approximately 2 million NAT pairs in 69 plant species. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. PlantNATsDB provides various user-friendly web interfaces to facilitate the presentation of NATs and an integrated, graphical network browser to display the complex networks formed by different NATs. Moreover, a 'Gene Set Analysis' module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs. The PlantNATsDB is freely available at http://bis.zju.edu.cn/pnatdb/.
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Text mining for metabolic pathways, signaling cascades, and protein networks.
Hoffmann, Robert; Krallinger, Martin; Andres, Eduardo; Tamames, Javier; Blaschke, Christian; Valencia, Alfonso
2005-05-10
The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks.
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CerebralWeb: a Cytoscape.js plug-in to visualize networks stratified by subcellular localization.
Frias, Silvia; Bryan, Kenneth; Brinkman, Fiona S L; Lynn, David J
2015-01-01
CerebralWeb is a light-weight JavaScript plug-in that extends Cytoscape.js to enable fast and interactive visualization of molecular interaction networks stratified based on subcellular localization or other user-supplied annotation. The application is designed to be easily integrated into any website and is configurable to support customized network visualization. CerebralWeb also supports the automatic retrieval of Cerebral-compatible localizations for human, mouse and bovine genes via a web service and enables the automated parsing of Cytoscape compatible XGMML network files. CerebralWeb currently supports embedded network visualization on the InnateDB (www.innatedb.com) and Allergy and Asthma Portal (allergen.innatedb.com) database and analysis resources. Database tool URL: http://www.innatedb.com/CerebralWeb © The Author(s) 2015. Published by Oxford University Press.
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Exploring molecular networks using MONET ontology.
Silva, João Paulo Müller da; Lemke, Ney; Mombach, José Carlos; Souza, José Guilherme Camargo de; Sinigaglia, Marialva; Vieira, Renata
2006-03-31
The description of the complex molecular network responsible for cell behavior requires new tools to integrate large quantities of experimental data in the design of biological information systems. These tools could be used in the characterization of these networks and in the formulation of relevant biological hypotheses. The building of an ontology is a crucial step because it integrates in a coherent framework the concepts necessary to accomplish such a task. We present MONET (molecular network), an extensible ontology and an architecture designed to facilitate the integration of data originating from different public databases in a single- and well-documented relational database, that is compatible with MONET formal definition. We also present an example of an application that can easily be implemented using these tools.
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The Design and Implementation of Network Teaching Platform Basing on .NET
NASA Astrophysics Data System (ADS)
Yanna, Ren
This paper addresses the problem that students under traditional teaching model have poor operation ability and studies in depth the network teaching platform in domestic colleges and universities, proposing the design concept of network teaching platform of NET + C # + SQL excellent course and designing the overall structure, function module and back-end database of the platform. This paper emphatically expounds the use of MD5 encryption techniques in order to solve data security problems and the assessment of student learning using ADO.NET database access technology as well as the mathematical formula. The example shows that the network teaching platform developed by using WEB application technology has higher safety and availability, and thus improves the students' operation ability.
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Phylogenetically informed logic relationships improve detection of biological network organization
2011-01-01
Background A "phylogenetic profile" refers to the presence or absence of a gene across a set of organisms, and it has been proven valuable for understanding gene functional relationships and network organization. Despite this success, few studies have attempted to search beyond just pairwise relationships among genes. Here we search for logic relationships involving three genes, and explore its potential application in gene network analyses. Results Taking advantage of a phylogenetic matrix constructed from the large orthologs database Roundup, we invented a method to create balanced profiles for individual triplets of genes that guarantee equal weight on the different phylogenetic scenarios of coevolution between genes. When we applied this idea to LAPP, the method to search for logic triplets of genes, the balanced profiles resulted in significant performance improvement and the discovery of hundreds of thousands more putative triplets than unadjusted profiles. We found that logic triplets detected biological network organization and identified key proteins and their functions, ranging from neighbouring proteins in local pathways, to well separated proteins in the whole pathway, and to the interactions among different pathways at the system level. Finally, our case study suggested that the directionality in a logic relationship and the profile of a triplet could disclose the connectivity between the triplet and surrounding networks. Conclusion Balanced profiles are superior to the raw profiles employed by traditional methods of phylogenetic profiling in searching for high order gene sets. Gene triplets can provide valuable information in detection of biological network organization and identification of key genes at different levels of cellular interaction. PMID:22172058
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Pre-Clinical Drug Prioritization via Prognosis-Guided Genetic Interaction Networks
Xiong, Jianghui; Liu, Juan; Rayner, Simon; Tian, Ze; Li, Yinghui; Chen, Shanguang
2010-01-01
The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call ‘synergistic outcome determination’ (SOD), a concept similar to ‘Synthetic Lethality’. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies. PMID:21085674
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HoPaCI-DB: host-Pseudomonas and Coxiella interaction database
Bleves, Sophie; Dunger, Irmtraud; Walter, Mathias C.; Frangoulidis, Dimitrios; Kastenmüller, Gabi; Voulhoux, Romé; Ruepp, Andreas
2014-01-01
Bacterial infectious diseases are the result of multifactorial processes affected by the interplay between virulence factors and host targets. The host-Pseudomonas and Coxiella interaction database (HoPaCI-DB) is a publicly available manually curated integrative database (http://mips.helmholtz-muenchen.de/HoPaCI/) of host–pathogen interaction data from Pseudomonas aeruginosa and Coxiella burnetii. The resource provides structured information on 3585 experimentally validated interactions between molecules, bioprocesses and cellular structures extracted from the scientific literature. Systematic annotation and interactive graphical representation of disease networks make HoPaCI-DB a versatile knowledge base for biologists and network biology approaches. PMID:24137008
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Wang, James K. T.; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J.
2017-01-01
Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene (HTT), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases. PMID:28611571
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Wang, James K T; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J
2017-01-01
Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene ( HTT ), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases.
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Dziuba, Bartłomiej; Dziuba, Marta
2014-08-20
New peptides with potential antimicrobial activity, encrypted in milk protein sequences, were searched for with the use of bioinformatic tools. The major milk proteins were hydrolyzed in silico by 28 enzymes. The obtained peptides were characterized by the following parameters: molecular weight, isoelectric point, composition and number of amino acid residues, net charge at pH 7.0, aliphatic index, instability index, Boman index, and GRAVY index, and compared with those calculated for known 416 antimicrobial peptides including 59 antimicrobial peptides (AMPs) from milk proteins listed in the BIOPEP database. A simple analysis of physico-chemical properties and the values of biological activity indicators were insufficient to select potentially antimicrobial peptides released in silico from milk proteins by proteolytic enzymes. The final selection was made based on the results of multidimensional statistical analysis such as support vector machines (SVM), random forest (RF), artificial neural networks (ANN) and discriminant analysis (DA) available in the Collection of Anti-Microbial Peptides (CAMP database). Eleven new peptides with potential antimicrobial activity were selected from all peptides released during in silico proteolysis of milk proteins.
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Dziuba, Bartłomiej; Dziuba, Marta
2014-01-01
New peptides with potential antimicrobial activity, encrypted in milk protein sequences, were searched for with the use of bioinformatic tools. The major milk proteins were hydrolyzed in silico by 28 enzymes. The obtained peptides were characterized by the following parameters: molecular weight, isoelectric point, composition and number of amino acid residues, net charge at pH 7.0, aliphatic index, instability index, Boman index, and GRAVY index, and compared with those calculated for known 416 antimicrobial peptides including 59 antimicrobial peptides (AMPs) from milk proteins listed in the BIOPEP database. A simple analysis of physico-chemical properties and the values of biological activity indicators were insufficient to select potentially antimicrobial peptides released in silico from milk proteins by proteolytic enzymes. The final selection was made based on the results of multidimensional statistical analysis such as support vector machines (SVM), random forest (RF), artificial neural networks (ANN) and discriminant analysis (DA) available in the Collection of Anti-Microbial Peptides (CAMP database). Eleven new peptides with potential antimicrobial activity were selected from all peptides released during in silico proteolysis of milk proteins. PMID:25141106
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Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.
Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin
2017-08-10
Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.
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Organization and dissemination of multimedia medical databases on the WWW.
Todorovski, L; Ribaric, S; Dimec, J; Hudomalj, E; Lunder, T
1999-01-01
In the paper, we focus on the problem of building and disseminating multimedia medical databases on the World Wide Web (WWW). The current results of the ongoing project of building a prototype dermatology images database and its WWW presentation are presented. The dermatology database is part of an ambitious plan concerning an organization of a network of medical institutions building distributed and federated multimedia databases of a much wider scale.
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Data Base Management: Proceedings of a Conference, November 1-2, 1984 Held at Monterey, California.
1985-07-31
Dolby Put the Information in the San Jose State University Database Not the Program San Jose , California 4:15 Douglas Lenat Relevance of Machine...network model permits multiple owners for one subsidi- ary entity. The DAPLEX network model includes the subset connection as well. I The SOCRATE system... Jose State University San Js, California -. A ..... .. .... [. . . ...- . . . - Js . . . .*es L * Dolby** PUT TIM INFORMATION IN THE DATABASE, NOT THE
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Ionospheric characteristics for archiving at the World Data Centers. Technical report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gamache, R.R.; Reinisch, B.W.
1990-12-01
A database structure for archiving ionospheric characteristics at uneven data rates was developed at the July 1989 Ionospheric Informatics Working Group (IIWG) Lowell Workshop in Digital Ionogram Data Formats for World Data Center Archiving. This structure is proposed as a new URSI standard and is being employed by the World Data Center A for solar terrestrial physics for archiving characteristics. Here the database has been slightly refined for the application and programs written to generate these database files using as input Digisonde 256 ARTIST data, post processed by the ULCAR ADEP (ARTIST Data Editing Program) system. The characteristics program asmore » well as supplemental programs developed for this task are described here. The new software will make it possible to archive the ionospheric characteristics from the Geophysics Laboratory high latitude Digisonde network, the AWS DISS and the international Digisonde networks, and other ionospheric sounding networks.« less
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RAIN: RNA–protein Association and Interaction Networks
Junge, Alexander; Refsgaard, Jan C.; Garde, Christian; Pan, Xiaoyong; Santos, Alberto; Alkan, Ferhat; Anthon, Christian; von Mering, Christian; Workman, Christopher T.; Jensen, Lars Juhl; Gorodkin, Jan
2017-01-01
Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA–RNA and ncRNA–protein interactions and its integration with the STRING database of protein–protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data, interaction predictions and automatic literature mining. RAIN uses an integrative scoring scheme to assign a confidence score to each interaction. We demonstrate that RAIN outperforms the underlying microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated through an easily accessible web interface and all interaction data can be downloaded. Database URL: http://rth.dk/resources/rain PMID:28077569
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Method for a dummy CD mirror server based on NAS
NASA Astrophysics Data System (ADS)
Tang, Muna; Pei, Jing
2002-09-01
With the development of computer network, information sharing is becoming the necessity in human life. The rapid development of CD-ROM and CD-ROM driver techniques makes it possible to issue large database online. After comparing many designs of dummy CD mirror database, which are the embodiment of a main product in CD-ROM database now and in near future, we proposed and realized a new PC based scheme. Our system has the following merits, such as, supporting all kinds of CD format; supporting many network protocol; the independence of mirror network server and the main server; low price, super large capacity, without the need of any special hardware. Preliminarily experiments have verified the validity of the proposed scheme. Encouraged by the promising application future, we are now preparing to put it into market. This paper discusses the design and implement of the CD-ROM server detailedly.
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Computer Security Products Technology Overview
1988-10-01
13 3. DATABASE MANAGEMENT SYSTEMS ................................... 15 Definition...this paper addresses fall into the areas of multi-user hosts, database management systems (DBMS), workstations, networks, guards and gateways, and...provide a portion of that protection, for example, a password scheme, a file protection mechanism, a secure database management system, or even a
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The EPA DSSTox website (http://www/epa.gov/nheerl/dsstox) publishes standardized, structure-annotated toxicity databases, covering a broad range of toxicity disciplines. Each DSSTox database features documentation written in collaboration with the source authors and toxicity expe...
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Transformation of social networks in the late pre-Hispanic US Southwest.
Mills, Barbara J; Clark, Jeffery J; Peeples, Matthew A; Haas, W R; Roberts, John M; Hill, J Brett; Huntley, Deborah L; Borck, Lewis; Breiger, Ronald L; Clauset, Aaron; Shackley, M Steven
2013-04-09
The late pre-Hispanic period in the US Southwest (A.D. 1200-1450) was characterized by large-scale demographic changes, including long-distance migration and population aggregation. To reconstruct how these processes reshaped social networks, we compiled a comprehensive artifact database from major sites dating to this interval in the western Southwest. We combine social network analysis with geographic information systems approaches to reconstruct network dynamics over 250 y. We show how social networks were transformed across the region at previously undocumented spatial, temporal, and social scales. Using well-dated decorated ceramics, we track changes in network topology at 50-y intervals to show a dramatic shift in network density and settlement centrality from the northern to the southern Southwest after A.D. 1300. Both obsidian sourcing and ceramic data demonstrate that long-distance network relationships also shifted from north to south after migration. Surprisingly, social distance does not always correlate with spatial distance because of the presence of network relationships spanning long geographic distances. Our research shows how a large network in the southern Southwest grew and then collapsed, whereas networks became more fragmented in the northern Southwest but persisted. The study also illustrates how formal social network analysis may be applied to large-scale databases of material culture to illustrate multigenerational changes in network structure.
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Transformation of social networks in the late pre-Hispanic US Southwest
Mills, Barbara J.; Clark, Jeffery J.; Peeples, Matthew A.; Haas, W. R.; Roberts, John M.; Hill, J. Brett; Huntley, Deborah L.; Borck, Lewis; Breiger, Ronald L.; Clauset, Aaron; Shackley, M. Steven
2013-01-01
The late pre-Hispanic period in the US Southwest (A.D. 1200–1450) was characterized by large-scale demographic changes, including long-distance migration and population aggregation. To reconstruct how these processes reshaped social networks, we compiled a comprehensive artifact database from major sites dating to this interval in the western Southwest. We combine social network analysis with geographic information systems approaches to reconstruct network dynamics over 250 y. We show how social networks were transformed across the region at previously undocumented spatial, temporal, and social scales. Using well-dated decorated ceramics, we track changes in network topology at 50-y intervals to show a dramatic shift in network density and settlement centrality from the northern to the southern Southwest after A.D. 1300. Both obsidian sourcing and ceramic data demonstrate that long-distance network relationships also shifted from north to south after migration. Surprisingly, social distance does not always correlate with spatial distance because of the presence of network relationships spanning long geographic distances. Our research shows how a large network in the southern Southwest grew and then collapsed, whereas networks became more fragmented in the northern Southwest but persisted. The study also illustrates how formal social network analysis may be applied to large-scale databases of material culture to illustrate multigenerational changes in network structure. PMID:23530201
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McDonnell, Mark D.; Tissera, Migel D.; Vladusich, Tony; van Schaik, André; Tapson, Jonathan
2015-01-01
Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the ‘Extreme Learning Machine’ (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random ‘receptive field’ sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems. PMID:26262687
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IAU Meteor Data Center-the shower database: A status report
NASA Astrophysics Data System (ADS)
Jopek, Tadeusz Jan; Kaňuchová, Zuzana
2017-09-01
Currently, the meteor shower part of Meteor Data Center database includes: 112 established showers, 563 in the working list, among them 36 have the pro tempore status. The list of shower complexes contains 25 groups, 3 have established status and 1 has the pro tempore status. In the past three years, new meteor showers submitted to the MDC database were detected amongst the meteors observed by CAMS stations (Cameras for Allsky Meteor Surveillance), those included in the EDMOND (European viDeo MeteOr Network Database), those collected by the Japanese SonotaCo Network, recorded in the IMO (International Meteor Organization) database, observed by the Croatian Meteor Network and on the Southern Hemisphere by the SAAMER radar. At the XXIX General Assembly of the IAU in Honolulu, Hawaii in 2015, the names of 18 showers were officially accepted and moved to the list of established ones. Also, one shower already officially named (3/SIA the Southern iota Aquariids) was moved back to the working list of meteor showers. At the XXIX GA IAU the basic shower nomenclature rule was modified, the new formulation predicates ;The general rule is that a meteor shower (and a meteoroid stream) should be named after the constellation that contains the nearest star to the radiant point, using the possessive Latin form;. Over the last three years the MDC database was supplemented with the earlier published original data on meteor showers, which permitted verification of the correctness of the MDC data and extension of bibliographic information. Slowly but surely new database software options are implemented, and software bugs are corrected.
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Mass-storage management for distributed image/video archives
NASA Astrophysics Data System (ADS)
Franchi, Santina; Guarda, Roberto; Prampolini, Franco
1993-04-01
The realization of image/video database requires a specific design for both database structures and mass storage management. This issue has addressed the project of the digital image/video database system that has been designed at IBM SEMEA Scientific & Technical Solution Center. Proper database structures have been defined to catalog image/video coding technique with the related parameters, and the description of image/video contents. User workstations and servers are distributed along a local area network. Image/video files are not managed directly by the DBMS server. Because of their wide size, they are stored outside the database on network devices. The database contains the pointers to the image/video files and the description of the storage devices. The system can use different kinds of storage media, organized in a hierarchical structure. Three levels of functions are available to manage the storage resources. The functions of the lower level provide media management. They allow it to catalog devices and to modify device status and device network location. The medium level manages image/video files on a physical basis. It manages file migration between high capacity media and low access time media. The functions of the upper level work on image/video file on a logical basis, as they archive, move and copy image/video data selected by user defined queries. These functions are used to support the implementation of a storage management strategy. The database information about characteristics of both storage devices and coding techniques are used by the third level functions to fit delivery/visualization requirements and to reduce archiving costs.
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Network-Based Visual Analysis of Tabular Data
ERIC Educational Resources Information Center
Liu, Zhicheng
2012-01-01
Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look…
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Distributing stand inventory data and maps over a wide area network
Thomas E. Burk
2000-01-01
High-speed networks connecting multiple levels of management are becoming commonplace among forest resources organizations. Such networks can be used to deliver timely spatial and aspatial data relevant to the management of stands to field personnel. A network infrastructure allows maintenance of cost-effective, centralized databases with the potential for updating by...
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LavaNet—Neural network development environment in a general mine planning package
NASA Astrophysics Data System (ADS)
Kapageridis, Ioannis Konstantinou; Triantafyllou, A. G.
2011-04-01
LavaNet is a series of scripts written in Perl that gives access to a neural network simulation environment inside a general mine planning package. A well known and a very popular neural network development environment, the Stuttgart Neural Network Simulator, is used as the base for the development of neural networks. LavaNet runs inside VULCAN™—a complete mine planning package with advanced database, modelling and visualisation capabilities. LavaNet is taking advantage of VULCAN's Perl based scripting environment, Lava, to bring all the benefits of neural network development and application to geologists, mining engineers and other users of the specific mine planning package. LavaNet enables easy development of neural network training data sets using information from any of the data and model structures available, such as block models and drillhole databases. Neural networks can be trained inside VULCAN™ and the results be used to generate new models that can be visualised in 3D. Direct comparison of developed neural network models with conventional and geostatistical techniques is now possible within the same mine planning software package. LavaNet supports Radial Basis Function networks, Multi-Layer Perceptrons and Self-Organised Maps.
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Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.
Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi
2007-10-04
In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.
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Determining root correspondence between previously and newly detected objects
Paglieroni, David W.; Beer, N Reginald
2014-06-17
A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.
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Databases as policy instruments. About extending networks as evidence-based policy.
de Bont, Antoinette; Stoevelaar, Herman; Bal, Roland
2007-12-07
This article seeks to identify the role of databases in health policy. Access to information and communication technologies has changed traditional relationships between the state and professionals, creating new systems of surveillance and control. As a result, databases may have a profound effect on controlling clinical practice. We conducted three case studies to reconstruct the development and use of databases as policy instruments. Each database was intended to be employed to control the use of one particular pharmaceutical in the Netherlands (growth hormone, antiretroviral drugs for HIV and Taxol, respectively). We studied the archives of the Dutch Health Insurance Board, conducted in-depth interviews with key informants and organized two focus groups, all focused on the use of databases both in policy circles and in clinical practice. Our results demonstrate that policy makers hardly used the databases, neither for cost control nor for quality assurance. Further analysis revealed that these databases facilitated self-regulation and quality assurance by (national) bodies of professionals, resulting in restrictive prescription behavior amongst physicians. The databases fulfill control functions that were formerly located within the policy realm. The databases facilitate collaboration between policy makers and physicians, since they enable quality assurance by professionals. Delegating regulatory authority downwards into a network of physicians who control the use of pharmaceuticals seems to be a good alternative for centralized control on the basis of monitoring data.
