An integrative model for in-silico clinical-genomics discovery science.

PubMed

Lussier, Yves A; Sarkar, Indra Nell; Cantor, Michael

2002-01-01

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

Network-based approaches to climate knowledge discovery

NASA Astrophysics Data System (ADS)

Budich, Reinhard; Nyberg, Per; Weigel, Tobias

2011-11-01

Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

DataHub: Knowledge-based data management for data discovery

NASA Astrophysics Data System (ADS)

Handley, Thomas H.; Li, Y. Philip

1993-08-01

Currently available database technology is largely designed for business data-processing applications, and seems inadequate for scientific applications. The research described in this paper, the DataHub, will address the issues associated with this shortfall in technology utilization and development. The DataHub development is addressing the key issues in scientific data management of scientific database models and resource sharing in a geographically distributed, multi-disciplinary, science research environment. Thus, the DataHub will be a server between the data suppliers and data consumers to facilitate data exchanges, to assist science data analysis, and to provide as systematic approach for science data management. More specifically, the DataHub's objectives are to provide support for (1) exploratory data analysis (i.e., data driven analysis); (2) data transformations; (3) data semantics capture and usage; analysis-related knowledge capture and usage; and (5) data discovery, ingestion, and extraction. Applying technologies that vary from deductive databases, semantic data models, data discovery, knowledge representation and inferencing, exploratory data analysis techniques and modern man-machine interfaces, DataHub will provide a prototype, integrated environement to support research scientists' needs in multiple disciplines (i.e. oceanography, geology, and atmospheric) while addressing the more general science data management issues. Additionally, the DataHub will provide data management services to exploratory data analysis applications such as LinkWinds and NCSA's XIMAGE.

Virtual Observatories, Data Mining, and Astroinformatics

NASA Astrophysics Data System (ADS)

Borne, Kirk

The historical, current, and future trends in knowledge discovery from data in astronomy are presented here. The story begins with a brief history of data gathering and data organization. A description of the development ofnew information science technologies for astronomical discovery is then presented. Among these are e-Science and the virtual observatory, with its data discovery, access, display, and integration protocols; astroinformatics and data mining for exploratory data analysis, information extraction, and knowledge discovery from distributed data collections; new sky surveys' databases, including rich multivariate observational parameter sets for large numbers of objects; and the emerging discipline of data-oriented astronomical research, called astroinformatics. Astroinformatics is described as the fourth paradigm of astronomical research, following the three traditional research methodologies: observation, theory, and computation/modeling. Astroinformatics research areas include machine learning, data mining, visualization, statistics, semantic science, and scientific data management.Each of these areas is now an active research discipline, with significantscience-enabling applications in astronomy. Research challenges and sample research scenarios are presented in these areas, in addition to sample algorithms for data-oriented research. These information science technologies enable scientific knowledge discovery from the increasingly large and complex data collections in astronomy. The education and training of the modern astronomy student must consequently include skill development in these areas, whose practitioners have traditionally been limited to applied mathematicians, computer scientists, and statisticians. Modern astronomical researchers must cross these traditional discipline boundaries, thereby borrowing the best of breed methodologies from multiple disciplines. In the era of large sky surveys and numerous large telescopes, the potential for astronomical discovery is equally large, and so the data-oriented research methods, algorithms, and techniques that are presented here will enable the greatest discovery potential from the ever-growing data and information resources in astronomy.

Roles and applications of biomedical ontologies in experimental animal science.

PubMed

Masuya, Hiroshi

2012-01-01

A huge amount of experimental data from past studies has played a vital role in the development of new knowledge and technologies in biomedical science. The importance of computational technologies for the reuse of data, data integration, and knowledge discoveries has also increased, providing means of processing large amounts of data. In recent years, information technologies related to "ontologies" have played more significant roles in the standardization, integration, and knowledge representation of biomedical information. This review paper outlines the history of data integration in biomedical science and its recent trends in relation to the field of experimental animal science.

How does non-formal marine education affect student attitude and knowledge? A case study using SCDNR's Discovery program

NASA Astrophysics Data System (ADS)

McGovern, Mary Francis

Non-formal environmental education provides students the opportunity to learn in ways that would not be possible in a traditional classroom setting. Outdoor learning allows students to make connections to their environment and helps to foster an appreciation for nature. This type of education can be interdisciplinary---students not only develop skills in science, but also in mathematics, social studies, technology, and critical thinking. This case study focuses on a non-formal marine education program, the South Carolina Department of Natural Resources' (SCDNR) Discovery vessel based program. The Discovery curriculum was evaluated to determine impact on student knowledge about and attitude toward the estuary. Students from two South Carolina coastal counties who attended the boat program during fall 2014 were asked to complete a brief survey before, immediately after, and two weeks following the program. The results of this study indicate that both student knowledge about and attitude significantly improved after completion of the Discovery vessel based program. Knowledge and attitude scores demonstrated a positive correlation.

The WISECARE Project and the impact of information technology on nursing knowledge.

PubMed

Sermeus, W; Hoy, D; Jodrell, N; Hyslop, A; Gypen, T; Kinnunen, J; Mantas, J; Delesie, L; Tansley, J; Hofdijk, J

1997-01-01

The European Union retained the WISECARE project "Work flow Information Systems for European nursing CARE" for funding. The project focuses on the use of telematics technology for clinical and resource management in oncology care in hospitals. This paper outlines the impact of introducing this kind of advanced nursing informatics application on the management of nursing knowledge. Three shift in knowledge management that will get high attention in WISECARE, are identified. The first is the shift from knowledge dissemination to knowledge sharing. The second is the shift from individual knowledge to organisational knowledge. The third is the shift from deductive, prescriptive knowledge as seen in guidelines, protocols to more inductive, experience based knowledge. The paper emphasizes that the real impact of information technology is not in the automation of existing processes but on the discovery of new ways of organisation and living.