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Lee, A Yeong; Park, Won; Kang, Tae-Wook; Cha, Min Ho; Chun, Jin Mi
2018-07-15
Yijin-Tang (YJT) is a traditional prescription for the treatment of hyperlipidaemia, atherosclerosis and other ailments related to dampness phlegm, a typical pathological symptom of abnormal body fluid metabolism in Traditional Korean Medicine. However, a holistic network pharmacology approach to understanding the therapeutic mechanisms underlying hyperlipidaemia and atherosclerosis has not been pursued. To examine the network pharmacological potential effects of YJT on hyperlipidaemia and atherosclerosis, we analysed components, performed target prediction and network analysis, and investigated interacting pathways using a network pharmacology approach. Information on compounds in herbal medicines was obtained from public databases, and oral bioavailability and drug-likeness was screened using absorption, distribution, metabolism, and excretion (ADME) criteria. Correlations between compounds and genes were linked using the STITCH database, and genes related to hyperlipidaemia and atherosclerosis were gathered using the GeneCards database. Human genes were identified and subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Network analysis identified 447 compounds in five herbal medicines that were subjected to ADME screening, and 21 compounds and 57 genes formed the main pathways linked to hyperlipidaemia and atherosclerosis. Among them, 10 compounds (naringenin, nobiletin, hesperidin, galangin, glycyrrhizin, homogentisic acid, stigmasterol, 6-gingerol, quercetin and glabridin) were linked to more than four genes, and are bioactive compounds and key chemicals. Core genes in this network were CASP3, CYP1A1, CYP1A2, MMP2 and MMP9. The compound-target gene network revealed close interactions between multiple components and multiple targets, and facilitates a better understanding of the potential therapeutic effects of YJT. Pharmacological network analysis can help to explain the potential effects of YJT for treating dampness phlegm-related diseases such as hyperlipidaemia and atherosclerosis. Copyright © 2018 Elsevier B.V. All rights reserved.
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Slimani, N; Deharveng, G; Unwin, I; Southgate, D A T; Vignat, J; Skeie, G; Salvini, S; Parpinel, M; Møller, A; Ireland, J; Becker, W; Farran, A; Westenbrink, S; Vasilopoulou, E; Unwin, J; Borgejordet, A; Rohrmann, S; Church, S; Gnagnarella, P; Casagrande, C; van Bakel, M; Niravong, M; Boutron-Ruault, M C; Stripp, C; Tjønneland, A; Trichopoulou, A; Georga, K; Nilsson, S; Mattisson, I; Ray, J; Boeing, H; Ocké, M; Peeters, P H M; Jakszyn, P; Amiano, P; Engeset, D; Lund, E; de Magistris, M Santucci; Sacerdote, C; Welch, A; Bingham, S; Subar, A F; Riboli, E
2007-09-01
This paper describes the ad hoc methodological concepts and procedures developed to improve the comparability of Nutrient databases (NDBs) across the 10 European countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). This was required because there is currently no European reference NDB available. A large network involving national compilers, nutritionists and experts on food chemistry and computer science was set up for the 'EPIC Nutrient DataBase' (ENDB) project. A total of 550-1500 foods derived from about 37,000 standardized EPIC 24-h dietary recalls (24-HDRS) were matched as closely as possible to foods available in the 10 national NDBs. The resulting national data sets (NDS) were then successively documented, standardized and evaluated according to common guidelines and using a DataBase Management System specifically designed for this project. The nutrient values of foods unavailable or not readily available in NDSs were approximated by recipe calculation, weighted averaging or adjustment for weight changes and vitamin/mineral losses, using common algorithms. The final ENDB contains about 550-1500 foods depending on the country and 26 common components. Each component value was documented and standardized for unit, mode of expression, definition and chemical method of analysis, as far as possible. Furthermore, the overall completeness of NDSs was improved (>or=99%), particularly for beta-carotene and vitamin E. The ENDB constitutes a first real attempt to improve the comparability of NDBs across European countries. This methodological work will provide a useful tool for nutritional research as well as end-user recommendations to improve NDBs in the future.
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dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins.
Huang, Kai-Yao; Su, Min-Gang; Kao, Hui-Ju; Hsieh, Yun-Chung; Jhong, Jhih-Hua; Cheng, Kuang-Hao; Huang, Hsien-Da; Lee, Tzong-Yi
2016-01-04
Owing to the importance of the post-translational modifications (PTMs) of proteins in regulating biological processes, the dbPTM (http://dbPTM.mbc.nctu.edu.tw/) was developed as a comprehensive database of experimentally verified PTMs from several databases with annotations of potential PTMs for all UniProtKB protein entries. For this 10th anniversary of dbPTM, the updated resource provides not only a comprehensive dataset of experimentally verified PTMs, supported by the literature, but also an integrative interface for accessing all available databases and tools that are associated with PTM analysis. As well as collecting experimental PTM data from 14 public databases, this update manually curates over 12 000 modified peptides, including the emerging S-nitrosylation, S-glutathionylation and succinylation, from approximately 500 research articles, which were retrieved by text mining. As the number of available PTM prediction methods increases, this work compiles a non-homologous benchmark dataset to evaluate the predictive power of online PTM prediction tools. An increasing interest in the structural investigation of PTM substrate sites motivated the mapping of all experimental PTM peptides to protein entries of Protein Data Bank (PDB) based on database identifier and sequence identity, which enables users to examine spatially neighboring amino acids, solvent-accessible surface area and side-chain orientations for PTM substrate sites on tertiary structures. Since drug binding in PDB is annotated, this update identified over 1100 PTM sites that are associated with drug binding. The update also integrates metabolic pathways and protein-protein interactions to support the PTM network analysis for a group of proteins. Finally, the web interface is redesigned and enhanced to facilitate access to this resource. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
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SIRSALE: integrated video database management tools
NASA Astrophysics Data System (ADS)
Brunie, Lionel; Favory, Loic; Gelas, J. P.; Lefevre, Laurent; Mostefaoui, Ahmed; Nait-Abdesselam, F.
2002-07-01
Video databases became an active field of research during the last decade. The main objective in such systems is to provide users with capabilities to friendly search, access and playback distributed stored video data in the same way as they do for traditional distributed databases. Hence, such systems need to deal with hard issues : (a) video documents generate huge volumes of data and are time sensitive (streams must be delivered at a specific bitrate), (b) contents of video data are very hard to be automatically extracted and need to be humanly annotated. To cope with these issues, many approaches have been proposed in the literature including data models, query languages, video indexing etc. In this paper, we present SIRSALE : a set of video databases management tools that allow users to manipulate video documents and streams stored in large distributed repositories. All the proposed tools are based on generic models that can be customized for specific applications using ad-hoc adaptation modules. More precisely, SIRSALE allows users to : (a) browse video documents by structures (sequences, scenes, shots) and (b) query the video database content by using a graphical tool, adapted to the nature of the target video documents. This paper also presents an annotating interface which allows archivists to describe the content of video documents. All these tools are coupled to a video player integrating remote VCR functionalities and are based on active network technology. So, we present how dedicated active services allow an optimized video transport for video streams (with Tamanoir active nodes). We then describe experiments of using SIRSALE on an archive of news video and soccer matches. The system has been demonstrated to professionals with a positive feedback. Finally, we discuss open issues and present some perspectives.
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NetIntel: A Database for Manipulation of Rich Social Network Data
2005-03-03
between entities in a social or organizational system. For most of its history , social network analysis has operated on a notion of a dataset - a clearly...and procedural), as well as stored procedure and trigger capabilities. For the current implementation, we have chosen PostgreSQL [1] database. Of the...data and easy-to-use facilities for export of data into analysis tools as well as online browsing and data entry. References [1] Postgresql
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Liao, Stephen Shaoyi; Wang, Huai Qing; Li, Qiu Dan; Liu, Wei Yi
2006-06-01
This paper presents a new method for learning Bayesian networks from functional dependencies (FD) and third normal form (3NF) tables in relational databases. The method sets up a linkage between the theory of relational databases and probabilistic reasoning models, which is interesting and useful especially when data are incomplete and inaccurate. The effectiveness and practicability of the proposed method is demonstrated by its implementation in a mobile commerce system.
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Bousquet, P-J; Demoly, P; Romano, A; Aberer, W; Bircher, A; Blanca, M; Brockow, K; Pichler, W; Torres, M J; Terreehorst, I; Arnoux, B; Atanaskovic-Markovic, M; Barbaud, A; Bijl, A; Bonadonna, P; Burney, P G; Caimmi, S; Canonica, G W; Cernadas, J; Dahlen, B; Daures, J-P; Fernandez, J; Gomes, E; Gueant, J-L; Kowalski, M L; Kvedariene, V; Mertes, P-M; Martins, P; Nizankowska-Mogilnicka, E; Papadopoulos, N; Ponvert, C; Pirmohamed, M; Ring, J; Salapatas, M; Sanz, M L; Szczeklik, A; Van Ganse, E; De Weck, A L; Zuberbier, T; Merk, H F; Sachs, B; Sidoroff, A
2009-02-01
Nonallergic hypersensitivity and allergic reactions are part of the many different types of adverse drug reactions (ADRs). Databases exist for the collection of ADRs. Spontaneous reporting makes up the core data-generating system of pharmacovigilance, but there is a large under-estimation of allergy/hypersensitivity drug reactions. A specific database is therefore required for drug allergy and hypersensitivity using standard operating procedures (SOPs), as the diagnosis of drug allergy/hypersensitivity is difficult and current pharmacovigilance algorithms are insufficient. Although difficult, the diagnosis of drug allergy/hypersensitivity has been standardized by the European Network for Drug Allergy (ENDA) under the aegis of the European Academy of Allergology and Clinical Immunology and SOPs have been published. Based on ENDA and Global Allergy and Asthma European Network (GA(2)LEN, EU Framework Programme 6) SOPs, a Drug Allergy and Hypersensitivity Database (DAHD((R))) has been established under FileMaker((R)) Pro 9. It is already available online in many different languages and can be accessed using a personal login. GA(2)LEN is a European network of 27 partners (16 countries) and 59 collaborating centres (26 countries), which can coordinate and implement the DAHD across Europe. The GA(2)LEN-ENDA-DAHD platform interacting with a pharmacovigilance network appears to be of great interest for the reporting of allergy/hypersensitivity ADRs in conjunction with other pharmacovigilance instruments.
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Firnkorn, D; Ganzinger, M; Muley, T; Thomas, M; Knaup, P
2015-01-01
Joint data analysis is a key requirement in medical research networks. Data are available in heterogeneous formats at each network partner and their harmonization is often rather complex. The objective of our paper is to provide a generic approach for the harmonization process in research networks. We applied the process when harmonizing data from three sites for the Lung Cancer Phenotype Database within the German Center for Lung Research. We developed a spreadsheet-based solution as tool to support the harmonization process for lung cancer data and a data integration procedure based on Talend Open Studio. The harmonization process consists of eight steps describing a systematic approach for defining and reviewing source data elements and standardizing common data elements. The steps for defining common data elements and harmonizing them with local data definitions are repeated until consensus is reached. Application of this process for building the phenotype database led to a common basic data set on lung cancer with 285 structured parameters. The Lung Cancer Phenotype Database was realized as an i2b2 research data warehouse. Data harmonization is a challenging task requiring informatics skills as well as domain knowledge. Our approach facilitates data harmonization by providing guidance through a uniform process that can be applied in a wide range of projects.
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Application of WebGIS for traffic risk assessment
NASA Astrophysics Data System (ADS)
Voumard, Jérémie; Aye, Zar Chi; Derron, Marc-Henri; Jaboyedoff, Michel
2015-04-01
Roads and railways are threatened throughout the year by several natural hazards around the world, leading to the closing of transportation corridors, loss of access, deviation travels and potentially infrastructures damages and loss of human lives and also financial, social and economic consequences. Protection measures used to reduce the exposure to natural hazards are usually expensive and cannot be deployed on an entire transportation network. It is thus necessary to choose priority areas where protection measures need to be built. The aim of this study is to propose a friendly tool to evaluate and to understand issues and consequences of section closing and affected parts of a transportation network at small region scale. The proposed tool, currently in its design and building phase, will provide ways to simulate different closure scenarios and to analyze their consequences on transportation network; like deviating traffic on others roads and railways sections, additional time and distance travel or accessibility for emergency services like police, firefighters and ambulances. The tool is based on OpenGeo architecture, which is composed of open-source components. It integrates PostGIS for database, GeoServer and GeoWebCache for application servers and finally GeoExt and OpenLayers for user interface. Users will be able to attribute quantitative (like roads and railway type and closure consequences) and qualitative (like section unavailability duration, season, etc.) data to the different roads and railways sections based on their user rights. They will also be able to evaluate different track closures consequences in terms of different scenarios. Once finalized, the goal of this project including natural hazards, traffic and geomatic thematic is to propose a decision support tool for public authorities firstly and for specialists secondly so that they can evaluate easily and accurately as much as possible to highlight the weakpoints of the transportation network in the case track closures due to natural hazards.
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Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information
Jang, Haeran
2014-01-01
Objectives Utilizing social network analysis, this study aimed to analyze the main keywords in the literature regarding the health literacy of and the use of online health information by aged persons over 65. Methods Medical Subject Heading keywords were extracted from articles on the PubMed database of the National Library of Medicine. For health literacy, 110 articles out of 361 were initially extracted. Seventy-one keywords out of 1,021 were finally selected after removing repeated keywords and applying pruning. Regarding the use of online health information, 19 articles out of 26 were selected. One hundred forty-four keywords were initially extracted. After removing the repeated keywords, 74 keywords were finally selected. Results Health literacy was found to be strongly connected with 'Health knowledge, attitudes, practices' and 'Patient education as topic.' 'Computer literacy' had strong connections with 'Internet' and 'Attitude towards computers.' 'Computer literacy' was connected to 'Health literacy,' and was studied according to the parameters 'Attitude towards health' and 'Patient education as topic.' The use of online health information was strongly connected with 'Health knowledge, attitudes, practices,' 'Consumer health information,' 'Patient education as topic,' etc. In the network, 'Computer literacy' was connected with 'Health education,' 'Patient satisfaction,' 'Self-efficacy,' 'Attitude to computer,' etc. Conclusions Research on older citizens' health literacy and their use of online health information was conducted together with study of computer literacy, patient education, attitude towards health, health education, patient satisfaction, etc. In particular, self-efficacy was noted as an important keyword. Further research should be conducted to identify the effective outcomes of self-efficacy in the area of interest. PMID:25152835
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The Philip Morris Information Network: A Library Database on an In-House Timesharing System.
ERIC Educational Resources Information Center
DeBardeleben, Marian Z.; And Others
1983-01-01
Outlines a database constructed at Philip Morris Research Center Library which encompasses holdings and circulation and acquisitions records for all items in the library. Host computer (DECSYSTEM-2060), software (BASIC), database design, search methodology, cataloging, and accessibility are noted; sample search, circ-in profile, end user profiles,…
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Code of Federal Regulations, 2010 CFR
2010-10-01
... database or spectrum sensing. (b) Client device. A TVBD operating in client mode. (c) Client mode. An... TVBD is able to select a channel itself based on a list provided by the database and initiate a network... does not require use of a geo-location capability or access to the TV bands database and requires...
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Tao of Gateway: Providing Internet Access to Licensed Databases.
ERIC Educational Resources Information Center
McClellan, Gregory A.; Garrison, William V.
1997-01-01
Illustrates an approach for providing networked access to licensed databases over the Internet by positioning the library between patron and vendor. Describes how the gateway systems and database connection servers work and discusses how treatment of security has evolved with the introduction of the World Wide Web. Outlines plans to reimplement…
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A Database Design and Development Case: NanoTEK Networks
ERIC Educational Resources Information Center
Ballenger, Robert M.
2010-01-01
This case provides a real-world project-oriented case study for students enrolled in a management information systems, database management, or systems analysis and design course in which database design and development are taught. The case consists of a business scenario to provide background information and details of the unique operating…
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The Design of Lexical Database for Indonesian Language
NASA Astrophysics Data System (ADS)
Gunawan, D.; Amalia, A.
2017-03-01
Kamus Besar Bahasa Indonesia (KBBI), an official dictionary for Indonesian language, provides lists of words with their meaning. The online version can be accessed via Internet network. Another online dictionary is Kateglo. KBBI online and Kateglo only provides an interface for human. A machine cannot retrieve data from the dictionary easily without using advanced techniques. Whereas, lexical of words is required in research or application development which related to natural language processing, text mining, information retrieval or sentiment analysis. To address this requirement, we need to build a lexical database which provides well-defined structured information about words. A well-known lexical database is WordNet, which provides the relation among words in English. This paper proposes the design of a lexical database for Indonesian language based on the combination of KBBI 4th edition, Kateglo and WordNet structure. Knowledge representation by utilizing semantic networks depict the relation among words and provide the new structure of lexical database for Indonesian language. The result of this design can be used as the foundation to build the lexical database for Indonesian language.
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Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases
Zhang, Hongpo
2018-01-01
Quantitative analysis and prediction can help to reduce the risk of cardiovascular disease. Quantitative prediction based on traditional model has low accuracy. The variance of model prediction based on shallow neural network is larger. In this paper, cardiovascular disease prediction model based on improved deep belief network (DBN) is proposed. Using the reconstruction error, the network depth is determined independently, and unsupervised training and supervised optimization are combined. It ensures the accuracy of model prediction while guaranteeing stability. Thirty experiments were performed independently on the Statlog (Heart) and Heart Disease Database data sets in the UCI database. Experimental results showed that the mean of prediction accuracy was 91.26% and 89.78%, respectively. The variance of prediction accuracy was 5.78 and 4.46, respectively. PMID:29854369
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Cytoscape: a software environment for integrated models of biomolecular interaction networks.
Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey
2003-11-01
Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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Consulting report on the NASA technology utilization network system
NASA Technical Reports Server (NTRS)
Hlava, Marjorie M. K.
1992-01-01
The purposes of this consulting effort are: (1) to evaluate the existing management and production procedures and workflow as they each relate to the successful development, utilization, and implementation of the NASA Technology Utilization Network System (TUNS) database; (2) to identify, as requested by the NASA Project Monitor, the strengths, weaknesses, areas of bottlenecking, and previously unaddressed problem areas affecting TUNS; (3) to recommend changes or modifications of existing procedures as necessary in order to effect corrections for the overall benefit of NASA TUNS database production, implementation, and utilization; and (4) to recommend the addition of alternative procedures, routines, and activities that will consolidate and facilitate the production, implementation, and utilization of the NASA TUNS database.
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Constructing a Graph Database for Semantic Literature-Based Discovery.
Hristovski, Dimitar; Kastrin, Andrej; Dinevski, Dejan; Rindflesch, Thomas C
2015-01-01
Literature-based discovery (LBD) generates discoveries, or hypotheses, by combining what is already known in the literature. Potential discoveries have the form of relations between biomedical concepts; for example, a drug may be determined to treat a disease other than the one for which it was intended. LBD views the knowledge in a domain as a network; a set of concepts along with the relations between them. As a starting point, we used SemMedDB, a database of semantic relations between biomedical concepts extracted with SemRep from Medline. SemMedDB is distributed as a MySQL relational database, which has some problems when dealing with network data. We transformed and uploaded SemMedDB into the Neo4j graph database, and implemented the basic LBD discovery algorithms with the Cypher query language. We conclude that storing the data needed for semantic LBD is more natural in a graph database. Also, implementing LBD discovery algorithms is conceptually simpler with a graph query language when compared with standard SQL.
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The Erector Set Computer: Building a Virtual Workstation over a Large Multi-Vendor Network.
ERIC Educational Resources Information Center
Farago, John M.
1989-01-01
Describes a computer network developed at the City University of New York Law School that uses device sharing and local area networking to create a simulated law office. Topics discussed include working within a multi-vendor environment, and the communication, information, and database access services available through the network. (CLB)
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Pitkänen, Esa; Akerlund, Arto; Rantanen, Ari; Jouhten, Paula; Ukkonen, Esko
2008-08-25
ReMatch is a web-based, user-friendly tool that constructs stoichiometric network models for metabolic flux analysis, integrating user-developed models into a database collected from several comprehensive metabolic data resources, including KEGG, MetaCyc and CheBI. Particularly, ReMatch augments the metabolic reactions of the model with carbon mappings to facilitate (13)C metabolic flux analysis. The construction of a network model consisting of biochemical reactions is the first step in most metabolic modelling tasks. This model construction can be a tedious task as the required information is usually scattered to many separate databases whose interoperability is suboptimal, due to the heterogeneous naming conventions of metabolites in different databases. Another, particularly severe data integration problem is faced in (13)C metabolic flux analysis, where the mappings of carbon atoms from substrates into products in the model are required. ReMatch has been developed to solve the above data integration problems. First, ReMatch matches the imported user-developed model against the internal ReMatch database while considering a comprehensive metabolite name thesaurus. This, together with wild card support, allows the user to specify the model quickly without having to look the names up manually. Second, ReMatch is able to augment reactions of the model with carbon mappings, obtained either from the internal database or given by the user with an easy-touse tool. The constructed models can be exported into 13C-FLUX and SBML file formats. Further, a stoichiometric matrix and visualizations of the network model can be generated. The constructed models of metabolic networks can be optionally made available to the other users of ReMatch. Thus, ReMatch provides a common repository for metabolic network models with carbon mappings for the needs of metabolic flux analysis community. ReMatch is freely available for academic use at http://www.cs.helsinki.fi/group/sysfys/software/rematch/.
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NASA Astrophysics Data System (ADS)
Wang, Gangbo; Guan, Jiancheng
2011-12-01
This article contributes to the growing study on the interactions between science and technology with China's evidence in the field of nanotechnology, based on the database of United States Patent and Trademark Office. The analysis is focused during the period of 1991-2008, a rapid increasing period for the development of nanotechnology. Using the non-patent references cited by patents, we first investigate the science-technology connections in the context of Chinese nanotechnology, especially in institutional sectors and its application fields. Those patents, produced by academic researchers and directed towards basic scientific knowledge, generally cite more scientific references with a higher proportion of self-citations. It is interesting to find that patents contributed by collaborations between public organizations and corporations seldom contain scientific references. Following an interesting path on matching the data of publications and patents, we establish the author-inventor links in this emerging field. Author-inventors, who are co-active in publishing and patenting, are at the very top of the most prolific and highly cited researchers. Finally, we employ social network analysis to explore the characteristics of scientific and technological networks generated by co-authorship and co-invention data, to investigate the position and the role of patenting-publishing scientists in these research networks.
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Denier, P; Le Beux, P; Delamarre, D; Fresnel, A; Cleret, M; Courtin, C; Seka, L P; Pouliquen, B; Cleran, L; Riou, C; Burgun, A; Jarno, P; Leduff, F; Lesaux, H; Duvauferrier, R
1997-08-01
Modern medicine requires a rapid access to information including clinical data from medical records, bibliographic databases, knowledge bases and nomenclature databases. This is especially true for University Hospitals and Medical Schools for training as well as for fundamental and clinical research for diagnosis and therapeutic purposes. This implies the development of local, national and international cooperation which can be enhanced via the use and access to computer networks such as Internet. The development of professional cooperative networks goes with the development of the telecommunication and computer networks and our project is to make these new tools and technologies accessible to the medical students both during the teaching time in Medical School and during the training periods at the University Hospital. We have developed a local area network which communicates between the School of Medicine and the Hospital which takes advantage of the new Web client-server technology both internally (Intranet) and externally by access to the National Research Network (RENATER in France) connected to the Internet network. The address of our public web server is http:(/)/www.med.univ-rennesl.fr.
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Telecommunication Networks. Tech Use Guide: Using Computer Technology.
ERIC Educational Resources Information Center
Council for Exceptional Children, Reston, VA. Center for Special Education Technology.
One of nine brief guides for special educators on using computer technology, this guide focuses on utilizing the telecommunications capabilities of computers. Network capabilities including electronic mail, bulletin boards, and access to distant databases are briefly explained. Networks useful to the educator, general commercial systems, and local…
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Iorio, Francesco; Shrestha, Roshan L.; Levin, Nicolas; Boilot, Viviane; Garnett, Mathew J.; Saez-Rodriguez, Julio; Draviam, Viji M.
2015-01-01
We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound). This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent) as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells–consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel. PMID:26452147
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Materials, processes, and environmental engineering network
NASA Technical Reports Server (NTRS)
White, Margo M.
1993-01-01
The Materials, Processes, and Environmental Engineering Network (MPEEN) was developed as a central holding facility for materials testing information generated by the Materials and Processes Laboratory. It contains information from other NASA centers and outside agencies, and also includes the NASA Environmental Information System (NEIS) and Failure Analysis Information System (FAIS) data. Environmental replacement materials information is a newly developed focus of MPEEN. This database is the NASA Environmental Information System, NEIS, which is accessible through MPEEN. Environmental concerns are addressed regarding materials identified by the NASA Operational Environment Team, NOET, to be hazardous to the environment. An environmental replacement technology database is contained within NEIS. Environmental concerns about materials are identified by NOET, and control or replacement strategies are formed. This database also contains the usage and performance characteristics of these hazardous materials. In addition to addressing environmental concerns, MPEEN contains one of the largest materials databases in the world. Over 600 users access this network on a daily basis. There is information available on failure analysis, metals and nonmetals testing, materials properties, standard and commercial parts, foreign alloy cross-reference, Long Duration Exposure Facility (LDEF) data, and Materials and Processes Selection List data.
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Hierarchical Data Distribution Scheme for Peer-to-Peer Networks
NASA Astrophysics Data System (ADS)
Bhushan, Shashi; Dave, M.; Patel, R. B.
2010-11-01
In the past few years, peer-to-peer (P2P) networks have become an extremely popular mechanism for large-scale content sharing. P2P systems have focused on specific application domains (e.g. music files, video files) or on providing file system like capabilities. P2P is a powerful paradigm, which provides a large-scale and cost-effective mechanism for data sharing. P2P system may be used for storing data globally. Can we implement a conventional database on P2P system? But successful implementation of conventional databases on the P2P systems is yet to be reported. In this paper we have presented the mathematical model for the replication of the partitions and presented a hierarchical based data distribution scheme for the P2P networks. We have also analyzed the resource utilization and throughput of the P2P system with respect to the availability, when a conventional database is implemented over the P2P system with variable query rate. Simulation results show that database partitions placed on the peers with higher availability factor perform better. Degradation index, throughput, resource utilization are the parameters evaluated with respect to the availability factor.
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QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm.
Bao, Ying; Lei, Weimin; Zhang, Wei; Zhan, Yuzhuo
2016-01-01
At present, to realize or improve the quality of experience (QoE) is a major goal for network media transmission service, and QoE evaluation is the basis for adjusting the transmission control mechanism. Therefore, a kind of QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm is proposed in this paper, which is concentrated on service score calculation at the server side. The server side collects network transmission quality of service (QoS) parameter, node location data, and user expectation value from client feedback information. Then it manages the historical data in database through the "big data" process mode, and predicts user score according to heuristic rules. On this basis, it completes fuzzy clustering analysis, and generates service QoE score and management message, which will be finally fed back to clients. Besides, this paper mainly discussed service evaluation generative rules, heuristic evaluation rules and fuzzy clustering analysis methods, and presents service-based QoE evaluation processes. The simulation experiments have verified the effectiveness of QoE collaborative evaluation method based on fuzzy clustering heuristic rules.
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On-line access to remote sensing data with the satellite-data information system (ISIS)
NASA Astrophysics Data System (ADS)
Strunz, G.; Lotz-Iwen, H.-J.
1994-08-01
The German Remote Sensing Data Center (DFD) is developing the satellite-data information system ISIS as central interface for users to access Earth observation data. ISIS has been designed to support international scientific research as well as operational applications by offering online database access via public networks, and is integrated in the international activities dedicated to catalogue and archive interoperability. A prototype of ISIS is already in use within the German Processing and Archiving Facility for ERS-1 for the storage and retrieval of digital SAR quicklook products and for the Radarmap of Germany. An operational status of the system is envisaged for the launch of ERS-2. The paper in hand describes the underlying concepts of ISIS and the recent state of realization. It explains the overall structure of the system and the functionality of each of its components. Emphasis is put on the description of the advisory system, the catalogue retrieval, and the online access and transfer of image data. Finally, the integration into a future global environmental data network is outlined.
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Comparison of eye imaging pattern recognition using neural network
NASA Astrophysics Data System (ADS)
Bukhari, W. M.; Syed A., M.; Nasir, M. N. M.; Sulaima, M. F.; Yahaya, M. S.
2015-05-01
The beauty of eye recognition system that it is used in automatic identifying and verifies a human weather from digital images or video source. There are various behaviors of the eye such as the color of the iris, size of pupil and shape of the eye. This study represents the analysis, design and implementation of a system for recognition of eye imaging. All the eye images that had been captured from the webcam in RGB format must through several techniques before it can be input for the pattern and recognition processes. The result shows that the final value of weight and bias after complete training 6 eye images for one subject is memorized by the neural network system and be the reference value of the weight and bias for the testing part. The target classifies to 5 different types for 5 subjects. The eye images can recognize the subject based on the target that had been set earlier during the training process. When the values between new eye image and the eye image in the database are almost equal, it is considered the eye image is matched.
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A High Speed Mobile Courier Data Access System That Processes Database Queries in Real-Time
NASA Astrophysics Data System (ADS)
Gatsheni, Barnabas Ndlovu; Mabizela, Zwelakhe
A secure high-speed query processing mobile courier data access (MCDA) system for a Courier Company has been developed. This system uses the wireless networks in combination with wired networks for updating a live database at the courier centre in real-time by an offsite worker (the Courier). The system is protected by VPN based on IPsec. There is no system that we know of to date that performs the task for the courier as proposed in this paper.
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Federal Register 2010, 2011, 2012, 2013, 2014
2010-08-16
...-BI51 Information Reporting for Payments Made in Settlement of Payment Card and Third Party Network..., and backup withholding requirements for payment card and third party network transactions. The final... third party network transactions for each calendar year. The final regulations in this document will...
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Seismic databases of The Caucasus
NASA Astrophysics Data System (ADS)
Gunia, I.; Sokhadze, G.; Mikava, D.; Tvaradze, N.; Godoladze, T.
2012-12-01
The Caucasus is one of the active segments of the Alpine-Himalayan collision belt. The region needs continues seismic monitoring systems for better understanding of tectonic processes going in the region. Seismic Monitoring Center of Georgia (Ilia State University) is operating the digital seismic network of the country and is also collecting and exchanging data with neighboring countries. The main focus of our study was to create seismic database which is well organized, easily reachable and is convenient for scientists to use. The seismological database includes the information about more than 100 000 earthquakes from the whole Caucasus. We have to mention that it includes data from analog and digital seismic networks. The first analog seismic station in Georgia was installed in 1899 in the Caucasus in Tbilisi city. The number of analog seismic stations was increasing during next decades and in 1980s about 100 analog stations were operated all over the region. From 1992 due to political and economical situation the number of stations has been decreased and in 2002 just two analog equipments was operated. New digital seismic network was developed in Georgia since 2003. The number of digital seismic stations was increasing and in current days there are more than 25 digital stations operating in the country. The database includes the detailed information about all equipments installed on seismic stations. Database is available online. That will make convenient interface for seismic data exchange data between Caucasus neighboring countries. It also makes easier both the seismic data processing and transferring them to the database and decreases the operator's mistakes during the routine work. The database was created using the followings: php, MySql, Javascript, Ajax, GMT, Gmap, Hypoinverse.
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Uhlirova, Hana; Tian, Peifang; Kılıç, Kıvılcım; Thunemann, Martin; Sridhar, Vishnu B; Chmelik, Radim; Bartsch, Hauke; Dale, Anders M; Devor, Anna; Saisan, Payam A
2018-05-04
The importance of sharing experimental data in neuroscience grows with the amount and complexity of data acquired and various techniques used to obtain and process these data. However, the majority of experimental data, especially from individual studies of regular-sized laboratories never reach wider research community. A graphical user interface (GUI) engine called Neurovascular Network Explorer 2.0 (NNE 2.0) has been created as a tool for simple and low-cost sharing and exploring of vascular imaging data. NNE 2.0 interacts with a database containing optogenetically-evoked dilation/constriction time-courses of individual vessels measured in mice somatosensory cortex in vivo by 2-photon microscopy. NNE 2.0 enables selection and display of the time-courses based on different criteria (subject, branching order, cortical depth, vessel diameter, arteriolar tree) as well as simple mathematical manipulation (e.g. averaging, peak-normalization) and data export. It supports visualization of the vascular network in 3D and enables localization of the individual functional vessel diameter measurements within vascular trees. NNE 2.0, its source code, and the corresponding database are freely downloadable from UCSD Neurovascular Imaging Laboratory website 1 . The source code can be utilized by the users to explore the associated database or as a template for databasing and sharing their own experimental results provided the appropriate format.
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Zhang, Shihua; Xuan, Hongdong; Zhang, Liang; Fu, Sicong; Wang, Yijun; Yang, Hua; Tai, Yuling; Song, Youhong; Zhang, Jinsong; Ho, Chi-Tang; Li, Shaowen; Wan, Xiaochun
2017-09-01
Tea is one of the most consumed beverages in the world. Considerable studies show the exceptional health benefits (e.g. antioxidation, cancer prevention) of tea owing to its various bioactive components. However, data from these extensively published papers had not been made available in a central database. To lay a foundation in improving the understanding of healthy tea functions, we established a TBC2health database that currently documents 1338 relationships between 497 tea bioactive compounds and 206 diseases (or phenotypes) manually culled from over 300 published articles. Each entry in TBC2health contains comprehensive information about a bioactive relationship that can be accessed in three aspects: (i) compound information, (ii) disease (or phenotype) information and (iii) evidence and reference. Using the curated bioactive relationships, a bipartite network was reconstructed and the corresponding network (or sub-network) visualization and topological analyses are provided for users. This database has a user-friendly interface for entry browse, search and download. In addition, TBC2health provides a submission page and several useful tools (e.g. BLAST, molecular docking) to facilitate use of the database. Consequently, TBC2health can serve as a valuable bioinformatics platform for the exploration of beneficial effects of tea on human health. TBC2health is freely available at http://camellia.ahau.edu.cn/TBC2health. © The Author 2016. Published by Oxford University Press.
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SSER: Species specific essential reactions database.
Labena, Abraham A; Ye, Yuan-Nong; Dong, Chuan; Zhang, Fa-Z; Guo, Feng-Biao
2017-04-19
Essential reactions are vital components of cellular networks. They are the foundations of synthetic biology and are potential candidate targets for antimetabolic drug design. Especially if a single reaction is catalyzed by multiple enzymes, then inhibiting the reaction would be a better option than targeting the enzymes or the corresponding enzyme-encoding gene. The existing databases such as BRENDA, BiGG, KEGG, Bio-models, Biosilico, and many others offer useful and comprehensive information on biochemical reactions. But none of these databases especially focus on essential reactions. Therefore, building a centralized repository for this class of reactions would be of great value. Here, we present a species-specific essential reactions database (SSER). The current version comprises essential biochemical and transport reactions of twenty-six organisms which are identified via flux balance analysis (FBA) combined with manual curation on experimentally validated metabolic network models. Quantitative data on the number of essential reactions, number of the essential reactions associated with their respective enzyme-encoding genes and shared essential reactions across organisms are the main contents of the database. SSER would be a prime source to obtain essential reactions data and related gene and metabolite information and it can significantly facilitate the metabolic network models reconstruction and analysis, and drug target discovery studies. Users can browse, search, compare and download the essential reactions of organisms of their interest through the website http://cefg.uestc.edu.cn/sser .
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Code of Federal Regulations, 2013 CFR
2013-10-01
... bands database, initiate and operate a network by sending enabling signals to one or more fixed TVBDs... specified in § 15.711(b)(1), i.e. 50 meters. This capability is used with a TV bands database approved by... to a TV bands database to obtain a list of available channels. A Mode I device must obtain a list of...
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Code of Federal Regulations, 2011 CFR
2011-10-01
... bands database, initiate and operate a network by sending enabling signals to one or more fixed TVBDs... specified in § 15.711(b)(1), i.e. 50 meters. This capability is used with a TV bands database approved by... to a TV bands database to obtain a list of available channels. A Mode I device must obtain a list of...
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Code of Federal Regulations, 2012 CFR
2012-10-01
... bands database, initiate and operate a network by sending enabling signals to one or more fixed TVBDs... specified in § 15.711(b)(1), i.e. 50 meters. This capability is used with a TV bands database approved by... to a TV bands database to obtain a list of available channels. A Mode I device must obtain a list of...
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ERIC Educational Resources Information Center
Barker, Philip
1986-01-01
Discussion of developments in information storage technology likely to have significant impact upon library utilization focuses on hardware (videodisc technology) and software developments (knowledge databases; computer networks; database management systems; interactive video, computer, and multimedia user interfaces). Three generic computer-based…
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Attribute and topology based change detection in a constellation of previously detected objects
Paglieroni, David W.; Beer, Reginald N.
2016-01-19
A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.
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Data Auditor: Analyzing Data Quality Using Pattern Tableaux
NASA Astrophysics Data System (ADS)
Srivastava, Divesh
Monitoring databases maintain configuration and measurement tables about computer systems, such as networks and computing clusters, and serve important business functions, such as troubleshooting customer problems, analyzing equipment failures, planning system upgrades, etc. These databases are prone to many data quality issues: configuration tables may be incorrect due to data entry errors, while measurement tables may be affected by incorrect, missing, duplicate and delayed polls. We describe Data Auditor, a tool for analyzing data quality and exploring data semantics of monitoring databases. Given a user-supplied constraint, such as a boolean predicate expected to be satisfied by every tuple, a functional dependency, or an inclusion dependency, Data Auditor computes "pattern tableaux", which are concise summaries of subsets of the data that satisfy or fail the constraint. We discuss the architecture of Data Auditor, including the supported types of constraints and the tableau generation mechanism. We also show the utility of our approach on an operational network monitoring database.