32 CFR 34.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... increasing knowledge or understanding in science and engineering. Applied research is defined as efforts that attempt to determine and exploit the potential of scientific discoveries or improvements in technology...

Streamlining the Discovery, Evaluation, and Integration of Data, Models, and Decision Support Systems: a Big Picture View

EPA Science Inventory

21st century environmental problems are wicked and require holistic systems thinking and solutions that integrate social and economic knowledge with knowledge of the environment. Computer-based technologies are fundamental to our ability to research and understand the relevant sy...

Globalization of Knowledge Discovery and Information Retrieval in Teaching and Learning

ERIC Educational Resources Information Center

Zaidel, Mark; Guerrero, Osiris

2008-01-01

Developments in communication and information technologies in the last decade have had a significant impact on instructional and learning activities. For many students and educators, the Internet became the significant medium for sharing instruction, learning and communication. Access to knowledge beyond boundaries and cultures has an impact on…

Understanding University Technology Transfer

ERIC Educational Resources Information Center

Association of American Universities, 2011

2011-01-01

Federal government agencies provide about $33 billion a year to universities to conduct scientific research. That continuing investment expands human knowledge and helps educate the next generation of science and technology leaders. New discoveries from university research also form the basis for many new products and processes that benefit the…

Discovering and Articulating What Is Not yet Known: Using Action Learning and Grounded Theory as a Knowledge Management Strategy

ERIC Educational Resources Information Center

Pauleen, David J.; Corbitt, Brian; Yoong, Pak

2007-01-01

Purpose: To provide a conceptual model for the discovery and articulation of emergent organizational knowledge, particularly knowledge that develops when people work with new technologies. Design/methodology/approach: The model is based on two widely accepted research methods--action learning and grounded theory--and is illustrated using a case…

Marshall Space Flight Center Research and Technology Report 2016

NASA Technical Reports Server (NTRS)

Tinker, M. L.; Abney, M. B. (Compiler); Reynolds, D. W. (Compiler); Morris, H. C. (Compiler)

2017-01-01

Marshall Space Flight Center is essential to human space exploration and our work is a catalyst for ongoing technological development. As we address the challenges facing human deep space exploration, we advance new technologies and applications here on Earth, expand scientific knowledge and discovery, create new economic opportunities, and continue to lead global space exploration.

At the Crossroads: Portrait of an Undergraduate Composition Teacher Whose Heuristics Were Transformed by Computer-Technology

ERIC Educational Resources Information Center

Grover, Susan Hendricks

2010-01-01

Heuristics are deeply-held, tacit knowledge structures connected to our feelings. A heuristic study explores a phenomenon crucial to the researcher's self-discovery (Moustakas, 1990). Like me, many undergraduate composition instructors feel both fear and hope at the crossroads of composition and technology. Technology and composition shape one…

Discovering Drugs with DNA-Encoded Library Technology: From Concept to Clinic with an Inhibitor of Soluble Epoxide Hydrolase.

PubMed

Belyanskaya, Svetlana L; Ding, Yun; Callahan, James F; Lazaar, Aili L; Israel, David I

2017-05-04

DNA-encoded chemical library technology was developed with the vision of its becoming a transformational platform for drug discovery. The hope was that a new paradigm for the discovery of low-molecular-weight drugs would be enabled by combining the vast molecular diversity achievable with combinatorial chemistry, the information-encoding attributes of DNA, the power of molecular biology, and a streamlined selection-based discovery process. Here, we describe the discovery and early clinical development of GSK2256294, an inhibitor of soluble epoxide hydrolase (sEH, EPHX2), by using encoded-library technology (ELT). GSK2256294 is an orally bioavailable, potent and selective inhibitor of sEH that has a long half life and produced no serious adverse events in a first-time-in-human clinical study. To our knowledge, GSK2256294 is the first molecule discovered from this technology to enter human clinical testing and represents a realization of the vision that DNA-encoded chemical library technology can efficiently yield molecules with favorable properties that can be readily progressed into high-quality drugs. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Federation of Earth Science Information Partners ESIP

NASA Technical Reports Server (NTRS)

Tilmes, Curt

2013-01-01

A broad-based, distributed community of science, data and information technology practitioners. With over 150 member organizations, the ESIP Federation brings together public, academic, commercial, and nongovernmental organizations to share knowledge, expertise, technology and best practices to improve opportunities for increasing access, discovery, integration and usability of Earth science data.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.

2013-01-01

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges thatmore » have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.« less

Integrating semantic web technologies and geospatial catalog services for geospatial information discovery and processing in cyberinfrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Peng; Gong, Jianya; Di, Liping

Abstract A geospatial catalogue service provides a network-based meta-information repository and interface for advertising and discovering shared geospatial data and services. Descriptive information (i.e., metadata) for geospatial data and services is structured and organized in catalogue services. The approaches currently available for searching and using that information are often inadequate. Semantic Web technologies show promise for better discovery methods by exploiting the underlying semantics. Such development needs special attention from the Cyberinfrastructure perspective, so that the traditional focus on discovery of and access to geospatial data can be expanded to support the increased demand for processing of geospatial information andmore » discovery of knowledge. Semantic descriptions for geospatial data, services, and geoprocessing service chains are structured, organized, and registered through extending elements in the ebXML Registry Information Model (ebRIM) of a geospatial catalogue service, which follows the interface specifications of the Open Geospatial Consortium (OGC) Catalogue Services for the Web (CSW). The process models for geoprocessing service chains, as a type of geospatial knowledge, are captured, registered, and discoverable. Semantics-enhanced discovery for geospatial data, services/service chains, and process models is described. Semantic search middleware that can support virtual data product materialization is developed for the geospatial catalogue service. The creation of such a semantics-enhanced geospatial catalogue service is important in meeting the demands for geospatial information discovery and analysis in Cyberinfrastructure.« less

State of the Art in Tumor Antigen and Biomarker Discovery

PubMed Central

Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

2011-01-01

Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology. PMID:24212823

Accomplishments of Long-Term Research and Development

DOE R&D Accomplishments Database

Jordy, George Y.