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Real-World Examples: Developing a Departmental Alumni Network
ERIC Educational Resources Information Center
Ashline, George
2017-01-01
We describe the context for and implementation of a departmental alumni network. More than a database compiling facts about graduates, this network provides students with information and inspiration. It also offers a wonderful opportunity to support lifelong learning through the development of collaborative relationships between alumni and faculty…
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2010-01-01
Background Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License. PMID:20587024
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Database Entity Persistence with Hibernate for the Network Connectivity Analysis Model
2014-04-01
time savings in the Java coding development process. Appendices A and B describe address setup procedures for installing the MySQL database...development environment is required: • The open source MySQL Database Management System (DBMS) from Oracle, which is a Java Database Connectivity (JDBC...compliant DBMS • MySQL JDBC Driver library that comes as a plug-in with the Netbeans distribution • The latest Java Development Kit with the latest
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Chen, Wei; Zhao, Wenshan; Yang, Aiting; Xu, Anjian; Wang, Huan; Cong, Min; Liu, Tianhui; Wang, Ping; You, Hong
2017-12-15
Liver fibrosis, characterized with the excessive accumulation of extracellular matrix (ECM) proteins, represents the final common pathway of chronic liver inflammation. Ever-increasing evidence indicates microRNAs (miRNAs) dysregulation has important implications in the different stages of liver fibrosis. However, our knowledge of miRNA-gene regulation details pertaining to such disease remains unclear. The publicly available Gene Expression Omnibus (GEO) datasets of patients suffered from cirrhosis were extracted for integrated analysis. Differentially expressed miRNAs (DEMs) and genes (DEGs) were identified using GEO2R web tool. Putative target gene prediction of DEMs was carried out using the intersection of five major algorithms: DIANA-microT, TargetScan, miRanda, PICTAR5 and miRWalk. Functional miRNA-gene regulatory network (FMGRN) was constructed based on the computational target predictions at the sequence level and the inverse expression relationships between DEMs and DEGs. DAVID web server was selected to perform KEGG pathway enrichment analysis. Functional miRNA-gene regulatory module was generated based on the biological interpretation. Internal connections among genes in liver fibrosis-related module were determined using String database. MiRNA-gene regulatory modules related to liver fibrosis were experimentally verified in recombinant human TGFβ1 stimulated and specific miRNA inhibitor treated LX-2 cells. We totally identified 85 and 923 dysregulated miRNAs and genes in liver cirrhosis biopsy samples compared to their normal controls. All evident miRNA-gene pairs were identified and assembled into FMGRN which consisted of 990 regulations between 51 miRNAs and 275 genes, forming two big sub-networks that were defined as down-network and up-network, respectively. KEGG pathway enrichment analysis revealed that up-network was prominently involved in several KEGG pathways, in which "Focal adhesion", "PI3K-Akt signaling pathway" and "ECM-receptor interaction" were remarked significant (adjusted p<0.001). Genes enriched in these pathways coupled with their regulatory miRNAs formed a functional miRNA-gene regulatory module that contains 7 miRNAs, 22 genes and 42 miRNA-gene connections. Gene interaction analysis based on String database revealed that 8 out of 22 genes were highly clustered. Finally, we experimentally confirmed a functional regulatory module containing 5 miRNAs (miR-130b-3p, miR-148a-3p, miR-345-5p, miR-378a-3p, and miR-422a) and 6 genes (COL6A1, COL6A2, COL6A3, PIK3R3, COL1A1, CCND2) associated with liver fibrosis. Our integrated analysis of miRNA and gene expression profiles highlighted a functional miRNA-gene regulatory module associated with liver fibrosis, which, to some extent, may provide important clues to better understand the underlying pathogenesis of liver fibrosis. Copyright © 2017. Published by Elsevier B.V.
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Archiving and Distributing Seismic Data at the Southern California Earthquake Data Center (SCEDC)
NASA Astrophysics Data System (ADS)
Appel, V. L.
2002-12-01
The Southern California Earthquake Data Center (SCEDC) archives and provides public access to earthquake parametric and waveform data gathered by the Southern California Seismic Network and since January 1, 2001, the TriNet seismic network, southern California's earthquake monitoring network. The parametric data in the archive includes earthquake locations, magnitudes, moment-tensor solutions and phase picks. The SCEDC waveform archive prior to TriNet consists primarily of short-period, 100-samples-per-second waveforms from the SCSN. The addition of the TriNet array added continuous recordings of 155 broadband stations (20 samples per second or less), and triggered seismograms from 200 accelerometers and 200 short-period instruments. Since the Data Center and TriNet use the same Oracle database system, new earthquake data are available to the seismological community in near real-time. Primary access to the database and waveforms is through the Seismogram Transfer Program (STP) interface. The interface enables users to search the database for earthquake information, phase picks, and continuous and triggered waveform data. Output is available in SAC, miniSEED, and other formats. Both the raw counts format (V0) and the gain-corrected format (V1) of COSMOS (Consortium of Organizations for Strong-Motion Observation Systems) are now supported by STP. EQQuest is an interface to prepackaged waveform data sets for select earthquakes in Southern California stored at the SCEDC. Waveform data for large-magnitude events have been prepared and new data sets will be available for download in near real-time following major events. The parametric data from 1981 to present has been loaded into the Oracle 9.2.0.1 database system and the waveforms for that time period have been converted to mSEED format and are accessible through the STP interface. The DISC optical-disk system (the "jukebox") that currently serves as the mass-storage for the SCEDC is in the process of being replaced with a series of inexpensive high-capacity (1.6 Tbyte) magnetic-disk RAIDs. These systems are built with PC-technology components, using 16 120-Gbyte IDE disks, hot-swappable disk trays, two RAID controllers, dual redundant power supplies and a Linux operating system. The system is configured over a private gigabit network that connects to the two Data Center servers and spans between the Seismological Lab and the USGS. To ensure data integrity, each RAID disk system constantly checks itself against its twin and verifies file integrity using 128-bit MD5 file checksums that are stored separate from the system. The final level of data protection is a Sony AIT-3 tape backup of the files. The primary advantage of the magnetic-disk approach is faster data access because magnetic disk drives have almost no latency. This means that the SCEDC can provide better "on-demand" interactive delivery of the seismograms in the archive.
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Networked gamma radiation detection system for tactical deployment
NASA Astrophysics Data System (ADS)
Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ronald; Smith, Ethan; Guss, Paul; Mitchell, Stephen
2015-08-01
A networked gamma radiation detection system with directional sensitivity and energy spectral data acquisition capability is being developed by the National Security Technologies, LLC, Remote Sensing Laboratory to support the close and intense tactical engagement of law enforcement who carry out counterterrorism missions. In the proposed design, three clusters of 2″ × 4″ × 16″ sodium iodide crystals (4 each) with digiBASE-E (for list mode data collection) would be placed on the passenger side of a minivan. To enhance localization and facilitate rapid identification of isotopes, advanced smart real-time localization and radioisotope identification algorithms like WAVRAD (wavelet-assisted variance reduction for anomaly detection) and NSCRAD (nuisance-rejection spectral comparison ratio anomaly detection) will be incorporated. We will test a collection of algorithms and analysis that centers on the problem of radiation detection with a distributed sensor network. We will study the basic characteristics of a radiation sensor network and focus on the trade-offs between false positive alarm rates, true positive alarm rates, and time to detect multiple radiation sources in a large area. Empirical and simulation analyses of critical system parameters, such as number of sensors, sensor placement, and sensor response functions, will be examined. This networked system will provide an integrated radiation detection architecture and framework with (i) a large nationally recognized search database equivalent that would help generate a common operational picture in a major radiological crisis; (ii) a robust reach back connectivity for search data to be evaluated by home teams; and, finally, (iii) a possibility of integrating search data from multi-agency responders.
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ERIC Educational Resources Information Center
Lynch, Clifford A.
1989-01-01
Reviews the history of the network that supports the MELVYL online union catalog, describes current technological and policy issues, and discusses the role the network plays in integrating local automation, the union catalog, access to resource databases, and other initiatives. Sidebars by Mark Needleman discuss the TCP/IP protocol suite, internet…
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Kinetic modeling of cell metabolism for microbial production.
Costa, Rafael S; Hartmann, Andras; Vinga, Susana
2016-02-10
Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations. Copyright © 2015 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Yang, Kun; Xu, Quan-li; Peng, Shuang-yun; Cao, Yan-bo
2008-10-01
Based on the necessity analysis of GIS applications in earthquake disaster prevention, this paper has deeply discussed the spatial integration scheme of urban earthquake disaster loss evaluation models and visualization technologies by using the network development methods such as COM/DCOM, ActiveX and ASP, as well as the spatial database development methods such as OO4O and ArcSDE based on ArcGIS software packages. Meanwhile, according to Software Engineering principles, a solution of Urban Earthquake Emergency Response Decision Support Systems based on GIS technologies have also been proposed, which include the systems logical structures, the technical routes,the system realization methods and function structures etc. Finally, the testing systems user interfaces have also been offered in the paper.
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Segmentation of Retinal Blood Vessels Based on Cake Filter
Bao, Xi-Rong; Ge, Xin; She, Li-Huang; Zhang, Shi
2015-01-01
Segmentation of retinal blood vessels is significant to diagnosis and evaluation of ocular diseases like glaucoma and systemic diseases such as diabetes and hypertension. The retinal blood vessel segmentation for small and low contrast vessels is still a challenging problem. To solve this problem, a new method based on cake filter is proposed. Firstly, a quadrature filter band called cake filter band is made up in Fourier field. Then the real component fusion is used to separate the blood vessel from the background. Finally, the blood vessel network is got by a self-adaption threshold. The experiments implemented on the STARE database indicate that the new method has a better performance than the traditional ones on the small vessels extraction, average accuracy rate, and true and false positive rate. PMID:26636095
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Expression and Organization of Geographic Spatial Relations Based on Topic Maps
NASA Astrophysics Data System (ADS)
Liang, H. J.; Wang, H.; Cui, T. J.; Guo, J. F.
2017-09-01
Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations.
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Lyme borreliosis: an update for Canadian dermatologists.
Potok, Olivia V; Brassard, Alain
2013-01-01
Lyme borreliosis is a multisystemic tick-borne spirochetosis, which may result in dermatologic, musculoskeletal, cardiovascular, and neurologic manifestations. Patients with suspected acute Lyme borreliosis infection may be referred for urgent dermatologic review. Canadian dermatologists should be aware of the latest information regarding the diagnosis and management of Lyme borreliosis. This review is based on a PubMed database search combining the word "Lyme" with variations of the word "Canada." Data sources included articles from the fields of ecology, epidemiology, laboratory diagnostics, and clinical management. In this review, the ecological basis of spirochete transmission by tick vectors is described. The latest available Canadian epidemiologic data are summarized. North American clinical manifestations of Lyme borreliosis are contrasted with European presentations. The Canadian Public Health Laboratory Network's diagnostic guidelines are summarized. Finally, treatment recommendations are outlined.
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Optimization-based method for automated road network extraction
DOT National Transportation Integrated Search
2001-09-18
Automated road information extraction has significant applicability in transportation. : It provides a means for creating, maintaining, and updating transportation network databases that : are needed for purposes ranging from traffic management to au...
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Bioinformatics analysis on molecular mechanism of rheum officinale in treatment of jaundice
NASA Astrophysics Data System (ADS)
Shan, Si; Tu, Jun; Nie, Peng; Yan, Xiaojun
2017-01-01
Objective: To study the molecular mechanism of Rheum officinale in the treatment of Jaundice by building molecular networks and comparing canonical pathways. Methods: Target proteins of Rheum officinale and related genes of Jaundice were searched from Pubchem and Gene databases online respectively. Molecular networks and canonical pathways comparison analyses were performed by Ingenuity Pathway Analysis (IPA). Results: The molecular networks of Rheum officinale and Jaundice were complex and multifunctional. The 40 target proteins of Rheum officinale and 33 Homo sapiens genes of Jaundice were found in databases. There were 19 common pathways both related networks. Rheum officinale could regulate endothelial differentiation, Interleukin-1B (IL-1B) and Tumor Necrosis Factor (TNF) in these pathways. Conclusions: Rheum officinale treat Jaundice by regulating many effective nodes of Apoptotic pathway and cellular immunity related pathways.
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Li, Wei; Cao, Peng; Zhao, Dazhe; Wang, Junbo
2016-01-01
Computer aided detection (CAD) systems can assist radiologists by offering a second opinion on early diagnosis of lung cancer. Classification and feature representation play critical roles in false-positive reduction (FPR) in lung nodule CAD. We design a deep convolutional neural networks method for nodule classification, which has an advantage of autolearning representation and strong generalization ability. A specified network structure for nodule images is proposed to solve the recognition of three types of nodules, that is, solid, semisolid, and ground glass opacity (GGO). Deep convolutional neural networks are trained by 62,492 regions-of-interest (ROIs) samples including 40,772 nodules and 21,720 nonnodules from the Lung Image Database Consortium (LIDC) database. Experimental results demonstrate the effectiveness of the proposed method in terms of sensitivity and overall accuracy and that it consistently outperforms the competing methods.
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You, Seng Chan; Lee, Seongwon; Cho, Soo-Yeon; Park, Hojun; Jung, Sungjae; Cho, Jaehyeong; Yoon, Dukyong; Park, Rae Woong
2017-01-01
It is increasingly necessary to generate medical evidence applicable to Asian people compared to those in Western countries. Observational Health Data Sciences a Informatics (OHDSI) is an international collaborative which aims to facilitate generating high-quality evidence via creating and applying open-source data analytic solutions to a large network of health databases across countries. We aimed to incorporate Korean nationwide cohort data into the OHDSI network by converting the national sample cohort into Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM). The data of 1.13 million subjects was converted to OMOP-CDM, resulting in average 99.1% conversion rate. The ACHILLES, open-source OMOP-CDM-based data profiling tool, was conducted on the converted database to visualize data-driven characterization and access the quality of data. The OMOP-CDM version of National Health Insurance Service-National Sample Cohort (NHIS-NSC) can be a valuable tool for multiple aspects of medical research by incorporation into the OHDSI research network.
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NASA Astrophysics Data System (ADS)
Gay, D. A.; Schmeltz, D.; Prestbo, E.; Olson, M.; Sharac, T.; Tordon, R.
2013-04-01
The National Atmospheric Deposition Program (NADP) developed and operates a collaborative network of atmospheric mercury monitoring sites based in North America - the Atmospheric Mercury Network (AMNet). The justification for the network was growing interest and demand from many scientists and policy makers for a robust database of measurements to improve model development, assess policies and programs, and improve estimates of mercury dry deposition. Many different agencies and groups support the network, including federal, state, tribal, and international governments, academic institutions, and private companies. AMNet has added two high elevation sites outside of continental North America in Hawaii and Taiwan because of new partnerships forged within NADP. Network sites measure concentrations of atmospheric mercury fractions using automated, continuous mercury speciation systems. The procedures that NADP developed for field operations, data management, and quality assurance ensure that the network makes scientifically valid and consistent measurements. AMNet reports concentrations of hourly gaseous elemental mercury (GEM), two-hour gaseous oxidized mercury (GOM), and two-hour particulate-bound mercury less than 2.5 microns in size (PBM2.5). As of January 2012, over 450 000 valid observations are available from 30 stations. The AMNet also collects ancillary meteorological data and information on land-use and vegetation, when available. We present atmospheric mercury data comparisons by time (3 yr) at 22 unique site locations. Highlighted are contrasting values for site locations across the network: urban versus rural, coastal versus high-elevation and the range of maximum observations. The data presented should catalyze the formation of many scientific questions that may be answered through further in-depth analysis and modeling studies of the AMNet database. All data and methods are publically available through an online database on the NADP website (http://nadp.isws.illinois.edu/amn/). Future network directions are to foster new network partnerships and continue to collect, quality assure, and post data, including dry deposition estimates, for each fraction.
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NASA Astrophysics Data System (ADS)
Gay, D. A.; Schmeltz, D.; Prestbo, E.; Olson, M.; Sharac, T.; Tordon, R.
2013-11-01
The National Atmospheric Deposition Program (NADP) developed and operates a collaborative network of atmospheric-mercury-monitoring sites based in North America - the Atmospheric Mercury Network (AMNet). The justification for the network was growing interest and demand from many scientists and policy makers for a robust database of measurements to improve model development, assess policies and programs, and improve estimates of mercury dry deposition. Many different agencies and groups support the network, including federal, state, tribal, and international governments, academic institutions, and private companies. AMNet has added two high-elevation sites outside of continental North America in Hawaii and Taiwan because of new partnerships forged within NADP. Network sites measure concentrations of atmospheric mercury fractions using automated, continuous mercury speciation systems. The procedures that NADP developed for field operations, data management, and quality assurance ensure that the network makes scientifically valid and consistent measurements. AMNet reports concentrations of hourly gaseous elemental mercury (GEM), two-hour gaseous oxidized mercury (GOM), and two-hour particulate-bound mercury less than 2.5 microns in size (PBM2.5). As of January 2012, over 450 000 valid observations are available from 30 stations. AMNet also collects ancillary meteorological data and information on land use and vegetation, when available. We present atmospheric mercury data comparisons by time (3 yr) at 21 individual sites and instruments. Highlighted are contrasting values for site locations across the network: urban versus rural, coastal versus high elevation and the range of maximum observations. The data presented should catalyze the formation of many scientific questions that may be answered through further in-depth analysis and modeling studies of the AMNet database. All data and methods are publically available through an online database on the NADP website (http://nadp.sws.uiuc.edu/amn/). Future network directions are to foster new network partnerships and continue to collect, quality assure, and post data, including dry deposition estimates, for each fraction.
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Final Report - Cloud-Based Management Platform for Distributed, Multi-Domain Networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chowdhury, Pulak; Mukherjee, Biswanath
2017-11-03
In this Department of Energy (DOE) Small Business Innovation Research (SBIR) Phase II project final report, Ennetix presents the development of a solution for end-to-end monitoring, analysis, and visualization of network performance for distributed networks. This solution benefits enterprises of all sizes, operators of distributed and federated networks, and service providers.
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Technology and the Modern Library.
ERIC Educational Resources Information Center
Boss, Richard W.
1984-01-01
Overview of the impact of information technology on libraries highlights turnkey vendors, bibliographic utilities, commercial suppliers of records, state and regional networks, computer-to-computer linkages, remote database searching, terminals and microcomputers, building local databases, delivery of information, digital telefacsimile,…
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Quality Analysis of Open Street Map Data
NASA Astrophysics Data System (ADS)
Wang, M.; Li, Q.; Hu, Q.; Zhou, M.
2013-05-01
Crowd sourcing geographic data is an opensource geographic data which is contributed by lots of non-professionals and provided to the public. The typical crowd sourcing geographic data contains GPS track data like OpenStreetMap, collaborative map data like Wikimapia, social websites like Twitter and Facebook, POI signed by Jiepang user and so on. These data will provide canonical geographic information for pubic after treatment. As compared with conventional geographic data collection and update method, the crowd sourcing geographic data from the non-professional has characteristics or advantages of large data volume, high currency, abundance information and low cost and becomes a research hotspot of international geographic information science in the recent years. Large volume crowd sourcing geographic data with high currency provides a new solution for geospatial database updating while it need to solve the quality problem of crowd sourcing geographic data obtained from the non-professionals. In this paper, a quality analysis model for OpenStreetMap crowd sourcing geographic data is proposed. Firstly, a quality analysis framework is designed based on data characteristic analysis of OSM data. Secondly, a quality assessment model for OSM data by three different quality elements: completeness, thematic accuracy and positional accuracy is presented. Finally, take the OSM data of Wuhan for instance, the paper analyses and assesses the quality of OSM data with 2011 version of navigation map for reference. The result shows that the high-level roads and urban traffic network of OSM data has a high positional accuracy and completeness so that these OSM data can be used for updating of urban road network database.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Kristofferson, D.; Mack, D.
1996-10-01
This is the final report for a DOE funded project on BIOSCI Electronic Newsgroup Network for the biological sciences. A usable network for scientific discussion, major announcements, problem solving, etc. has been created.
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Report on Legal Protection for Databases. A Report of the Register of Copyrights. August, 1997.
ERIC Educational Resources Information Center
Library of Congress, Washington, DC. Copyright Office.
This report gives an overview of the past and present domestic and international legal framework for database protection. It describes database industry practices in securing protection against unauthorized use and Copyright Office registration practices relating to databases. Finally, it discusses issues raised and concerns expressed in a series…
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ERIC Educational Resources Information Center
Griffiths, Jose-Marie; And Others
This document contains validated activities and competencies needed by librarians working in a database distributor/service organization. The activities of professionals working in database distributor/service organizations are listed by function: Database Processing; Customer Support; System Administration; and Planning. The competencies are…
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Data, knowledge and method bases in chemical sciences. Part IV. Current status in databases.
Braibanti, Antonio; Rao, Rupenaguntla Sambasiva; Rao, Gollapalli Nagesvara; Ramam, Veluri Anantha; Rao, Sattiraju Veera Venkata Satyanarayana
2002-01-01
Computer readable databases have become an integral part of chemical research right from planning data acquisition to interpretation of the information generated. The databases available today are numerical, spectral and bibliographic. Data representation by different schemes--relational, hierarchical and objects--is demonstrated. Quality index (QI) throws light on the quality of data. The objective, prospects and impact of database activity on expert systems are discussed. The number and size of corporate databases available on international networks crossed manageable number leading to databases about their contents. Subsets of corporate or small databases have been developed by groups of chemists. The features and role of knowledge-based or intelligent databases are described.