1988-07-01

Technological breakthroughs cannot be penciled on the calendar in advance. The rate of new technological discovery, while highly uncertain, depends on a base of knowledge acquired earlier. In the economic environment of 1980, progress in basic research, which builds the technology base that will underpin future energy development by Government and industry, was being slowed as cost increases due to inflation grew faster than funding increase.

100 years of elementary particles [Beam Line, vol. 27, issue 1, Spring 1997

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pais, Abraham; Weinberg, Steven; Quigg, Chris

1997-04-01

This issue of Beam Line commemorates the 100th anniversary of the April 30, 1897 report of the discovery of the electron by J.J. Thomson and the ensuing discovery of other subatomic particles. In the first three articles, theorists Abraham Pais, Steven Weinberg, and Chris Quigg provide their perspectives on the discoveries of elementary particles as well as the implications and future directions resulting from these discoveries. In the following three articles, Michael Riordan, Wolfgang Panofsky, and Virginia Trimble apply our knowledge about elementary particles to high-energy research, electronics technology, and understanding the origin and evolution of our Universe.

100 years of Elementary Particles [Beam Line, vol. 27, issue 1, Spring 1997

DOE R&D Accomplishments Database

Pais, Abraham; Weinberg, Steven; Quigg, Chris; Riordan, Michael; Panofsky, Wolfgang K. H.; Trimble, Virginia

1997-04-01

This issue of Beam Line commemorates the 100th anniversary of the April 30, 1897 report of the discovery of the electron by J.J. Thomson and the ensuing discovery of other subatomic particles. In the first three articles, theorists Abraham Pais, Steven Weinberg, and Chris Quigg provide their perspectives on the discoveries of elementary particles as well as the implications and future directions resulting from these discoveries. In the following three articles, Michael Riordan, Wolfgang Panofsky, and Virginia Trimble apply our knowledge about elementary particles to high-energy research, electronics technology, and understanding the origin and evolution of our Universe.

48 CFR 31.205-18 - Independent research and development and bid and proposal costs.

Code of Federal Regulations, 2012 CFR

2012-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... systematic use, under whatever name, of scientific and technical knowledge in the design, development, test...

48 CFR 31.205-18 - Independent research and development and bid and proposal costs.

Code of Federal Regulations, 2013 CFR

2013-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... systematic use, under whatever name, of scientific and technical knowledge in the design, development, test...

48 CFR 31.205-18 - Independent research and development and bid and proposal costs.

Code of Federal Regulations, 2011 CFR

2011-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... systematic use, under whatever name, of scientific and technical knowledge in the design, development, test...

48 CFR 31.205-18 - Independent research and development and bid and proposal costs.

Code of Federal Regulations, 2014 CFR

2014-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... systematic use, under whatever name, of scientific and technical knowledge in the design, development, test...

Novel drug discovery for Chagas disease.

PubMed

Moraes, Carolina B; Franco, Caio H

2016-01-01

Chagas disease is a chronic infection associated with long-term morbidity. Increased funding and advocacy for drug discovery for neglected diseases have prompted the introduction of several important technological advances, and Chagas disease is among the neglected conditions that has mostly benefited from technological developments. A number of screening campaigns, and the development of new and improved in vitro and in vivo assays, has led to advances in the field of drug discovery. This review highlights the major advances in Chagas disease drug screening, and how these are being used not only to discover novel chemical entities and drug candidates, but also increase our knowledge about the disease and the parasite. Different methodologies used for compound screening and prioritization are discussed, as well as novel techniques for the investigation of these targets. The molecular mechanism of action is also discussed. Technological advances have been executed with scientific rigour for the development of new in vitro cell-based assays and in vivo animal models, to bring about novel and better drugs for Chagas disease, as well as to increase our understanding of what are the necessary properties for a compound to be successful in the clinic. The gained knowledge, combined with new exciting approaches toward target deconvolution, will help identifying new targets for Chagas disease chemotherapy in the future.

Knowledge Discovery/A Collaborative Approach, an Innovative Solution

NASA Technical Reports Server (NTRS)

Fitts, Mary A.

2009-01-01

Collaboration between Medical Informatics and Healthcare Systems (MIHCS) at NASA/Johnson Space Center (JSC) and the Texas Medical Center (TMC) Library was established to investigate technologies for facilitating knowledge discovery across multiple life sciences research disciplines in multiple repositories. After reviewing 14 potential Enterprise Search System (ESS) solutions, Collexis was determined to best meet the expressed needs. A three month pilot evaluation of Collexis produced positive reports from multiple scientists across 12 research disciplines. The joint venture and a pilot-phased approach achieved the desired results without the high cost of purchasing software, hardware or additional resources to conduct the task. Medical research is highly compartmentalized by discipline, e.g. cardiology, immunology, neurology. The medical research community at large, as well as at JSC, recognizes the need for cross-referencing relevant information to generate best evidence. Cross-discipline collaboration at JSC is specifically required to close knowledge gaps affecting space exploration. To facilitate knowledge discovery across these communities, MIHCS combined expertise with the TMC library and found Collexis to best fit the needs of our researchers including:

Closed-Loop Multitarget Optimization for Discovery of New Emulsion Polymerization Recipes

PubMed Central

2015-01-01

Self-optimization of chemical reactions enables faster optimization of reaction conditions or discovery of molecules with required target properties. The technology of self-optimization has been expanded to discovery of new process recipes for manufacture of complex functional products. A new machine-learning algorithm, specifically designed for multiobjective target optimization with an explicit aim to minimize the number of “expensive” experiments, guides the discovery process. This “black-box” approach assumes no a priori knowledge of chemical system and hence particularly suited to rapid development of processes to manufacture specialist low-volume, high-value products. The approach was demonstrated in discovery of process recipes for a semibatch emulsion copolymerization, targeting a specific particle size and full conversion. PMID:26435638

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

Cosmic Discovery

NASA Astrophysics Data System (ADS)

Harwit, Martin

1984-04-01

In the remarkable opening section of this book, a well-known Cornell astronomer gives precise thumbnail histories of the 43 basic cosmic discoveries - stars, planets, novae, pulsars, comets, gamma-ray bursts, and the like - that form the core of our knowledge of the universe. Many of them, he points out, were made accidentally and outside the mainstream of astronomical research and funding. This observation leads him to speculate on how many more major phenomena there might be and how they might be most effectively sought out in afield now dominated by large instruments and complex investigative modes and observational conditions. The book also examines discovery in terms of its political, financial, and sociological context - the role of new technologies and of industry and the military in revealing new knowledge; and methods of funding, of peer review, and of allotting time on our largest telescopes. It concludes with specific recommendations for organizing astronomy in ways that will best lead to the discovery of the many - at least sixty - phenomena that Harwit estimates are still waiting to be found.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

Succinic acid: technology development and commercialization

USDA-ARS?s Scientific Manuscript database

Succinic acid is a precursor of many important, large volume industrial chemicals and consumer products. It was common knowledge that many ruminant microorganisms accumulated succinic acid under anaerobic conditions. However, it was not until the discovery of Anaerobiospirillum succiniciproducens at...

New materials: Fountainhead for new technologies and new science

NASA Technical Reports Server (NTRS)

Rustum, Roy

1993-01-01

The role of materials as the benchmark technologies which give epochs of human history their names continues into the present. The discovery of new materials has nearly always been the source of new materials science, and frequently of new technologies. This paper analyzes the actual processes by which new materials are synthesized, i.e. whether driven by serendipitous observations, new knowledge is pulled by the market, or integrated into a technological thrust. This analysis focuses on modern ceramic materials discoveries, since World War 2 and uses 45 years experience in materials synthesis in the author's own laboratory as case studies. A dozen different families of materials or processes are involved: hydrothermal reactions; sol-gel processing; clays and zeolites; electroceramics; zero expansion ceramics; diamond films; and radioactive waste host phases. Nanocomposite concepts introduced by the author a decade ago offer an entire, large, new class of materials which will dominate synthesis for the next period. The future of materials research for the next 25 years cannot be extrapolated from the past 25 years. We are near the asymptote for materials utilization in most metals. Likewise we are approaching saturation in improvement of many useful properties. Justifying much further 'basic' R/D for incremental improvement in civilian-oriented industries will not be easy. In materials synthesis, the near-term future is sure to emphasize not new phases, but tailored micro- and nanocomposites for chemical, electrical, optical, and magnetic uses. Unexpected new discoveries such as the Lanxide process may offer rarer chances for step function advances. The new structure of knowledge management will rely less on local research than on integration of worldwide inputs. Better scientific and technological opportunities will lie in designing knowledge intensive materials to meet the new environmental and conservation goals, and the human needs of the very large numbers at the bottom of the socio-economic structures of the world.

The interface of genomic technologies and nursing.

PubMed

Loescher, Lois J; Merkle, Carrie J

2005-01-01

(a) to summarize views of the interface of technology, genomic technology, and nursing; (b) provide an overview of current and emerging genomic technologies; (c) present clinical exemplars of uses of genomic technology in two disease conditions; and (d) list genomic-focused nursing research on genomic technologies. A discussion of genomic technology in the context of nurses' views of technology, the importance of genomic technology for nurses, linking the central dogma of molecular biology to state-of-the-art tests and assays, and nurses' current use of technologies. Human genome discoveries will continue to be an integral part of disease prevention, diagnosis, treatment, and management. These discoveries also have the potential for being integrated into nursing science. Genomic technologies are becoming a driving force in patient management, so that nurses will be unable to provide quality care without knowledge of the types of genomic technologies, the rationale for their use, and the possible sequelae that can result from genetic diagnosis or treatment. Many nurses already are using genomic technologies to conduct genomic-focused nursing research. The biobehavioral nature of much of this research further indicates the important contributions of nurses in genomics.

Causality discovery technology

NASA Astrophysics Data System (ADS)

Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

2012-11-01

Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

Introduction to biological complexity as a missing link in drug discovery.

PubMed

Gintant, Gary A; George, Christopher H

2018-06-06

Despite a burgeoning knowledge of the intricacies and mechanisms responsible for human disease, technological advances in medicinal chemistry, and more efficient assays used for drug screening, it remains difficult to discover novel and effective pharmacologic therapies. Areas covered: By reference to the primary literature and concepts emerging from academic and industrial drug screening landscapes, the authors propose that this disconnect arises from the inability to scale and integrate responses from simpler model systems to outcomes from more complex and human-based biological systems. Expert opinion: Further collaborative efforts combining target-based and phenotypic-based screening along with systems-based pharmacology and informatics will be necessary to harness the technological breakthroughs of today to derive the novel drug candidates of tomorrow. New questions must be asked of enabling technologies-while recognizing inherent limitations-in a way that moves drug development forward. Attempts to integrate mechanistic and observational information acquired across multiple scales frequently expose the gap between our knowledge and our understanding as the level of complexity increases. We hope that the thoughts and actionable items highlighted will help to inform the directed evolution of the drug discovery process.