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Chan, Derek K P; Tsui, Henry C L; Kot, Brian C W
2017-11-21
Databases are systematic tools to archive and manage information related to marine mammal stranding and mortality events. Stranding response networks, governmental authorities and non-governmental organizations have established regional or national stranding networks and have developed unique standard stranding response and necropsy protocols to document and track stranded marine mammal demographics, signalment and health data. The objectives of this study were to (1) describe and review the current status of marine mammal stranding and mortality databases worldwide, including the year established, types of database and their goals; and (2) summarize the geographic range included in the database, the number of cases recorded, accessibility, filter and display methods. Peer-reviewed literature was searched, focussing on published databases of live and dead marine mammal strandings and mortality and information released from stranding response organizations (i.e. online updates, journal articles and annual stranding reports). Databases that were not published in the primary literature or recognized by government agencies were excluded. Based on these criteria, 10 marine mammal stranding and mortality databases were identified, and strandings and necropsy data found in these databases were evaluated. We discuss the results, limitations and future prospects of database development. Future prospects include the development and application of virtopsy, a new necropsy investigation tool. A centralized web-accessed database of all available postmortem multimedia from stranded marine mammals may eventually support marine conservation and policy decisions, which will allow the use of marine animals as sentinels of ecosystem health, working towards a 'One Ocean-One Health' ideal.
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NONATObase: a database for Polychaeta (Annelida) from the Southwestern Atlantic Ocean.
Pagliosa, Paulo R; Doria, João G; Misturini, Dairana; Otegui, Mariana B P; Oortman, Mariana S; Weis, Wilson A; Faroni-Perez, Larisse; Alves, Alexandre P; Camargo, Maurício G; Amaral, A Cecília Z; Marques, Antonio C; Lana, Paulo C
2014-01-01
Networks can greatly advance data sharing attitudes by providing organized and useful data sets on marine biodiversity in a friendly and shared scientific environment. NONATObase, the interactive database on polychaetes presented herein, will provide new macroecological and taxonomic insights of the Southwestern Atlantic region. The database was developed by the NONATO network, a team of South American researchers, who integrated available information on polychaetes from between 5°N and 80°S in the Atlantic Ocean and near the Antarctic. The guiding principle of the database is to keep free and open access to data based on partnerships. Its architecture consists of a relational database integrated in the MySQL and PHP framework. Its web application allows access to the data from three different directions: species (qualitative data), abundance (quantitative data) and data set (reference data). The database has built-in functionality, such as the filter of data on user-defined taxonomic levels, characteristics of site, sample, sampler, and mesh size used. Considering that there are still many taxonomic issues related to poorly known regional fauna, a scientific committee was created to work out consistent solutions to current misidentifications and equivocal taxonomy status of some species. Expertise from this committee will be incorporated by NONATObase continually. The use of quantitative data was possible by standardization of a sample unit. All data, maps of distribution and references from a data set or a specified query can be visualized and exported to a commonly used data format in statistical analysis or reference manager software. The NONATO network has initialized with NONATObase, a valuable resource for marine ecologists and taxonomists. The database is expected to grow in functionality as it comes in useful, particularly regarding the challenges of dealing with molecular genetic data and tools to assess the effects of global environment change. Database URL: http://nonatobase.ufsc.br/.
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NONATObase: a database for Polychaeta (Annelida) from the Southwestern Atlantic Ocean
Pagliosa, Paulo R.; Doria, João G.; Misturini, Dairana; Otegui, Mariana B. P.; Oortman, Mariana S.; Weis, Wilson A.; Faroni-Perez, Larisse; Alves, Alexandre P.; Camargo, Maurício G.; Amaral, A. Cecília Z.; Marques, Antonio C.; Lana, Paulo C.
2014-01-01
Networks can greatly advance data sharing attitudes by providing organized and useful data sets on marine biodiversity in a friendly and shared scientific environment. NONATObase, the interactive database on polychaetes presented herein, will provide new macroecological and taxonomic insights of the Southwestern Atlantic region. The database was developed by the NONATO network, a team of South American researchers, who integrated available information on polychaetes from between 5°N and 80°S in the Atlantic Ocean and near the Antarctic. The guiding principle of the database is to keep free and open access to data based on partnerships. Its architecture consists of a relational database integrated in the MySQL and PHP framework. Its web application allows access to the data from three different directions: species (qualitative data), abundance (quantitative data) and data set (reference data). The database has built-in functionality, such as the filter of data on user-defined taxonomic levels, characteristics of site, sample, sampler, and mesh size used. Considering that there are still many taxonomic issues related to poorly known regional fauna, a scientific committee was created to work out consistent solutions to current misidentifications and equivocal taxonomy status of some species. Expertise from this committee will be incorporated by NONATObase continually. The use of quantitative data was possible by standardization of a sample unit. All data, maps of distribution and references from a data set or a specified query can be visualized and exported to a commonly used data format in statistical analysis or reference manager software. The NONATO network has initialized with NONATObase, a valuable resource for marine ecologists and taxonomists. The database is expected to grow in functionality as it comes in useful, particularly regarding the challenges of dealing with molecular genetic data and tools to assess the effects of global environment change. Database URL: http://nonatobase.ufsc.br/ PMID:24573879
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15 CFR Supplement No. 8 to Part 742 - Self-Classification Report for Encryption Items
Code of Federal Regulations, 2011 CFR
2011-01-01
... forensics (v) Cryptographic accelerator (vi) Data backup and recovery (vii) Database (viii) Disk/drive... (MAN) (xxii) Modem (xxiii) Network convergence or infrastructure n.e.s. (xxiv) Network forensics (xxv...
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15 CFR Supplement No. 8 to Part 742 - Self-Classification Report for Encryption Items
Code of Federal Regulations, 2014 CFR
2014-01-01
... forensics (v) Cryptographic accelerator (vi) Data backup and recovery (vii) Database (viii) Disk/drive... (MAN) (xxii) Modem (xxiii) Network convergence or infrastructure n.e.s. (xxiv) Network forensics (xxv...
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15 CFR Supplement No. 8 to Part 742 - Self-Classification Report for Encryption Items
Code of Federal Regulations, 2013 CFR
2013-01-01
... forensics (v) Cryptographic accelerator (vi) Data backup and recovery (vii) Database (viii) Disk/drive... (MAN) (xxii) Modem (xxiii) Network convergence or infrastructure n.e.s. (xxiv) Network forensics (xxv...
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15 CFR Supplement No. 8 to Part 742 - Self-Classification Report for Encryption Items
Code of Federal Regulations, 2012 CFR
2012-01-01
... forensics (v) Cryptographic accelerator (vi) Data backup and recovery (vii) Database (viii) Disk/drive... (MAN) (xxii) Modem (xxiii) Network convergence or infrastructure n.e.s. (xxiv) Network forensics (xxv...
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Tamminga, Carol A; Pearlson, Godfrey D; Stan, Ana D; Gibbons, Robert D; Padmanabhan, Jaya; Keshavan, Matcheri; Clementz, Brett A
2017-01-01
It is critical for psychiatry as a field to develop approaches to define the molecular, cellular, and circuit basis of its brain diseases, especially for serious mental illnesses, and then to use these definitions to generate biologically based disease categories, as well as to explore disease mechanisms and illness etiologies. Our current reliance on phenomenology is inadequate to support exploration of molecular treatment targets and disease formulations, and the leap directly from phenomenology to disease biology has been limiting because of broad heterogeneity within conventional diagnoses. The questions addressed in this review are formulated around how we can use brain biomarkers to achieve disease categories that are biologically based. We have grouped together a series of vignettes as examples of early approaches, all using the Bipolar and Schizophrenia Network on Intermediate Phenotypes (BSNIP) biomarker database and collaborators, starting off with describing the foundational statistical methods for these goals. We use primarily criterion-free statistics to identify pertinent groups of involved genes related to psychosis as well as symptoms, and finally, to create new biologically based disease cohorts within the psychopathological dimension of psychosis. Although we do not put these results forward as final formulations, they represent a novel effort to rely minimally on phenomenology as a diagnostic tool and to fully embrace brain characteristics of structure, as well as molecular and cellular characteristics and function, to support disease definition in psychosis. Copyright © 2016. Published by Elsevier Inc.
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MIPS: analysis and annotation of proteins from whole genomes in 2005
Mewes, H. W.; Frishman, D.; Mayer, K. F. X.; Münsterkötter, M.; Noubibou, O.; Pagel, P.; Rattei, T.; Oesterheld, M.; Ruepp, A.; Stümpflen, V.
2006-01-01
The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein–protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (). PMID:16381839
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MIPS: analysis and annotation of proteins from whole genomes in 2005.
Mewes, H W; Frishman, D; Mayer, K F X; Münsterkötter, M; Noubibou, O; Pagel, P; Rattei, T; Oesterheld, M; Ruepp, A; Stümpflen, V
2006-01-01
The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein-protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.gsf.de).
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Gonzalez, J; Marchand-Geneste, N; Giraudel, J L; Shimada, T
2012-01-01
To obtain chemical clues on the process of bioactivation by cytochromes P450 1A1 and 1B1, some QSAR studies were carried out based on cellular experiments of the metabolic activation of polycyclic aromatic hydrocarbons and heterocyclic aromatic compounds by those enzymes. Firstly, the 3D structures of cytochromes 1A1 and 1B1 were built using homology modelling with a cytochrome 1A2 template. Using these structures, 32 ligands including heterocyclic aromatic compounds, polycyclic aromatic hydrocarbons and corresponding diols, were docked with LigandFit and CDOCKER algorithms. Binding mode analysis highlighted the importance of hydrophobic interactions and the hydrogen bonding network between cytochrome amino acids and docked molecules. Finally, for each enzyme, multilinear regression and artificial neural network QSAR models were developed and compared. These statistical models highlighted the importance of electronic, structural and energetic descriptors in metabolic activation process, and could be used for virtual screening of ligand databases. In the case of P450 1A1, the best model was obtained with artificial neural network analysis and gave an r (2) of 0.66 and an external prediction [Formula: see text] of 0.73. Concerning P450 1B1, artificial neural network analysis gave a much more robust model, associated with an r (2) value of 0.73 and an external prediction [Formula: see text] of 0.59.
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Gao, Li; Zhang, Li-Jie; Li, Sheng-Hua; Wei, Li-Li; Luo, Bin; He, Rong-Quan; Xia, Shuang
2018-03-06
MiR-452-5p has been reported to be down-regulated in prostate cancer, affecting the development of this type of cancer. However, the molecular mechanism of miR-452-5p in prostate cancer remains unclear. Therefore, we investigated the network of target genes of miR-452-5p in prostate cancer using bioinformatics analyses. We first analyzed the expression profiles and prognostic value of miR-452-5p in prostate cancer tissues from a public database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), PANTHER pathway analyses, and a disease ontology (DG) analysis were performed to find the molecular functions of the target genes from GSE datasets and miRWalk. Finally, we validated hub genes from the protein-protein interaction (PPI) networks of the target genes in the Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA). Narrowing down the optimal target genes was conducted by seeking the common parts of up-regulated genes from GEPIA, down-regulated genes from GSE datasets, and predicted genes in miRWalk. Based on mining of GEO and ArrayExpress microarray chips and miRNA-Seq data in the TCGA database, which includes 1007 prostate cancer samples and 387 non-cancer samples, miR-452-5p is shown to be down-regulated in prostate cancer. GO, KEGG, and PANTHER pathway analyses suggested that the target genes might participate in important biological processes, such as transforming growth factor beta signaling and the positive regulation of brown fat cell differentiation and mesenchymal cell differentiation, as well as the Ras signaling pathway and pathways regulating the pluripotency of stem cells and arrhythmogenic right ventricular cardiomyopathy (ARVC). Nine genes-GABBR, PNISR, NTSR1, DOCK1, EREG, SFRP1, PTGS2, LEF1, and BMP2-were defined as hub genes in the PPI network. Three genes-FAM174B, SLC30A4, and SLIT1-were jointly shared by GEPIA, the GSE datasets, and miRWalk. Down-regulated miR-452-5p might play an essential role in the tumorigenesis of prostate cancer. Copyright © 2018. Published by Elsevier GmbH.
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ERIC Educational Resources Information Center
CEDEFOP Flash, 1993
1993-01-01
During 1992, CEDEFOP (the European Centre for the Development of Vocational Training) commissioned two projects to investigate the current situation with regard to databases on vocational qualifications in Member States of the European Community (EC) and possibilities for networking such databases. Results of these two studies were presented and…
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Kawano, Shin; Watanabe, Tsutomu; Mizuguchi, Sohei; Araki, Norie; Katayama, Toshiaki; Yamaguchi, Atsuko
2014-07-01
TogoTable (http://togotable.dbcls.jp/) is a web tool that adds user-specified annotations to a table that a user uploads. Annotations are drawn from several biological databases that use the Resource Description Framework (RDF) data model. TogoTable uses database identifiers (IDs) in the table as a query key for searching. RDF data, which form a network called Linked Open Data (LOD), can be searched from SPARQL endpoints using a SPARQL query language. Because TogoTable uses RDF, it can integrate annotations from not only the reference database to which the IDs originally belong, but also externally linked databases via the LOD network. For example, annotations in the Protein Data Bank can be retrieved using GeneID through links provided by the UniProt RDF. Because RDF has been standardized by the World Wide Web Consortium, any database with annotations based on the RDF data model can be easily incorporated into this tool. We believe that TogoTable is a valuable Web tool, particularly for experimental biologists who need to process huge amounts of data such as high-throughput experimental output. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
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A generic method for improving the spatial interoperability of medical and ecological databases.
Ghenassia, A; Beuscart, J B; Ficheur, G; Occelli, F; Babykina, E; Chazard, E; Genin, M
2017-10-03
The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution. Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index. We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas. Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.
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Multi-Resolution Playback of Network Trace Files
2015-06-01
a com- plete MySQL database, C++ developer tools and the libraries utilized in the development of the system (Boost and Libcrafter), and Wireshark...XE suite has a limit to the allowed size of each database. In order to be scalable, the project had to switch to the MySQL database suite. The...programs that access the database use the MySQL C++ connector, provided by Oracle, and the supplied methods and libraries. 4.4 Flow Generator Chapter 3
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Wang, L.; Infante, D.; Esselman, P.; Cooper, A.; Wu, D.; Taylor, W.; Beard, D.; Whelan, G.; Ostroff, A.
2011-01-01
Fisheries management programs, such as the National Fish Habitat Action Plan (NFHAP), urgently need a nationwide spatial framework and database for health assessment and policy development to protect and improve riverine systems. To meet this need, we developed a spatial framework and database using National Hydrography Dataset Plus (I-.100,000-scale); http://www.horizon-systems.com/nhdplus). This framework uses interconfluence river reaches and their local and network catchments as fundamental spatial river units and a series of ecological and political spatial descriptors as hierarchy structures to allow users to extract or analyze information at spatial scales that they define. This database consists of variables describing channel characteristics, network position/connectivity, climate, elevation, gradient, and size. It contains a series of catchment-natural and human-induced factors that are known to influence river characteristics. Our framework and database assembles all river reaches and their descriptors in one place for the first time for the conterminous United States. This framework and database provides users with the capability of adding data, conducting analyses, developing management scenarios and regulation, and tracking management progresses at a variety of spatial scales. This database provides the essential data needs for achieving the objectives of NFHAP and other management programs. The downloadable beta version database is available at http://ec2-184-73-40-15.compute-1.amazonaws.com/nfhap/main/.
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Interactogeneous: Disease Gene Prioritization Using Heterogeneous Networks and Full Topology Scores
Gonçalves, Joana P.; Francisco, Alexandre P.; Moreau, Yves; Madeira, Sara C.
2012-01-01
Disease gene prioritization aims to suggest potential implications of genes in disease susceptibility. Often accomplished in a guilt-by-association scheme, promising candidates are sorted according to their relatedness to known disease genes. Network-based methods have been successfully exploiting this concept by capturing the interaction of genes or proteins into a score. Nonetheless, most current approaches yield at least some of the following limitations: (1) networks comprise only curated physical interactions leading to poor genome coverage and density, and bias toward a particular source; (2) scores focus on adjacencies (direct links) or the most direct paths (shortest paths) within a constrained neighborhood around the disease genes, ignoring potentially informative indirect paths; (3) global clustering is widely applied to partition the network in an unsupervised manner, attributing little importance to prior knowledge; (4) confidence weights and their contribution to edge differentiation and ranking reliability are often disregarded. We hypothesize that network-based prioritization related to local clustering on graphs and considering full topology of weighted gene association networks integrating heterogeneous sources should overcome the above challenges. We term such a strategy Interactogeneous. We conducted cross-validation tests to assess the impact of network sources, alternative path inclusion and confidence weights on the prioritization of putative genes for 29 diseases. Heat diffusion ranking proved the best prioritization method overall, increasing the gap to neighborhood and shortest paths scores mostly on single source networks. Heterogeneous associations consistently delivered superior performance over single source data across the majority of methods. Results on the contribution of confidence weights were inconclusive. Finally, the best Interactogeneous strategy, heat diffusion ranking and associations from the STRING database, was used to prioritize genes for Parkinson’s disease. This method effectively recovered known genes and uncovered interesting candidates which could be linked to pathogenic mechanisms of the disease. PMID:23185389
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Experiments and Analysis on a Computer Interface to an Information-Retrieval Network.
ERIC Educational Resources Information Center
Marcus, Richard S.; Reintjes, J. Francis
A primary goal of this project was to develop an interface that would provide direct access for inexperienced users to existing online bibliographic information retrieval networks. The experiment tested the concept of a virtual-system mode of access to a network of heterogeneous interactive retrieval systems and databases. An experimental…
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The Deep Impact Network Experiment Operations Center Monitor and Control System
NASA Technical Reports Server (NTRS)
Wang, Shin-Ywan (Cindy); Torgerson, J. Leigh; Schoolcraft, Joshua; Brenman, Yan
2009-01-01
The Interplanetary Overlay Network (ION) software at JPL is an implementation of Delay/Disruption Tolerant Networking (DTN) which has been proposed as an interplanetary protocol to support space communication. The JPL Deep Impact Network (DINET) is a technology development experiment intended to increase the technical readiness of the JPL implemented ION suite. The DINET Experiment Operations Center (EOC) developed by JPL's Protocol Technology Lab (PTL) was critical in accomplishing the experiment. EOC, containing all end nodes of simulated spaces and one administrative node, exercised publish and subscribe functions for payload data among all end nodes to verify the effectiveness of data exchange over ION protocol stacks. A Monitor and Control System was created and installed on the administrative node as a multi-tiered internet-based Web application to support the Deep Impact Network Experiment by allowing monitoring and analysis of the data delivery and statistics from ION. This Monitor and Control System includes the capability of receiving protocol status messages, classifying and storing status messages into a database from the ION simulation network, and providing web interfaces for viewing the live results in addition to interactive database queries.
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A neural network approach to cloud classification
NASA Technical Reports Server (NTRS)
Lee, Jonathan; Weger, Ronald C.; Sengupta, Sailes K.; Welch, Ronald M.
1990-01-01
It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Sikora, R.; Chady, T.; Baniukiewicz, P.
2010-02-22
Nondestructive testing and evaluation are under continuous development. Currently researches are concentrated on three main topics: advancement of existing methods, introduction of novel methods and development of artificial intelligent systems for automatic defect recognition (ADR). Automatic defect classification algorithm comprises of two main tasks: creating a defect database and preparing a defect classifier. Here, the database was built using defect features that describe all geometrical and texture properties of the defect. Almost twenty carefully selected features calculated for flaws extracted from real radiograms were used. The radiograms were obtained from shipbuilding industry and they were verified by qualified operator. Twomore » weld defect's classifiers based on artificial neural networks were proposed and compared. First model consisted of one neural network model, where each output neuron corresponded to different defect group. The second model contained five neural networks. Each neural network had one neuron on output and was responsible for detection of defects from one group. In order to evaluate the effectiveness of the neural networks classifiers, the mean square errors were calculated for test radiograms and compared.« less
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NASA Astrophysics Data System (ADS)
Sikora, R.; Chady, T.; Baniukiewicz, P.; Caryk, M.; Piekarczyk, B.
2010-02-01
Nondestructive testing and evaluation are under continuous development. Currently researches are concentrated on three main topics: advancement of existing methods, introduction of novel methods and development of artificial intelligent systems for automatic defect recognition (ADR). Automatic defect classification algorithm comprises of two main tasks: creating a defect database and preparing a defect classifier. Here, the database was built using defect features that describe all geometrical and texture properties of the defect. Almost twenty carefully selected features calculated for flaws extracted from real radiograms were used. The radiograms were obtained from shipbuilding industry and they were verified by qualified operator. Two weld defect's classifiers based on artificial neural networks were proposed and compared. First model consisted of one neural network model, where each output neuron corresponded to different defect group. The second model contained five neural networks. Each neural network had one neuron on output and was responsible for detection of defects from one group. In order to evaluate the effectiveness of the neural networks classifiers, the mean square errors were calculated for test radiograms and compared.
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National information network and database system of hazardous waste management in China
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ma Hongchang
1996-12-31
Industries in China generate large volumes of hazardous waste, which makes it essential for the nation to pay more attention to hazardous waste management. National laws and regulations, waste surveys, and manifest tracking and permission systems have been initiated. Some centralized hazardous waste disposal facilities are under construction. China`s National Environmental Protection Agency (NEPA) has also obtained valuable information on hazardous waste management from developed countries. To effectively share this information with local environmental protection bureaus, NEPA developed a national information network and database system for hazardous waste management. This information network will have such functions as information collection, inquiry,more » and connection. The long-term objective is to establish and develop a national and local hazardous waste management information network. This network will significantly help decision makers and researchers because it will be easy to obtain information (e.g., experiences of developed countries in hazardous waste management) to enhance hazardous waste management in China. The information network consists of five parts: technology consulting, import-export management, regulation inquiry, waste survey, and literature inquiry.« less
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Beyond the online catalog: developing an academic information system in the sciences.
Crawford, S; Halbrook, B; Kelly, E; Stucki, L
1987-01-01
The online public access catalog consists essentially of a machine-readable database with network capabilities. Like other computer-based information systems, it may be continuously enhanced by the addition of new capabilities and databases. It may also become a gateway to other information networks. This paper reports the evolution of the Bibliographic Access and Control System (BACS) of Washington University in end-user searching, current awareness services, information management, and administrative functions. Ongoing research and development and the future of the online catalog are also discussed. PMID:3315052
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Beyond the online catalog: developing an academic information system in the sciences.
Crawford, S; Halbrook, B; Kelly, E; Stucki, L
1987-07-01
The online public access catalog consists essentially of a machine-readable database with network capabilities. Like other computer-based information systems, it may be continuously enhanced by the addition of new capabilities and databases. It may also become a gateway to other information networks. This paper reports the evolution of the Bibliographic Access and Control System (BACS) of Washington University in end-user searching, current awareness services, information management, and administrative functions. Ongoing research and development and the future of the online catalog are also discussed.
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IRIS++ database: Merging of IRIS + Mark-1 + LOWL
NASA Astrophysics Data System (ADS)
Salabert, D.; Fossat, E.; Gelly, B.; Tomczyk, S.; Pallé, P.; Jiménez-Reyes, S. J.; Cacciani, A.; Corbard, T.; Ehgamberdiev, S.; Grec, G.; Hoeksema, J. T.; Kholikov, S.; Lazrek, M.; Schmider, F. X.
2002-08-01
The IRIS network has been operated continuously since July 1st 1989. To date, it has acquired more than a complete solar cycle of full-disk helioseismic data which has been used to constrain the structure and rotation of the deep solar interior. However, the duty cycle of the network data has never reached initial expectations. To improve this situation, several cooperations have been developed with teams collecting observations with similar instruments. This paper demonstrates that we are able to merge data from these different instruments in a consistent manner resulting in a very significant improvement in network duty cycle over more than one solar cycle initiating what we call the IRIS++ network. The integrated radial velocities from the IRIS++ database (1989 to 1999) are available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/390/717
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Molecular Interaction Map of the Mammalian Cell Cycle Control and DNA Repair Systems
Kohn, Kurt W.
1999-01-01
Eventually to understand the integrated function of the cell cycle regulatory network, we must organize the known interactions in the form of a diagram, map, and/or database. A diagram convention was designed capable of unambiguous representation of networks containing multiprotein complexes, protein modifications, and enzymes that are substrates of other enzymes. To facilitate linkage to a database, each molecular species is symbolically represented only once in each diagram. Molecular species can be located on the map by means of indexed grid coordinates. Each interaction is referenced to an annotation list where pertinent information and references can be found. Parts of the network are grouped into functional subsystems. The map shows how multiprotein complexes could assemble and function at gene promoter sites and at sites of DNA damage. It also portrays the richness of connections between the p53-Mdm2 subsystem and other parts of the network. PMID:10436023
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Integrated Approaches to Drug Discovery for Oxidative Stress-Related Retinal Diseases.
Nishimura, Yuhei; Hara, Hideaki
2016-01-01
Excessive oxidative stress induces dysregulation of functional networks in the retina, resulting in retinal diseases such as glaucoma, age-related macular degeneration, and diabetic retinopathy. Although various therapies have been developed to reduce oxidative stress in retinal diseases, most have failed to show efficacy in clinical trials. This may be due to oversimplification of target selection for such a complex network as oxidative stress. Recent advances in high-throughput technologies have facilitated the collection of multilevel omics data, which has driven growth in public databases and in the development of bioinformatics tools. Integration of the knowledge gained from omics databases can be used to generate disease-related biological networks and to identify potential therapeutic targets within the networks. Here, we provide an overview of integrative approaches in the drug discovery process and provide simple examples of how the approaches can be exploited to identify oxidative stress-related targets for retinal diseases.
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Integrated Approaches to Drug Discovery for Oxidative Stress-Related Retinal Diseases
Hara, Hideaki
2016-01-01
Excessive oxidative stress induces dysregulation of functional networks in the retina, resulting in retinal diseases such as glaucoma, age-related macular degeneration, and diabetic retinopathy. Although various therapies have been developed to reduce oxidative stress in retinal diseases, most have failed to show efficacy in clinical trials. This may be due to oversimplification of target selection for such a complex network as oxidative stress. Recent advances in high-throughput technologies have facilitated the collection of multilevel omics data, which has driven growth in public databases and in the development of bioinformatics tools. Integration of the knowledge gained from omics databases can be used to generate disease-related biological networks and to identify potential therapeutic targets within the networks. Here, we provide an overview of integrative approaches in the drug discovery process and provide simple examples of how the approaches can be exploited to identify oxidative stress-related targets for retinal diseases. PMID:28053689
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ENFIN--A European network for integrative systems biology.
Kahlem, Pascal; Clegg, Andrew; Reisinger, Florian; Xenarios, Ioannis; Hermjakob, Henning; Orengo, Christine; Birney, Ewan
2009-11-01
Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.
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Proteomic characterization of hempseed (Cannabis sativa L.).
Aiello, Gilda; Fasoli, Elisa; Boschin, Giovanna; Lammi, Carmen; Zanoni, Chiara; Citterio, Attilio; Arnoldi, Anna
2016-09-16
This paper presents an investigation on hempseed proteome. The experimental approach, based on combinatorial peptide ligand libraries (CPLLs), SDS-PAGE separation, nLC-ESI-MS/MS identification, and database search, permitted identifying in total 181 expressed proteins. This very large number of identifications was achieved by searching in two databases: Cannabis sativa L. (56 gene products identified) and Arabidopsis thaliana (125 gene products identified). By performing a protein-protein association network analysis using the STRING software, it was possible to build the first interactomic map of all detected proteins, characterized by 137 nodes and 410 interactions. Finally, a Gene Ontology analysis of the identified species permitted to classify their molecular functions: the great majority is involved in the seed metabolic processes (41%), responses to stimulus (8%), and biological process (7%). Hempseed is an underexploited non-legume protein-rich seed. Although its protein is well known for its digestibility, essential amino acid composition, and useful techno-functional properties, a comprehensive proteome characterization is still lacking. The objective of this work was to fill this knowledge gap and provide information useful for a better exploitation of this seed in different food products. Copyright © 2016 Elsevier B.V. All rights reserved.
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Liao, Pei-Hung; Chu, William; Chu, Woei-Chyn
2014-05-01
In 2009, the Department of Health, part of Taiwan's Executive Yuan, announced the advent of electronic medical records to reduce medical expenses and facilitate the international exchange of medical record information. An information technology platform for nursing records in medical institutions was then quickly established, which improved nursing information systems and electronic databases. The purpose of the present study was to explore the usability of the data mining techniques to enhance completeness and ensure consistency of nursing records in the database system.First, the study used a Chinese word-segmenting system on common and special terms often used by the nursing staff. We also used text-mining techniques to collect keywords and create a keyword lexicon. We then used an association rule and artificial neural network to measure the correlation and forecasting capability for keywords. Finally, nursing staff members were provided with an on-screen pop-up menu to use when establishing nursing records. Our study found that by using mining techniques we were able to create a powerful keyword lexicon and establish a forecasting model for nursing diagnoses, ensuring the consistency of nursing terminology and improving the nursing staff's work efficiency and productivity.
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NASA Technical Reports Server (NTRS)
Goldgof, Gregory M.
2005-01-01
Distributed systems allow scientists from around the world to plan missions concurrently, while being updated on the revisions of their colleagues in real time. However, permitting multiple clients to simultaneously modify a single data repository can quickly lead to data corruption or inconsistent states between users. Since our message broker, the Java Message Service, does not ensure that messages will be received in the order they were published, we must implement our own numbering scheme to guarantee that changes to mission plans are performed in the correct sequence. Furthermore, distributed architectures must ensure that as new users connect to the system, they synchronize with the database without missing any messages or falling into an inconsistent state. Robust systems must also guarantee that all clients will remain synchronized with the database even in the case of multiple client failure, which can occur at any time due to lost network connections or a user's own system instability. The final design for the distributed system behind the Mars rover mission planning software fulfills all of these requirements and upon completion will be deployed to MER at the end of 2005 as well as Phoenix (2007) and MSL (2009).
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The European Narcolepsy Network (EU-NN) database.
Khatami, Ramin; Luca, Gianina; Baumann, Christian R; Bassetti, Claudio L; Bruni, Oliviero; Canellas, Francesca; Dauvilliers, Yves; Del Rio-Villegas, Rafael; Feketeova, Eva; Ferri, Raffaele; Geisler, Peter; Högl, Birgit; Jennum, Poul; Kornum, Birgitte R; Lecendreux, Michel; Martins-da-Silva, Antonio; Mathis, Johannes; Mayer, Geert; Paiva, Teresa; Partinen, Markku; Peraita-Adrados, Rosa; Plazzi, Guiseppe; Santamaria, Joan; Sonka, Karel; Riha, Renata; Tafti, Mehdi; Wierzbicka, Aleksandra; Young, Peter; Lammers, Gert Jan; Overeem, Sebastiaan
2016-06-01
Narcolepsy with cataplexy is a rare disease with an estimated prevalence of 0.02% in European populations. Narcolepsy shares many features of rare disorders, in particular the lack of awareness of the disease with serious consequences for healthcare supply. Similar to other rare diseases, only a few European countries have registered narcolepsy cases in databases of the International Classification of Diseases or in registries of the European health authorities. A promising approach to identify disease-specific adverse health effects and needs in healthcare delivery in the field of rare diseases is to establish a distributed expert network. A first and important step is to create a database that allows collection, storage and dissemination of data on narcolepsy in a comprehensive and systematic way. Here, the first prospective web-based European narcolepsy database hosted by the European Narcolepsy Network is introduced. The database structure, standardization of data acquisition and quality control procedures are described, and an overview provided of the first 1079 patients from 18 European specialized centres. Due to its standardization this continuously increasing data pool is most promising to provide a better insight into many unsolved aspects of narcolepsy and related disorders, including clear phenotype characterization of subtypes of narcolepsy, more precise epidemiological data and knowledge on the natural history of narcolepsy, expectations about treatment effects, identification of post-marketing medication side-effects, and will contribute to improve clinical trial designs and provide facilities to further develop phase III trials. © 2016 European Sleep Research Society.
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An architecture for integrating distributed and cooperating knowledge-based Air Force decision aids
NASA Technical Reports Server (NTRS)
Nugent, Richard O.; Tucker, Richard W.
1988-01-01
MITRE has been developing a Knowledge-Based Battle Management Testbed for evaluating the viability of integrating independently-developed knowledge-based decision aids in the Air Force tactical domain. The primary goal for the testbed architecture is to permit a new system to be added to a testbed with little change to the system's software. Each system that connects to the testbed network declares that it can provide a number of services to other systems. When a system wants to use another system's service, it does not address the server system by name, but instead transmits a request to the testbed network asking for a particular service to be performed. A key component of the testbed architecture is a common database which uses a relational database management system (RDBMS). The RDBMS provides a database update notification service to requesting systems. Normally, each system is expected to monitor data relations of interest to it. Alternatively, a system may broadcast an announcement message to inform other systems that an event of potential interest has occurred. Current research is aimed at dealing with issues resulting from integration efforts, such as dealing with potential mismatches of each system's assumptions about the common database, decentralizing network control, and coordinating multiple agents.
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Food Composition Database Format and Structure: A User Focused Approach
Clancy, Annabel K.; Woods, Kaitlyn; McMahon, Anne; Probst, Yasmine
2015-01-01
This study aimed to investigate the needs of Australian food composition database user’s regarding database format and relate this to the format of databases available globally. Three semi structured synchronous online focus groups (M = 3, F = 11) and n = 6 female key informant interviews were recorded. Beliefs surrounding the use, training, understanding, benefits and limitations of food composition data and databases were explored. Verbatim transcriptions underwent preliminary coding followed by thematic analysis with NVivo qualitative analysis software to extract the final themes. Schematic analysis was applied to the final themes related to database format. Desktop analysis also examined the format of six key globally available databases. 24 dominant themes were established, of which five related to format; database use, food classification, framework, accessibility and availability, and data derivation. Desktop analysis revealed that food classification systems varied considerably between databases. Microsoft Excel was a common file format used in all databases, and available software varied between countries. User’s also recognised that food composition databases format should ideally be designed specifically for the intended use, have a user-friendly food classification system, incorporate accurate data with clear explanation of data derivation and feature user input. However, such databases are limited by data availability and resources. Further exploration of data sharing options should be considered. Furthermore, user’s understanding of food composition data and databases limitations is inherent to the correct application of non-specific databases. Therefore, further exploration of user FCDB training should also be considered. PMID:26554836
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2008-02-01
FINAL ENVIRONMENTAL ASSESSMENT February 2008 Malmstrom ® AFB WIDE AREA COVERAGE CONSTRUCT LAND MOBILE NETWORK COMMUNICATIONS INFRASTRUCTURE...Wide Area Coverage Construct Land Mobile Network Communications Infrastructure Malmstrom Air Force Base, Montana 5a. CONTRACT NUMBER 5b. GRANT...SIGNIFICANT IMPACT WIDE AREA COVERAGE CONSTRUCT LAND MOBILE NETWORK COMMUNICATIONS INFRASTRUCTURE MALMSTROM AIR FORCE BASE, MONTANA The
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75 FR 60415 - Proposed Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2010-09-30
... computer systems and networks. This information collection is required to obtain the necessary data... card reflecting those benefits and privileges, and to maintain a centralized database of the eligible... card reflecting those benefits and privileges, and to maintain a centralized database of the eligible...
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Sustaining Indigenous Languages in Cyberspace.
ERIC Educational Resources Information Center
Cazden, Courtney B.
This paper describes how certain types of electronic technologies, specifically CD-ROMs, computerized databases, and telecommunications networks, are being incorporated into language and culture revitalization projects in Alaska and around the Pacific. The paper presents two examples of CD-ROMs and computerized databases from Alaska, describing…
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Evolution of the social network of scientific collaborations
NASA Astrophysics Data System (ADS)
Barabási, A. L.; Jeong, H.; Néda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T.
2002-08-01
The co-authorship network of scientists represents a prototype of complex evolving networks. In addition, it offers one of the most extensive database to date on social networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an 8-year period (1991-98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. Three complementary approaches allow us to obtain a detailed characterization. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, affecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network's time evolution. In some limits the model can be solved analytically, predicting a two-regime scaling in agreement with the measurements. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically. The combined numerical and analytical results underline the important role internal links play in determining the observed scaling behavior and network topology. The results and methodologies developed in the context of the co-authorship network could be useful for a systematic study of other complex evolving networks as well, such as the world wide web, Internet, or other social networks.
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A Brief Review of RNA–Protein Interaction Database Resources
Yi, Ying; Zhao, Yue; Huang, Yan; Wang, Dong
2017-01-01
RNA–Protein interactions play critical roles in various biological processes. By collecting and analyzing the RNA–Protein interactions and binding sites from experiments and predictions, RNA–Protein interaction databases have become an essential resource for the exploration of the transcriptional and post-transcriptional regulatory network. Here, we briefly review several widely used RNA–Protein interaction database resources developed in recent years to provide a guide of these databases. The content and major functions in databases are presented. The brief description of database helps users to quickly choose the database containing information they interested. In short, these RNA–Protein interaction database resources are continually updated, but the current state shows the efforts to identify and analyze the large amount of RNA–Protein interactions. PMID:29657278
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Guerette, P.; Robinson, B.; Moran, W. P.; Messick, C.; Wright, M.; Wofford, J.; Velez, R.
1995-01-01
Community-based multi-disciplinary care of chronically ill individuals frequently requires the efforts of several agencies and organizations. The Community Care Coordination Network (CCCN) is an effort to establish a community-based clinical database and electronic communication system to facilitate the exchange of pertinent patient data among primary care, community-based and hospital-based providers. In developing a primary care based electronic record, a method is needed to update records from the field or remote sites and agencies and yet maintain data quality. Scannable data entry with fixed fields, optical character recognition and verification was compared to traditional keyboard data entry to determine the relative efficiency of each method in updating the CCCN database. PMID:8563414
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Shao, Q; Rowe, R C; York, P
2007-06-01
This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R(2). Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators.
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Networking consumer health information: bringing the patient into the medical information loop.
Martin, E R; Lanier, D
1996-04-01
The Library of the Health Sciences at the University of Illinois at Chicago obtained a grant from the Illinois State Library to implement a statewide demonstration project that would provide consumer health information (CHI) using InfoTrac's Health Reference Center CD-ROM database. The goals of the project were to cooperate with targeted public libraries and clinics in providing CHI at the earliest point of need; to provide access to the database via a dial-up network server and a toll-free telephone number; and to work with targeted sites on database training, core CHI reference sources, and referral procedures. This paper provides background information about the project; describes the major systems and technical issues encountered; and discusses the outcomes, impact, and envisioned enhancements.
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Automatic comparison of striation marks and automatic classification of shoe prints
NASA Astrophysics Data System (ADS)
Geradts, Zeno J.; Keijzer, Jan; Keereweer, Isaac
1995-09-01
A database for toolmarks (named TRAX) and a database for footwear outsole designs (named REBEZO) have been developed on a PC. The databases are filled with video-images and administrative data about the toolmarks and the footwear designs. An algorithm for the automatic comparison of the digitized striation patterns has been developed for TRAX. The algorithm appears to work well for deep and complete striation marks and will be implemented in TRAX. For REBEZO some efforts have been made to the automatic classification of outsole patterns. The algorithm first segments the shoeprofile. Fourier-features are selected for the separate elements and are classified with a neural network. In future developments information on invariant moments of the shape and rotation angle will be included in the neural network.
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A Quality-Control-Oriented Database for a Mesoscale Meteorological Observation Network
NASA Astrophysics Data System (ADS)
Lussana, C.; Ranci, M.; Uboldi, F.