A bioinformatics knowledge discovery in text application for grid computing

PubMed Central

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-01-01

Background A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. Methods The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. Results A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. Conclusion In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities. PMID:19534749

A bioinformatics knowledge discovery in text application for grid computing.

PubMed

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-06-16

A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities.

Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

ERIC Educational Resources Information Center

Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

2000-01-01

These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

48 CFR 35.001 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... aim is the design, development, or testing of specific items or services to be considered for sale..., means the systematic use of scientific and technical knowledge in the design, development, testing, or...

48 CFR 35.001 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... aim is the design, development, or testing of specific items or services to be considered for sale..., means the systematic use of scientific and technical knowledge in the design, development, testing, or...

48 CFR 35.001 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... aim is the design, development, or testing of specific items or services to be considered for sale..., means the systematic use of scientific and technical knowledge in the design, development, testing, or...

48 CFR 35.001 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... determine and exploit the potential of scientific discoveries or improvements in technology, materials... aim is the design, development, or testing of specific items or services to be considered for sale..., means the systematic use of scientific and technical knowledge in the design, development, testing, or...

Mission of the University in Science and Technology Discoveries and Applications of the Universal Knowledge within the Various Socio-economics Systems.

ERIC Educational Resources Information Center

Chiang, Gustavo

The mission of the university is fundamentally to interpret, create, and transmit culture and science. The historical development and the needs of the community condition and orientate the university in its task. A rational application of science and technology will contribute to the resolution of many of today's serious problems. A direct…

NCI Technology Transfer Center | TTC

Cancer.gov

The National Cancer Institute’s Technology Transfer Center (TTC) facilitates partnerships between the NIH research laboratories and external partners. With specialized teams, TTC guides the interactions of our partners from the point of discovery to patenting, from invention development to licensing. We play a key role in helping to accelerate development of cutting-edge research by connecting our partners to NIH’s world-class researchers, facilities, and knowledge.

Early Detection of Cancer by Affinity Mass Spectrometry-Set Aside funds — EDRN Public Portal

Cancer.gov

A.   RATIONALE The recent introduction of multiple reaction monitoring capabilities offers unprecedented capability to the research arsenal available to protein based biomarker discovery. Specific to the discovery process this technology offers an ability to monitor specific protein changes in concentration and/or post-translational modification. The ability to accurately confirm specific biomarkers in a sensitive and reproducible manner is critical to the confirmation and pre-validation process. We are proposing two collaborative studies that promise to develop Multiple Reaction Monitoring (MRM) work flows for the biomarker scientific community and specifically for EDRN. B.   GOALS The overall goal for this proposal is the identification of protein biomarkers that can be associated with prostate cancer detection. The underlying goal is the application of a novel technological approach aided by MRM toward biomarker discovery. An additional goal will be the dissemination of knowledge gained from these studies EDRN wide.

Scientific Knowledge and Technology, Animal Experimentation, and Pharmaceutical Development.

PubMed

Kinter, Lewis B; DeGeorge, Joseph J

2016-12-01

Human discovery of pharmacologically active substances is arguably the oldest of the biomedical sciences with origins >3500 years ago. Since ancient times, four major transformations have dramatically impacted pharmaceutical development, each driven by advances in scientific knowledge, technology, and/or regulation: (1) anesthesia, analgesia, and antisepsis; (2) medicinal chemistry; (3) regulatory toxicology; and (4) targeted drug discovery. Animal experimentation in pharmaceutical development is a modern phenomenon dating from the 20th century and enabling several of the four transformations. While each transformation resulted in more effective and/or safer pharmaceuticals, overall attrition, cycle time, cost, numbers of animals used, and low probability of success for new products remain concerns, and pharmaceutical development remains a very high risk business proposition. In this manuscript we review pharmaceutical development since ancient times, describe its coevolution with animal experimentation, and attempt to predict the characteristics of future transformations. © The Author 2016. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Knowledge Discovery and Data Mining in Iran's Climatic Researches

NASA Astrophysics Data System (ADS)

Karimi, Mostafa

2013-04-01

Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for internal climate studies in data mining and knowledge discovery techniques are used. However, it is necessary to use the KDD Approach and DM techniques in the climatic studies, specific interpreter of climate modeling result.

Early patterns of commercial activity in graphene

NASA Astrophysics Data System (ADS)

Shapira, Philip; Youtie, Jan; Arora, Sanjay

2012-03-01

Graphene, a novel nanomaterial consisting of a single layer of carbon atoms, has attracted significant attention due to its distinctive properties, including great strength, electrical and thermal conductivity, lightness, and potential benefits for diverse applications. The commercialization of scientific discoveries such as graphene is inherently uncertain, with the lag time between the scientific development of a new technology and its adoption by corporate actors revealing the extent to which firms are able to absorb knowledge and engage in learning to implement applications based on the new technology. From this perspective, we test for the existence of three different corporate learning and activity patterns: (1) a linear process where patenting follows scientific discovery; (2) a double-boom phenomenon where corporate (patenting) activity is first concentrated in technological improvements and then followed by a period of technology productization; and (3) a concurrent model where scientific discovery in publications occurs in parallel with patenting. By analyzing corporate publication and patent activity across country and application lines, we find that, while graphene as a whole is experiencing concurrent scientific development and patenting growth, country- and application-specific trends offer some evidence of the linear and double-boom models.