2012-04-01
In the operational context of a local weather service, data accessibility and quality related issues must be managed by taking into account a wide set of user needs. This work describes the structure and the operational choices made for the operational implementation of a database system storing data from highly automated observing stations, metadata and information on data quality. Lombardy's environmental protection agency, ARPA Lombardia, manages a highly automated mesoscale meteorological network. A Quality Assurance System (QAS) ensures that reliable observational information is collected and disseminated to the users. The weather unit in ARPA Lombardia, at the same time an important QAS component and an intensive data user, has developed a database specifically aimed to: 1) providing quick access to data for operational activities and 2) ensuring data quality for real-time applications, by means of an Automatic Data Quality Control (ADQC) procedure. Quantities stored in the archive include hourly aggregated observations of: precipitation amount, temperature, wind, relative humidity, pressure, global and net solar radiation. The ADQC performs several independent tests on raw data and compares their results in a decision-making procedure. An important ADQC component is the Spatial Consistency Test based on Optimal Interpolation. Interpolated and Cross-Validation analysis values are also stored in the database, providing further information to human operators and useful estimates in case of missing data. The technical solution adopted is based on a LAMP (Linux, Apache, MySQL and Php) system, constituting an open source environment suitable for both development and operational practice. The ADQC procedure itself is performed by R scripts directly interacting with the MySQL database. Users and network managers can access the database by using a set of web-based Php applications.
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Urban Mobility and Location-Based Social Networks: Social, Economic and Environmental Incentives
ERIC Educational Resources Information Center
Zhang, Ke
2016-01-01
Location-based social networks (LBSNs) have recently attracted the interest of millions of users who can now not only connect and interact with their friends--as it also happens in traditional online social networks--but can also voluntarily share their whereabouts in real time. A location database is the backbone of a location-based social…
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ERIC Educational Resources Information Center
Molina, Enzo
1986-01-01
Use of online bibliographic databases in Mexico is provided through Servicio de Consulta a Bancos de Informacion, a public service that provides information retrieval, document delivery, translation, technical support, and training services. Technical infrastructure is based on a public packet-switching network and institutional users may receive…
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DDRprot: a database of DNA damage response-related proteins.
Andrés-León, Eduardo; Cases, Ildefonso; Arcas, Aida; Rojas, Ana M
2016-01-01
The DNA Damage Response (DDR) signalling network is an essential system that protects the genome's integrity. The DDRprot database presented here is a resource that integrates manually curated information on the human DDR network and its sub-pathways. For each particular DDR protein, we present detailed information about its function. If involved in post-translational modifications (PTMs) with each other, we depict the position of the modified residue/s in the three-dimensional structures, when resolved structures are available for the proteins. All this information is linked to the original publication from where it was obtained. Phylogenetic information is also shown, including time of emergence and conservation across 47 selected species, family trees and sequence alignments of homologues. The DDRprot database can be queried by different criteria: pathways, species, evolutionary age or involvement in (PTM). Sequence searches using hidden Markov models can be also used.Database URL: http://ddr.cbbio.es. © The Author(s) 2016. Published by Oxford University Press.
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NASA Astrophysics Data System (ADS)
Wang, Jian
2017-01-01
In order to change traditional PE teaching mode and realize the interconnection, interworking and sharing of PE teaching resources, a distance PE teaching platform based on broadband network is designed and PE teaching information resource database is set up. The designing of PE teaching information resource database takes Windows NT 4/2000Server as operating system platform, Microsoft SQL Server 7.0 as RDBMS, and takes NAS technology for data storage and flow technology for video service. The analysis of system designing and implementation shows that the dynamic PE teaching information resource sharing platform based on Web Service can realize loose coupling collaboration, realize dynamic integration and active integration and has good integration, openness and encapsulation. The distance PE teaching platform based on Web Service and the design scheme of PE teaching information resource database can effectively solve and realize the interconnection, interworking and sharing of PE teaching resources and adapt to the informatization development demands of PE teaching.
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Premature ventricular contraction detection combining deep neural networks and rules inference.
Zhou, Fei-Yan; Jin, Lin-Peng; Dong, Jun
2017-06-01
Premature ventricular contraction (PVC), which is a common form of cardiac arrhythmia caused by ectopic heartbeat, can lead to life-threatening cardiac conditions. Computer-aided PVC detection is of considerable importance in medical centers or outpatient ECG rooms. In this paper, we proposed a new approach that combined deep neural networks and rules inference for PVC detection. The detection performance and generalization were studied using publicly available databases: the MIT-BIH arrhythmia database (MIT-BIH-AR) and the Chinese Cardiovascular Disease Database (CCDD). The PVC detection accuracy on the MIT-BIH-AR database was 99.41%, with a sensitivity and specificity of 97.59% and 99.54%, respectively, which were better than the results from other existing methods. To test the generalization capability, the detection performance was also evaluated on the CCDD. The effectiveness of the proposed method was confirmed by the accuracy (98.03%), sensitivity (96.42%) and specificity (98.06%) with the dataset over 140,000 ECG recordings of the CCDD. Copyright © 2017 Elsevier B.V. All rights reserved.
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Intrusion Detection in Database Systems
NASA Astrophysics Data System (ADS)
Javidi, Mohammad M.; Sohrabi, Mina; Rafsanjani, Marjan Kuchaki
Data represent today a valuable asset for organizations and companies and must be protected. Ensuring the security and privacy of data assets is a crucial and very difficult problem in our modern networked world. Despite the necessity of protecting information stored in database systems (DBS), existing security models are insufficient to prevent misuse, especially insider abuse by legitimate users. One mechanism to safeguard the information in these databases is to use an intrusion detection system (IDS). The purpose of Intrusion detection in database systems is to detect transactions that access data without permission. In this paper several database Intrusion detection approaches are evaluated.
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Second Line of Defense Master Spares Catalog
DOE Office of Scientific and Technical Information (OSTI.GOV)
Henderson, Dale L.; Muller, George; Mercier, Theresa M.
This catalog is intended to be a comprehensive listing of repair parts, components, kits, and consumable items used on the equipment deployed at SLD sites worldwide. The catalog covers detection, CAS, network, ancillary equipment, and tools. The catalog is backed by a Master Parts Database which is used to generate the standard report views of the catalog. The master parts database is a relational database containing a record for every part in the master parts catalog along with supporting tables for normalizing fields in the records. The database also includes supporting queries, database maintenance forms, and reports.
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Le, Duc-Hau
2015-01-01
Protein complexes formed by non-covalent interaction among proteins play important roles in cellular functions. Computational and purification methods have been used to identify many protein complexes and their cellular functions. However, their roles in terms of causing disease have not been well discovered yet. There exist only a few studies for the identification of disease-associated protein complexes. However, they mostly utilize complicated heterogeneous networks which are constructed based on an out-of-date database of phenotype similarity network collected from literature. In addition, they only apply for diseases for which tissue-specific data exist. In this study, we propose a method to identify novel disease-protein complex associations. First, we introduce a framework to construct functional similarity protein complex networks where two protein complexes are functionally connected by either shared protein elements, shared annotating GO terms or based on protein interactions between elements in each protein complex. Second, we propose a simple but effective neighborhood-based algorithm, which yields a local similarity measure, to rank disease candidate protein complexes. Comparing the predictive performance of our proposed algorithm with that of two state-of-the-art network propagation algorithms including one we used in our previous study, we found that it performed statistically significantly better than that of these two algorithms for all the constructed functional similarity protein complex networks. In addition, it ran about 32 times faster than these two algorithms. Moreover, our proposed method always achieved high performance in terms of AUC values irrespective of the ways to construct the functional similarity protein complex networks and the used algorithms. The performance of our method was also higher than that reported in some existing methods which were based on complicated heterogeneous networks. Finally, we also tested our method with prostate cancer and selected the top 100 highly ranked candidate protein complexes. Interestingly, 69 of them were evidenced since at least one of their protein elements are known to be associated with prostate cancer. Our proposed method, including the framework to construct functional similarity protein complex networks and the neighborhood-based algorithm on these networks, could be used for identification of novel disease-protein complex associations.
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Creating an Effective Network: The GRACEnet Example
NASA Astrophysics Data System (ADS)
Follett, R. F.; Del Grosso, S.
2008-12-01
Networking activities require time, work, and nurturing. The objective of this presentation is to share the experience gained from The Greenhouse gas Reduction through Agricultural Carbon Enhancement network (GRACEnet). GRACEnet, formally established in 2005 by the ARS/USDA, resulted from workshops, teleconferences, and other activities beginning in at least 2002. Critical factors for its formation were to develop and formalize a common vision, goals, and objectives, which was accomplished in a 2005 workshop. The 4-person steering committee (now 5) was charged with coordinating the part-time (0.05- to 0.5 SY/location) efforts across 30 ARS locations to develop four products; (1) a national database, (2) regional/national guidelines of management practices, (3) computer models, and (4) "state-of-knowledge" summary publications. All locations are asked to contribute to the database from their field studies. Communication with everyone and periodic meeting are extremely important. Required to populate the database has to be a common vision of sharing, format, and trust. Based upon the e-mail list, GRACEnet has expanded from about 30 to now nearly 70 participants. Annual reports and a new website help facilitate this activity.
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INTERPOL's Surveillance Network in Curbing Transnational Terrorism
Gardeazabal, Javier; Sandler, Todd
2015-01-01
Abstract This paper investigates the role that International Criminal Police Organization (INTERPOL) surveillance—the Mobile INTERPOL Network Database (MIND) and the Fixed INTERPOL Network Database (FIND)—played in the War on Terror since its inception in 2005. MIND/FIND surveillance allows countries to screen people and documents systematically at border crossings against INTERPOL databases on terrorists, fugitives, and stolen and lost travel documents. Such documents have been used in the past by terrorists to transit borders. By applying methods developed in the treatment‐effects literature, this paper establishes that countries adopting MIND/FIND experienced fewer transnational terrorist attacks than they would have had they not adopted MIND/FIND. Our estimates indicate that, on average, from 2008 to 2011, adopting and using MIND/FIND results in 0.5 fewer transnational terrorist incidents each year per 100 million people. Thus, a country like France with a population just above 64 million people in 2008 would have 0.32 fewer transnational terrorist incidents per year owing to its use of INTERPOL surveillance. This amounts to a sizeable average proportional reduction of about 30 percent.
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NASA Astrophysics Data System (ADS)
Zhao, Yiqun; Wang, Zhihui
2015-12-01
The Internet of things (IOT) is a kind of intelligent networks which can be used to locate, track, identify and supervise people and objects. One of important core technologies of intelligent visual internet of things ( IVIOT) is the intelligent visual tag system. In this paper, a research is done into visual feature extraction and establishment of visual tags of the human face based on ORL face database. Firstly, we use the principal component analysis (PCA) algorithm for face feature extraction, then adopt the support vector machine (SVM) for classifying and face recognition, finally establish a visual tag for face which is already classified. We conducted a experiment focused on a group of people face images, the result show that the proposed algorithm have good performance, and can show the visual tag of objects conveniently.
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Proposal of Network-Based Multilingual Space Dictionary Database System
NASA Astrophysics Data System (ADS)
Yoshimitsu, T.; Hashimoto, T.; Ninomiya, K.
2002-01-01
The International Academy of Astronautics (IAA) is now constructing a multilingual dictionary database system of space-friendly terms. The database consists of a lexicon and dictionaries of multiple languages. The lexicon is a table which relates corresponding terminology in different languages. Each language has a dictionary which contains terms and their definitions. The database assumes the use on the internet. Updating and searching the terms and definitions are conducted via the network. Maintaining the database is conducted by the international cooperation. A new word arises day by day, thus to easily input new words and their definitions to the database is required for the longstanding success of the system. The main key of the database is an English term which is approved at the table held once or twice with the working group members. Each language has at lease one working group member who is responsible of assigning the corresponding term and the definition of the term of his/her native language. Inputting and updating terms and their definitions can be conducted via the internet from the office of each member which may be located at his/her native country. The system is constructed by freely distributed database server program working on the Linux operating system, which will be installed at the head office of IAA. Once it is installed, it will be open to all IAA members who can search the terms via the internet. Currently the authors are constructing the prototype system which is described in this paper.
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Very Deep Convolutional Neural Networks for Morphologic Classification of Erythrocytes.
Durant, Thomas J S; Olson, Eben M; Schulz, Wade L; Torres, Richard
2017-12-01
Morphologic profiling of the erythrocyte population is a widely used and clinically valuable diagnostic modality, but one that relies on a slow manual process associated with significant labor cost and limited reproducibility. Automated profiling of erythrocytes from digital images by capable machine learning approaches would augment the throughput and value of morphologic analysis. To this end, we sought to evaluate the performance of leading implementation strategies for convolutional neural networks (CNNs) when applied to classification of erythrocytes based on morphology. Erythrocytes were manually classified into 1 of 10 classes using a custom-developed Web application. Using recent literature to guide architectural considerations for neural network design, we implemented a "very deep" CNN, consisting of >150 layers, with dense shortcut connections. The final database comprised 3737 labeled cells. Ensemble model predictions on unseen data demonstrated a harmonic mean of recall and precision metrics of 92.70% and 89.39%, respectively. Of the 748 cells in the test set, 23 misclassification errors were made, with a correct classification frequency of 90.60%, represented as a harmonic mean across the 10 morphologic classes. These findings indicate that erythrocyte morphology profiles could be measured with a high degree of accuracy with "very deep" CNNs. Further, these data support future efforts to expand classes and optimize practical performance in a clinical environment as a prelude to full implementation as a clinical tool. © 2017 American Association for Clinical Chemistry.
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Data management for the internet of things: design primitives and solution.
Abu-Elkheir, Mervat; Hayajneh, Mohammad; Ali, Najah Abu
2013-11-14
The Internet of Things (IoT) is a networking paradigm where interconnected, smart objects continuously generate data and transmit it over the Internet. Much of the IoT initiatives are geared towards manufacturing low-cost and energy-efficient hardware for these objects, as well as the communication technologies that provide objects interconnectivity. However, the solutions to manage and utilize the massive volume of data produced by these objects are yet to mature. Traditional database management solutions fall short in satisfying the sophisticated application needs of an IoT network that has a truly global-scale. Current solutions for IoT data management address partial aspects of the IoT environment with special focus on sensor networks. In this paper, we survey the data management solutions that are proposed for IoT or subsystems of the IoT. We highlight the distinctive design primitives that we believe should be addressed in an IoT data management solution, and discuss how they are approached by the proposed solutions. We finally propose a data management framework for IoT that takes into consideration the discussed design elements and acts as a seed to a comprehensive IoT data management solution. The framework we propose adapts a federated, data- and sources-centric approach to link the diverse Things with their abundance of data to the potential applications and services that are envisioned for IoT.
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Data Management for the Internet of Things: Design Primitives and Solution
Abu-Elkheir, Mervat; Hayajneh, Mohammad; Ali, Najah Abu
2013-01-01
The Internet of Things (IoT) is a networking paradigm where interconnected, smart objects continuously generate data and transmit it over the Internet. Much of the IoT initiatives are geared towards manufacturing low-cost and energy-efficient hardware for these objects, as well as the communication technologies that provide objects interconnectivity. However, the solutions to manage and utilize the massive volume of data produced by these objects are yet to mature. Traditional database management solutions fall short in satisfying the sophisticated application needs of an IoT network that has a truly global-scale. Current solutions for IoT data management address partial aspects of the IoT environment with special focus on sensor networks. In this paper, we survey the data management solutions that are proposed for IoT or subsystems of the IoT. We highlight the distinctive design primitives that we believe should be addressed in an IoT data management solution, and discuss how they are approached by the proposed solutions. We finally propose a data management framework for IoT that takes into consideration the discussed design elements and acts as a seed to a comprehensive IoT data management solution. The framework we propose adapts a federated, data- and sources-centric approach to link the diverse Things with their abundance of data to the potential applications and services that are envisioned for IoT. PMID:24240599
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Zhuang, Xiaowei; Walsh, Ryan R; Sreenivasan, Karthik; Yang, Zhengshi; Mishra, Virendra; Cordes, Dietmar
2018-05-15
The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD. Copyright © 2018 Elsevier Inc. All rights reserved.
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Kaiser, Roselinde H; Andrews-Hanna, Jessica R; Wager, Tor D; Pizzagalli, Diego A
2015-06-01
Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. To investigate network dysfunction in MDD through a meta-analysis of rsFC studies. Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data. Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis. Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network. Major depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions. Reduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.
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Distributed policy based access to networked heterogeneous ISR data sources
NASA Astrophysics Data System (ADS)
Bent, G.; Vyvyan, D.; Wood, David; Zerfos, Petros; Calo, Seraphin
2010-04-01
Within a coalition environment, ad hoc Communities of Interest (CoI's) come together, perhaps for only a short time, with different sensors, sensor platforms, data fusion elements, and networks to conduct a task (or set of tasks) with different coalition members taking different roles. In such a coalition, each organization will have its own inherent restrictions on how it will interact with the others. These are usually stated as a set of policies, including security and privacy policies. The capability that we want to enable for a coalition operation is to provide access to information from any coalition partner in conformance with the policies of all. One of the challenges in supporting such ad-hoc coalition operations is that of providing efficient access to distributed sources of data, where the applications requiring the data do not have knowledge of the location of the data within the network. To address this challenge the International Technology Alliance (ITA) program has been developing the concept of a Dynamic Distributed Federated Database (DDFD), also know as a Gaian Database. This type of database provides a means for accessing data across a network of distributed heterogeneous data sources where access to the information is controlled by a mixture of local and global policies. We describe how a network of disparate ISR elements can be expressed as a DDFD and how this approach enables sensor and other information sources to be discovered autonomously or semi-autonomously and/or combined, fused formally defined local and global policies.
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Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien
2016-01-01
This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.
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Robinson, J M; Henderson, W A
2018-01-12
We report a method using functional-molecular databases and network modelling to identify hypothetical mRNA-miRNA interaction networks regulating intestinal epithelial barrier function. The model forms a data-analysis component of our cell culture experiments, which produce RNA expression data from Nanostring Technologies nCounter ® system. The epithelial tight-junction (TJ) and actin cytoskeleton interact as molecular components of the intestinal epithelial barrier. Upstream regulation of TJ-cytoskeleton interaction is effected by the Rac/Rock/Rho signaling pathway and other associated pathways which may be activated or suppressed by extracellular signaling from growth factors, hormones, and immune receptors. Pathway activations affect epithelial homeostasis, contributing to degradation of the epithelial barrier associated with osmotic dysregulation, inflammation, and tumor development. The complexity underlying miRNA-mRNA interaction networks represents a roadblock for prediction and validation of competing-endogenous RNA network function. We developed a network model to identify hypothetical co-regulatory motifs in a miRNA-mRNA interaction network related to epithelial function. A mRNA-miRNA interaction list was generated using KEGG and miRWalk2.0 databases. R-code was developed to quantify and visualize inherent network structures. We identified a sub-network with a high number of shared, targeting miRNAs, of genes associated with cellular proliferation and cancer, including c-MYC and Cyclin D.
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The Listeria monocytogenes strain 10403S BioCyc database
Orsi, Renato H.; Bergholz, Teresa M.; Wiedmann, Martin; Boor, Kathryn J.