What NASA Has for You

ERIC Educational Resources Information Center

Pinelli, Thomas E.

1974-01-01

Instructors who want to keep up-to-date on new processes and technology can obtain inexpensive materials from NASA. Seven types are describeed, and instructions for obtaining them provided, to help industrial arts, vocational-industrial, and technical education teachers bridge the gap between discovery and use of new knowledge. (AJ)

Database systems for knowledge-based discovery.

PubMed

Jagarlapudi, Sarma A R P; Kishan, K V Radha

2009-01-01

Several database systems have been developed to provide valuable information from the bench chemist to biologist, medical practitioner to pharmaceutical scientist in a structured format. The advent of information technology and computational power enhanced the ability to access large volumes of data in the form of a database where one could do compilation, searching, archiving, analysis, and finally knowledge derivation. Although, data are of variable types the tools used for database creation, searching and retrieval are similar. GVK BIO has been developing databases from publicly available scientific literature in specific areas like medicinal chemistry, clinical research, and mechanism-based toxicity so that the structured databases containing vast data could be used in several areas of research. These databases were classified as reference centric or compound centric depending on the way the database systems were designed. Integration of these databases with knowledge derivation tools would enhance the value of these systems toward better drug design and discovery.

New technologies for application to veterinary therapeutics.

PubMed

Riviere, Jim E

2010-01-01

The purpose of this contribution is to review new technologies and make an educated prediction as to how they will impact veterinary pharmacology over the coming decades. By examining past developments, it becomes evident that change is incremental and predictable unless either a transforming discovery or a change in societal behaviour occurs. In the last century, both discoveries and behaviours have dramatically changed medicine, pharmacology and therapeutics. In this chapter, the potential effects of six transforming technologies on veterinary therapeutics are examined: continued advances in computer technology, microfluidics, nanotechnology, high-throughput screening, control and targeted drug delivery and pharmacogenomics. These should lead to the more efficacious and safer use of existing medicants, and the development of novel drugs across most therapeutic classes through increases in our knowledge base, as well as more efficient drug development. Although this growth in technology portends major advances over the next few decades, economic and regulatory constraints must still be overcome for these new drugs or therapeutic approaches to become common practise.

Modeling technology innovation: how science, engineering, and industry methods can combine to generate beneficial socioeconomic impacts.

PubMed

Stone, Vathsala I; Lane, Joseph P

2012-05-16

Government-sponsored science, technology, and innovation (STI) programs support the socioeconomic aspects of public policies, in addition to expanding the knowledge base. For example, beneficial healthcare services and devices are expected to result from investments in research and development (R&D) programs, which assume a causal link to commercial innovation. Such programs are increasingly held accountable for evidence of impact-that is, innovative goods and services resulting from R&D activity. However, the absence of comprehensive models and metrics skews evidence gathering toward bibliometrics about research outputs (published discoveries), with less focus on transfer metrics about development outputs (patented prototypes) and almost none on econometrics related to production outputs (commercial innovations). This disparity is particularly problematic for the expressed intent of such programs, as most measurable socioeconomic benefits result from the last category of outputs. This paper proposes a conceptual framework integrating all three knowledge-generating methods into a logic model, useful for planning, obtaining, and measuring the intended beneficial impacts through the implementation of knowledge in practice. Additionally, the integration of the Context-Input-Process-Product (CIPP) model of evaluation proactively builds relevance into STI policies and programs while sustaining rigor. The resulting logic model framework explicitly traces the progress of knowledge from inputs, following it through the three knowledge-generating processes and their respective knowledge outputs (discovery, invention, innovation), as it generates the intended socio-beneficial impacts. It is a hybrid model for generating technology-based innovations, where best practices in new product development merge with a widely accepted knowledge-translation approach. Given the emphasis on evidence-based practice in the medical and health fields and "bench to bedside" expectations for knowledge transfer, sponsors and grantees alike should find the model useful for planning, implementing, and evaluating innovation processes. High-cost/high-risk industries like healthcare require the market deployment of technology-based innovations to improve domestic society in a global economy. An appropriate balance of relevance and rigor in research, development, and production is crucial to optimize the return on public investment in such programs. The technology-innovation process needs a comprehensive operational model to effectively allocate public funds and thereby deliberately and systematically accomplish socioeconomic benefits.

Modeling technology innovation: How science, engineering, and industry methods can combine to generate beneficial socioeconomic impacts

PubMed Central

2012-01-01

Background Government-sponsored science, technology, and innovation (STI) programs support the socioeconomic aspects of public policies, in addition to expanding the knowledge base. For example, beneficial healthcare services and devices are expected to result from investments in research and development (R&D) programs, which assume a causal link to commercial innovation. Such programs are increasingly held accountable for evidence of impact—that is, innovative goods and services resulting from R&D activity. However, the absence of comprehensive models and metrics skews evidence gathering toward bibliometrics about research outputs (published discoveries), with less focus on transfer metrics about development outputs (patented prototypes) and almost none on econometrics related to production outputs (commercial innovations). This disparity is particularly problematic for the expressed intent of such programs, as most measurable socioeconomic benefits result from the last category of outputs. Methods This paper proposes a conceptual framework integrating all three knowledge-generating methods into a logic model, useful for planning, obtaining, and measuring the intended beneficial impacts through the implementation of knowledge in practice. Additionally, the integration of the Context-Input-Process-Product (CIPP) model of evaluation proactively builds relevance into STI policies and programs while sustaining rigor. Results The resulting logic model framework explicitly traces the progress of knowledge from inputs, following it through the three knowledge-generating processes and their respective knowledge outputs (discovery, invention, innovation), as it generates the intended socio-beneficial impacts. It is a hybrid model for generating technology-based innovations, where best practices in new product development merge with a widely accepted knowledge-translation approach. Given the emphasis on evidence-based practice in the medical and health fields and “bench to bedside” expectations for knowledge transfer, sponsors and grantees alike should find the model useful for planning, implementing, and evaluating innovation processes. Conclusions High-cost/high-risk industries like healthcare require the market deployment of technology-based innovations to improve domestic society in a global economy. An appropriate balance of relevance and rigor in research, development, and production is crucial to optimize the return on public investment in such programs. The technology-innovation process needs a comprehensive operational model to effectively allocate public funds and thereby deliberately and systematically accomplish socioeconomic benefits. PMID:22591638

Philosophers and Technologists: Vicarious and Virtual Knowledge Constructs

ERIC Educational Resources Information Center

McNeese, Beverly D.

2007-01-01

In an age of continual technological advancement, user-friendly software, and consumer demand for the latest upgraded gadget, the ethical and moral discoveries derived from a careful reading of any fictional literature by college students is struggling in the American college classroom. Easy-access information systems, coinciding with the…

Capillary Electrophoretic Technologies for Single Cell Metabolomics

ERIC Educational Resources Information Center

Lapainis, Theodore E.

2009-01-01

Understanding the functioning of the brain is hindered by a lack of knowledge of the full complement of neurotransmitters and neuromodulatory compounds. Single cell measurements aid in the discovery of neurotransmitters used by small subsets of neurons that would be diluted below detection limits or masked by ubiquitous compounds when working with…

Molecular biology and immunology of head and neck cancer.

PubMed

Guo, Theresa; Califano, Joseph A

2015-07-01

In recent years, our knowledge and understanding of head and neck squamous cell carcinoma (HNSCC) has expanded dramatically. New high-throughput sequencing technologies have accelerated these discoveries since the first reports of whole-exome sequencing of HNSCC tumors in 2011. In addition, the discovery of human papillomavirus in relationship with oropharyngeal squamous cell carcinoma has shifted our molecular understanding of the disease. New investigation into the role of immune evasion in HNSCC has also led to potential novel therapies based on immune-specific systemic therapies. Copyright © 2015 Elsevier Inc. All rights reserved.

Ontology-guided data preparation for discovering genotype-phenotype relationships.

PubMed

Coulet, Adrien; Smaïl-Tabbone, Malika; Benlian, Pascale; Napoli, Amedeo; Devignes, Marie-Dominique

2008-04-25

Complexity and amount of post-genomic data constitute two major factors limiting the application of Knowledge Discovery in Databases (KDD) methods in life sciences. Bio-ontologies may nowadays play key roles in knowledge discovery in life science providing semantics to data and to extracted units, by taking advantage of the progress of Semantic Web technologies concerning the understanding and availability of tools for knowledge representation, extraction, and reasoning. This paper presents a method that exploits bio-ontologies for guiding data selection within the preparation step of the KDD process. We propose three scenarios in which domain knowledge and ontology elements such as subsumption, properties, class descriptions, are taken into account for data selection, before the data mining step. Each of these scenarios is illustrated within a case-study relative to the search of genotype-phenotype relationships in a familial hypercholesterolemia dataset. The guiding of data selection based on domain knowledge is analysed and shows a direct influence on the volume and significance of the data mining results. The method proposed in this paper is an efficient alternative to numerical methods for data selection based on domain knowledge. In turn, the results of this study may be reused in ontology modelling and data integration.

Advanced Computing Methods for Knowledge Discovery and Prognosis in Acoustic Emission Monitoring

ERIC Educational Resources Information Center

Mejia, Felipe

2012-01-01

Structural health monitoring (SHM) has gained significant popularity in the last decade. This growing interest, coupled with new sensing technologies, has resulted in an overwhelming amount of data in need of management and useful interpretation. Acoustic emission (AE) testing has been particularly fraught by the problem of growing data and is…

Basic Scientific and Engineering Research at U.S. Universities. AAU Data & Policy Brief. No. 1

ERIC Educational Resources Information Center

Association of American Universities, 2015

2015-01-01

"Discovery," wrote William Press in a 2013 article in "Science," "leads to technology and invention, which lead to new products, jobs, and industries." Basic, curiosity-driven research continually expands the boundaries of knowledge across fields, providing insights that enrich lives. Such research helps drive the…

Confronting the Technological Pedagogical Knowledge of Finnish Net Generation Student Teachers

ERIC Educational Resources Information Center

Valtonen, Teemu; Pontinen, Susanna; Kukkonen, Jari; Dillon, Patrick; Vaisanen, Pertti; Hacklin, Stina

2011-01-01

The research reported here is concerned with a critical examination of some of the assumptions concerning the "Net Generation" capabilities of 74 first-year student teachers in a Finnish university. There are assumptions that: (i) Net Generation students are adept at learning through discovery and thinking in a hypertext-like manner…

The OceanLink Project

NASA Astrophysics Data System (ADS)

Narock, T.; Arko, R. A.; Carbotte, S. M.; Chandler, C. L.; Cheatham, M.; Finin, T.; Hitzler, P.; Krisnadhi, A.; Raymond, L. M.; Shepherd, A.; Wiebe, P. H.