2015-01-01
Listeria monocytogenes is a food-borne pathogen of humans and other animals. The striking ability to survive several stresses usually used for food preservation makes L. monocytogenes one of the biggest concerns to the food industry, while the high mortality of listeriosis in specific groups of humans makes it a great concern for public health. Previous studies have shown that a regulatory network involving alternative sigma (σ) factors and transcription factors is pivotal to stress survival. However, few studies have evaluated at the metabolic networks controlled by these regulatory mechanisms. The L. monocytogenes BioCyc database uses the strain 10403S as a model. Computer-generated initial annotation for all genes also allowed for identification, annotation and display of predicted reactions and pathways carried out by a single cell. Further ongoing manual curation based on published data as well as database mining for selected genes allowed the more refined annotation of functions, which, in turn, allowed for annotation of new pathways and fine-tuning of previously defined pathways to more L. monocytogenes-specific pathways. Using RNA-Seq data, several transcription start sites and promoter regions were mapped to the 10403S genome and annotated within the database. Additionally, the identification of promoter regions and a comprehensive review of available literature allowed the annotation of several regulatory interactions involving σ factors and transcription factors. The L. monocytogenes 10403S BioCyc database is a new resource for researchers studying Listeria and related organisms. It allows users to (i) have a comprehensive view of all reactions and pathways predicted to take place within the cell in the cellular overview, as well as to (ii) upload their own data, such as differential expression data, to visualize the data in the scope of predicted pathways and regulatory networks and to carry on enrichment analyses using several different annotations available within the database. Database URL: http://biocyc.org/organism-summary?object=10403S_RAST PMID:25819074
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A Markovian model of evolving world input-output network
Isacchini, Giulio
2017-01-01
The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money. PMID:29065145
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Munro, Kelly; Miller, Thomas H; Martins, Claudia P B; Edge, Anthony M; Cowan, David A; Barron, Leon P
2015-05-29
The modelling and prediction of reversed-phase chromatographic retention time (tR) under gradient elution conditions for 166 pharmaceuticals in wastewater extracts is presented using artificial neural networks for the first time. Radial basis function, multilayer perceptron and generalised regression neural networks were investigated and a comparison of their predictive ability for model solutions discussed. For real world application, the effect of matrix complexity on tR measurements is presented. Measured tR for some compounds in influent wastewater varied by >1min in comparison to tR in model solutions. Similarly, matrix impact on artificial neural network predictive ability was addressed towards developing a more robust approach for routine screening applications. Overall, the best neural network had a predictive accuracy of <1.3min at the 75th percentile of all measured tR data in wastewater samples (<10% of the total runtime). Coefficients of determination for 30 blind test compounds in wastewater matrices lay at or above R(2)=0.92. Finally, the model was evaluated for application to the semi-targeted identification of pharmaceutical residues during a weeklong wastewater sampling campaign. The model successfully identified native compounds at a rate of 83±4% and 73±5% in influent and effluent extracts, respectively. The use of an HRMS database and the optimised ANN model was also applied to shortlisting of 37 additional compounds in wastewater. Ultimately, this research will potentially enable faster identification of emerging contaminants in the environment through more efficient post-acquisition data mining. Copyright © 2015 Elsevier B.V. All rights reserved.
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Luo, Biao; Liu, Derong; Wu, Huai-Ning
2018-06-01
Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.
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Investigation of candidate genes for osteoarthritis based on gene expression profiles.
Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei
2016-12-01
To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.
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PEP725 Pan European Phenological Database
NASA Astrophysics Data System (ADS)
Koch, E.; Adler, S.; Lipa, W.; Ungersböck, M.; Zach-Hermann, S.
2010-09-01
Europe is in the fortunate situation that it has a long tradition in phenological networking: the history of collecting phenological data and using them in climatology has its starting point in 1751 when Carl von Linné outlined in his work Philosophia Botanica methods for compiling annual plant calendars of leaf opening, flowering, fruiting and leaf fall together with climatological observations "so as to show how areas differ". Recently in most European countries, phenological observations have been carried out routinely for more than 50 years by different governmental and non governmental organisations and following different observation guidelines, the data stored at different places in different formats. This has been really hampering pan European studies as one has to address many network operators to get access to the data before one can start to bring them in a uniform style. From 2004 to 2009 the COST-action 725 established a European wide data set of phenological observations. But the deliverables of this COST action was not only the common phenological database and common observation guidelines - COST725 helped to trigger a revival of some old networks and to establish new ones as for instance in Sweden. At the end of 2009 the COST action the database comprised about 8 million data in total from 15 European countries plus the data from the International Phenological Gardens IPG. In January 2010 PEP725 began its work as follow up project with funding from EUMETNET the network of European meteorological services and of ZAMG the Austrian national meteorological service. PEP725 not only will take over the part of maintaining, updating the COST725 database, but also to bring in phenological data from the time before 1951, developing better quality checking procedures and ensuring an open access to the database. An attractive webpage will make phenology and climate impacts on vegetation more visible in the public enabling a monitoring of vegetation development.
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2010-09-01
5 2. SCIL Architecture ...............................................................................6 3. Assertions...137 x THIS PAGE INTENTIONALLY LEFT BLANK xi LIST OF FIGURES Figure 1. SCIL architecture...Database Connectivity LAN Local Area Network ODBC Open Database Connectivity SCIL Social-Cultural Content in Language UMD
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Online Islamic Organizations and Measuring Web Effectiveness
2004-12-01
Internet Research 13 (2003) : 17-26. Retrived from ProQuest online database on 15 May 2004. Lee, Jae-Kwan. “A model for monitoring public sector...Web site strategy.” Internet Research : Electronic Networking Applications and Policy 13 (2003) : 259-266. Retrieved from Emerad online database on
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NASA Technical Reports Server (NTRS)
Petropulos, Dolores; Bittner, David; Murawski, Robert; Golden, Bert
2015-01-01
The SmallSat has an unrealized potential in both the private industry and in the federal government. Currently over 70 companies, 50 universities and 17 governmental agencies are involved in SmallSat research and development. In 1994, the U.S. Army Missile and Defense mapped the moon using smallSat imagery. Since then Smart Phones have introduced this imagery to the people of the world as diverse industries watched this trend. The deployment cost of smallSats is also greatly reduced compared to traditional satellites due to the fact that multiple units can be deployed in a single mission. Imaging payloads have become more sophisticated, smaller and lighter. In addition, the growth of small technology obtained from private industries has led to the more widespread use of smallSats. This includes greater revisit rates in imagery, significantly lower costs, the ability to update technology more frequently and the ability to decrease vulnerability of enemy attacks. The popularity of smallSats show a changing mentality in this fast paced world of tomorrow. What impact has this created on the NASA communication networks now and in future years? In this project, we are developing the SmallSat Relational Database which can support a simulation of smallSats within the NASA SCaN Compatability Environment for Networks and Integrated Communications (SCENIC) Modeling and Simulation Lab. The NASA Space Communications and Networks (SCaN) Program can use this modeling to project required network support needs in the next 10 to 15 years. The SmallSat Rational Database could model smallSats just as the other SCaN databases model the more traditional larger satellites, with a few exceptions. One being that the smallSat Database is designed to be built-to-order. The SmallSat database holds various hardware configurations that can be used to model a smallSat. It will require significant effort to develop as the research material can only be populated by hand to obtain the unique data required. When completed it will interface with the SCENIC environment to allow modeling of smallSats. The SmallSat Relational Database can also be integrated with the SCENIC Simulation modeling system that is currently in development. The SmallSat Relational Database simulation will be of great significance in assisting the NASA SCaN group to understand the impact the smallSats have made which have populated the lower orbit around our mother earth. What I have created and worked on this summer session 2015, is the basis for a tool that will be of value to the NASA SCaN SCENIC Simulation Environment for years to come.
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Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent
2009-01-01
Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039
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NASA Astrophysics Data System (ADS)
Nasertdinova, A. D.; Bochkarev, V. V.
2017-11-01
Deep neural networks with a large number of parameters are a powerful tool for solving problems of pattern recognition, prediction and classification. Nevertheless, overfitting remains a serious problem in the use of such networks. A method of solving the problem of overfitting is proposed in this article. This method is based on reducing the number of independent parameters of a neural network model using the principal component analysis, and can be implemented using existing libraries of neural computing. The algorithm was tested on the problem of recognition of handwritten symbols from the MNIST database, as well as on the task of predicting time series (rows of the average monthly number of sunspots and series of the Lorentz system were used). It is shown that the application of the principal component analysis enables reducing the number of parameters of the neural network model when the results are good. The average error rate for the recognition of handwritten figures from the MNIST database was 1.12% (which is comparable to the results obtained using the "Deep training" methods), while the number of parameters of the neural network can be reduced to 130 times.
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DRUG ABUSE WARNING NETWORK (DAWN) DATABASE
The Drug Abuse Warning Network (DAWN) is an ongoing drug abuse data collection system sponsored by SAMHSA's Office of Applied Studies. DAWN collects data from: (1) hospital emergency departments (EDs) and (2) medical examiners (MEs). The DAWN ED component relies on a nationally r...
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Florida: Library Networking and Technology Development.
ERIC Educational Resources Information Center
Wilkins, Barratt, Ed.
1996-01-01
Explains the development of library networks in Florida and the role of the state library. Topics include regional multitype library consortia; a statewide bibliographic database; interlibrary loan; Internet access in public libraries; government information, including remote public access; automation projects; telecommunications; and free-nets.…
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The University of South Carolina: College and University Computing Environment.
ERIC Educational Resources Information Center
CAUSE/EFFECT, 1987
1987-01-01
Both academic and administrative computing as well as network and communications services for the university are provided and supported by the Computer Services Division. Academic services, administrative services, systems engineering and database administration, communications, networking services, operations, and library technologies are…
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Integration Of An MR Image Network Into A Clinical PACS
NASA Astrophysics Data System (ADS)
Ratib, Osman M.; Mankovich, Nicholas J.; Taira, Ricky K.; Cho, Paul S.; Huang, H. K.
1988-06-01
A direct link between a clinical pediatric PACS module and a FONAR MRI image network was implemented. The original MR network combines together the MR scanner, a remote viewing station and a central archiving station. The pediatric PACS directly connects to the archiving unit through an Ethernet TCP-IP network adhering to FONAR's protocol. The PACS communication software developed supports the transfer of patient studies and the patient information directly from the MR archive database to the pediatric PACS. In the first phase of our project we developed a package to transfer data between a VAX-111750 and the IBM PC I AT-based MR archive database through the Ethernet network. This system served as a model for PACS-to-modality network communication. Once testing was complete on this research network, the software and network hardware was moved to the clinical pediatric VAX for full PACS integration. In parallel to the direct transmission of digital images to the Pediatric PACS, a broadband communication system in video format was developed for real-time broadcasting of images originating from the MR console to 8 remote viewing stations distributed in the radiology department. These analog viewing stations allow the radiologists to directly monitor patient positioning and to select the scan levels during a patient examination from remote locations in the radiology department. This paper reports (1) the technical details of this implementation, (2) the merits of this network development scheme, and (3) the performance statistics of the network-to-PACS interface.
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Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier
2016-01-01
Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses.
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REGENBOGEN, SAM; WILKINS, ANGELA D.; LICHTARGE, OLIVIER
2015-01-01
Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170
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From image captioning to video summary using deep recurrent networks and unsupervised segmentation
NASA Astrophysics Data System (ADS)
Morosanu, Bogdan-Andrei; Lemnaru, Camelia
2018-04-01
Automatic captioning systems based on recurrent neural networks have been tremendously successful at providing realistic natural language captions for complex and varied image data. We explore methods for adapting existing models trained on large image caption data sets to a similar problem, that of summarising videos using natural language descriptions and frame selection. These architectures create internal high level representations of the input image that can be used to define probability distributions and distance metrics on these distributions. Specifically, we interpret each hidden unit inside a layer of the caption model as representing the un-normalised log probability of some unknown image feature of interest for the caption generation process. We can then apply well understood statistical divergence measures to express the difference between images and create an unsupervised segmentation of video frames, classifying consecutive images of low divergence as belonging to the same context, and those of high divergence as belonging to different contexts. To provide a final summary of the video, we provide a group of selected frames and a text description accompanying them, allowing a user to perform a quick exploration of large unlabeled video databases.
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NASA Astrophysics Data System (ADS)
Wang, Y. S.; Shen, G. Q.; Xing, Y. F.
2014-03-01
Based on the artificial neural network (ANN) technique, an objective sound quality evaluation (SQE) model for synthesis annoyance of vehicle interior noises is presented in this paper. According to the standard named GB/T18697, firstly, the interior noises under different working conditions of a sample vehicle are measured and saved in a noise database. Some mathematical models for loudness, sharpness and roughness of the measured vehicle noises are established and performed by Matlab programming. Sound qualities of the vehicle interior noises are also estimated by jury tests following the anchored semantic differential (ASD) procedure. Using the objective and subjective evaluation results, furthermore, an ANN-based model for synthetical annoyance evaluation of vehicle noises, so-called ANN-SAE, is developed. Finally, the ANN-SAE model is proved by some verification tests with the leave-one-out algorithm. The results suggest that the proposed ANN-SAE model is accurate and effective and can be directly used to estimate sound quality of the vehicle interior noises, which is very helpful for vehicle acoustical designs and improvements. The ANN-SAE approach may be extended to deal with other sound-related fields for product quality evaluations in SQE engineering.
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An improved pulse coupled neural network with spectral residual for infrared pedestrian segmentation
NASA Astrophysics Data System (ADS)
He, Fuliang; Guo, Yongcai; Gao, Chao
2017-12-01
Pulse coupled neural network (PCNN) has become a significant tool for the infrared pedestrian segmentation, and a variety of relevant methods have been developed at present. However, these existing models commonly have several problems of the poor adaptability of infrared noise, the inaccuracy of segmentation results, and the fairly complex determination of parameters in current methods. This paper presents an improved PCNN model that integrates the simplified framework and spectral residual to alleviate the above problem. In this model, firstly, the weight matrix of the feeding input field is designed by the anisotropic Gaussian kernels (ANGKs), in order to suppress the infrared noise effectively. Secondly, the normalized spectral residual saliency is introduced as linking coefficient to enhance the edges and structural characteristics of segmented pedestrians remarkably. Finally, the improved dynamic threshold based on the average gray values of the iterative segmentation is employed to simplify the original PCNN model. Experiments on the IEEE OTCBVS benchmark and the infrared pedestrian image database built by our laboratory, demonstrate that the superiority of both subjective visual effects and objective quantitative evaluations in information differences and segmentation errors in our model, compared with other classic segmentation methods.
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Deep feature extraction and combination for synthetic aperture radar target classification
NASA Astrophysics Data System (ADS)
Amrani, Moussa; Jiang, Feng
2017-10-01
Feature extraction has always been a difficult problem in the classification performance of synthetic aperture radar automatic target recognition (SAR-ATR). It is very important to select discriminative features to train a classifier, which is a prerequisite. Inspired by the great success of convolutional neural network (CNN), we address the problem of SAR target classification by proposing a feature extraction method, which takes advantage of exploiting the extracted deep features from CNNs on SAR images to introduce more powerful discriminative features and robust representation ability for them. First, the pretrained VGG-S net is fine-tuned on moving and stationary target acquisition and recognition (MSTAR) public release database. Second, after a simple preprocessing is performed, the fine-tuned network is used as a fixed feature extractor to extract deep features from the processed SAR images. Third, the extracted deep features are fused by using a traditional concatenation and a discriminant correlation analysis algorithm. Finally, for target classification, K-nearest neighbors algorithm based on LogDet divergence-based metric learning triplet constraints is adopted as a baseline classifier. Experiments on MSTAR are conducted, and the classification accuracy results demonstrate that the proposed method outperforms the state-of-the-art methods.
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Inventory of Amphibians and Reptiles at Mojave National Preserve: Final Report
Persons, Trevor B.; Nowak, Erika M.
2007-01-01
As part of the National Park Service Inventory and Monitoring Program in the Mojave Network, we conducted an inventory of amphibians and reptiles at Mojave National Preserve in 2004-2005. Objectives for this inventory were to use fieldwork, museum collections, and literature review to document the occurrence of reptile and amphibian species occurring at MOJA. Our goals were to document at least 90% of the species present, provide one voucher specimen for each species identified, provide GIS-referenced distribution information for sensitive species, and provide all deliverables, including NPSpecies entries, as outlined in the Mojave Network Biological Inventory Study Plan. Methods included daytime and nighttime visual encounter surveys and nighttime road driving. Survey effort was concentrated in predetermined priority sampling areas, as well as in areas with a high potential for detecting undocumented species. We recorded 31 species during our surveys. During literature review and museum specimen database searches, we found records for seven additional species from MOJA, elevating the documented species list to 38 (two amphibians and 36 reptiles). Based on our surveys, as well as literature and museum specimen review, we estimate an overall inventory completeness of 95% for Mojave National Preserve herpetofauna; 67% for amphibians and 97% for reptiles.
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Face sketch recognition based on edge enhancement via deep learning
NASA Astrophysics Data System (ADS)
Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong
2017-11-01
In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.
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Sridhar, Vishnu B; Tian, Peifang; Dale, Anders M; Devor, Anna; Saisan, Payam A
2014-01-01
We present a database client software-Neurovascular Network Explorer 1.0 (NNE 1.0)-that uses MATLAB(®) based Graphical User Interface (GUI) for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication (Tian et al., 2010). These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization), and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches.
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The BioGRID interaction database: 2017 update
Chatr-aryamontri, Andrew; Oughtred, Rose; Boucher, Lorrie; Rust, Jennifer; Chang, Christie; Kolas, Nadine K.; O'Donnell, Lara; Oster, Sara; Theesfeld, Chandra; Sellam, Adnane; Stark, Chris; Breitkreutz, Bobby-Joe; Dolinski, Kara; Tyers, Mike
2017-01-01
The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases. PMID:27980099
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Including the Group Quarters Population in the US Synthesized Population Database
Chasteen, Bernadette M.; Wheaton, William D.; Cooley, Philip C.; Ganapathi, Laxminarayana; Wagener, Diane K.
2011-01-01
In 2005, RTI International researchers developed methods to generate synthesized population data on US households for the US Synthesized Population Database. These data are used in agent-based modeling, which simulates large-scale social networks to test how changes in the behaviors of individuals affect the overall network. Group quarters are residences where individuals live in close proximity and interact frequently. Although the Synthesized Population Database represents the population living in households, data for the nation’s group quarters residents are not easily quantified because of US Census Bureau reporting methods designed to protect individuals’ privacy. Including group quarters population data can be an important factor in agent-based modeling because the number of residents and the frequency of their interactions are variables that directly affect modeling results. Particularly with infectious disease modeling, the increased frequency of agent interaction may increase the probability of infectious disease transmission between individuals and the probability of disease outbreaks. This report reviews our methods to synthesize data on group quarters residents to match US Census Bureau data. Our goal in developing the Group Quarters Population Database was to enable its use with RTI’s US Synthesized Population Database in the Modeling of Infectious Diseases Agent Study. PMID:21841972
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The establishment and use of the point source catalog database of the 2MASS near infrared survey
NASA Astrophysics Data System (ADS)
Gao, Y. F.; Shan, H. G.; Cheng, D.
2003-02-01
The 2MASS near infrared survey project is introduced briefly. The 2MASS point sources catalog (2MASS PSC) database and the network query system are established by using the PHP Hypertext Preprocessor and MySQL database server. By using the system, one can not only query information of sources listed in the catalog, but also draw the plots related. Moreover, after the 2MASS data are diagnosed , some research fields which can be benefited from this database are suggested.
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Franke, Lude; Bakel, Harm van; Fokkens, Like; de Jong, Edwin D.; Egmont-Petersen, Michael; Wijmenga, Cisca
2006-01-01
Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray coexpressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown. PMID:16685651
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Parente, Eugenio; Cocolin, Luca; De Filippis, Francesca; Zotta, Teresa; Ferrocino, Ilario; O'Sullivan, Orla; Neviani, Erasmo; De Angelis, Maria; Cotter, Paul D; Ercolini, Danilo
2016-02-16
Amplicon targeted high-throughput sequencing has become a popular tool for the culture-independent analysis of microbial communities. Although the data obtained with this approach are portable and the number of sequences available in public databases is increasing, no tool has been developed yet for the analysis and presentation of data obtained in different studies. This work describes an approach for the development of a database for the rapid exploration and analysis of data on food microbial communities. Data from seventeen studies investigating the structure of bacterial communities in dairy, meat, sourdough and fermented vegetable products, obtained by 16S rRNA gene targeted high-throughput sequencing, were collated and analysed using Gephi, a network analysis software. The resulting database, which we named FoodMicrobionet, was used to analyse nodes and network properties and to build an interactive web-based visualisation. The latter allows the visual exploration of the relationships between Operational Taxonomic Units (OTUs) and samples and the identification of core- and sample-specific bacterial communities. It also provides additional search tools and hyperlinks for the rapid selection of food groups and OTUs and for rapid access to external resources (NCBI taxonomy, digital versions of the original articles). Microbial interaction network analysis was carried out using CoNet on datasets extracted from FoodMicrobionet: the complexity of interaction networks was much lower than that found for other bacterial communities (human microbiome, soil and other environments). This may reflect both a bias in the dataset (which was dominated by fermented foods and starter cultures) and the lower complexity of food bacterial communities. Although some technical challenges exist, and are discussed here, the net result is a valuable tool for the exploration of food bacterial communities by the scientific community and food industry. Copyright © 2015. Published by Elsevier B.V.