2014-12-01

A wide spectrum of maturing methods and tools, collectively characterized as the Semantic Web, is helping to vastly improve the dissemination of scientific research. Creating semantic integration requires input from both domain and cyberinfrastructure scientists. OceanLink, an NSF EarthCube Building Block, is demonstrating semantic technologies through the integration of geoscience data repositories, library holdings, conference abstracts, and funded research awards. Meeting project objectives involves applying semantic technologies to support data representation, discovery, sharing and integration. Our semantic cyberinfrastructure components include ontology design patterns, Linked Data collections, semantic provenance, and associated services to enhance data and knowledge discovery, interoperation, and integration. We discuss how these components are integrated, the continued automated and semi-automated creation of semantic metadata, and techniques we have developed to integrate ontologies, link resources, and preserve provenance and attribution.

Semantics-enabled service discovery framework in the SIMDAT pharma grid.

PubMed

Qu, Cangtao; Zimmermann, Falk; Kumpf, Kai; Kamuzinzi, Richard; Ledent, Valérie; Herzog, Robert

2008-03-01

We present the design and implementation of a semantics-enabled service discovery framework in the data Grids for process and product development using numerical simulation and knowledge discovery (SIMDAT) Pharma Grid, an industry-oriented Grid environment for integrating thousands of Grid-enabled biological data services and analysis services. The framework consists of three major components: the Web ontology language (OWL)-description logic (DL)-based biological domain ontology, OWL Web service ontology (OWL-S)-based service annotation, and semantic matchmaker based on the ontology reasoning. Built upon the framework, workflow technologies are extensively exploited in the SIMDAT to assist biologists in (semi)automatically performing in silico experiments. We present a typical usage scenario through the case study of a biological workflow: IXodus.

Rho Chi lecture. Pharmaceutical sciences in the next millennium.

PubMed

Triggle, D J

1999-02-01

Even a cursory survey of this article suggests that the pharmaceutical sciences are being rapidly transformed under the influence of both the new technologies and sciences and the economic imperatives. Of particular importance are scientific and technological advances that may greatly accelerate the critical process of discovery. The possibility of a drug discovery process built around the principles of directed diversity, self-reproduction, evolution, and self-targeting suggests a new paradigm of lead discovery, one based quite directly on the paradigms of molecular biology. Coupled with the principles of nanotechnology, we may contemplate miniature molecular machines containing directed drug factories, circulating the body and capable of self-targeting against defective cells and pathways -- the ultimate "drug delivery machine." However, science and technology are not the only factors that will transform the pharmaceutical sciences in the next century. The necessary reductions in the costs of drug discovery brought about by the rapidly increasing costs of the current drug discovery paradigms means that efforts to decrease the discovery phase and to make drug development part of drug discovery will become increasingly important. This is likely to involve increasing numbers of "alliances," as well as the creation of pharmaceutical research cells -- highly mobile and entrepreneurial groups within or outside of a pharmaceutical company that are formed to carry out specific discovery processes. Some of these will be in the biotechnology industry, but an increasing number will be in universities. The linear process from basic science to applied technology that has been the Western model since Vannevar Bush's Science: The Endless Frontier has probably never been particularly linear and, in any event, is likely to be rapidly supplanted by models where science, scientific development, and technology are more intimately linked. The pharmaceutical sciences have always been an example of use-directed basic research, but the relationships between the pharmaceutical industry, small and large, and the universities seems likely to become increasingly developed in the next century. This may serve as a significant catalyst for the continued transformation of universities into the "knowledge factories" of the 21st century. Regardless, we may expect to see major changes in the research organizational structure in the pharmaceutical sciences even as pharmaceutical companies enjoy record prosperity. And this is in anticipation of tough times to come.

On the Limitations of Biological Knowledge

PubMed Central

Dougherty, Edward R; Shmulevich, Ilya

2012-01-01

Scientific knowledge is grounded in a particular epistemology and, owing to the requirements of that epistemology, possesses limitations. Some limitations are intrinsic, in the sense that they depend inherently on the nature of scientific knowledge; others are contingent, depending on the present state of knowledge, including technology. Understanding limitations facilitates scientific research because one can then recognize when one is confronted by a limitation, as opposed to simply being unable to solve a problem within the existing bounds of possibility. In the hope that the role of limiting factors can be brought more clearly into focus and discussed, we consider several sources of limitation as they apply to biological knowledge: mathematical complexity, experimental constraints, validation, knowledge discovery, and human intellectual capacity. PMID:23633917

Integrating genetics and genomics into nursing curricula: you can do it too!

PubMed

Daack-Hirsch, Sandra; Jackson, Barbara; Belchez, Chito A; Elder, Betty; Hurley, Roxanne; Kerr, Peg; Nissen, Mary Kay

2013-12-01

Rapid advances in knowledge and technology related to genomics cross health care disciplines and touch almost every aspect of patient care. The ability to sequence a genome holds the promise that health care can be personalized. Health care professionals are faced with a gap in the ability to use the rapidly expanding technology and knowledge related to genomics in practice. Yet, nurses are key to bridging the gap between genomic discoveries and the human experience of illness. This article presents a case study documenting the experience of five nursing schools/colleges of nursing as they work to integrate genetics and genomics into their curricula. Copyright © 2013 Elsevier Inc. All rights reserved.

Large scale analysis of the mutational landscape in HT-SELEX improves aptamer discovery

PubMed Central

Hoinka, Jan; Berezhnoy, Alexey; Dao, Phuong; Sauna, Zuben E.; Gilboa, Eli; Przytycka, Teresa M.

2015-01-01

High-Throughput (HT) SELEX combines SELEX (Systematic Evolution of Ligands by EXponential Enrichment), a method for aptamer discovery, with massively parallel sequencing technologies. This emerging technology provides data for a global analysis of the selection process and for simultaneous discovery of a large number of candidates but currently lacks dedicated computational approaches for their analysis. To close this gap, we developed novel in-silico methods to analyze HT-SELEX data and utilized them to study the emergence of polymerase errors during HT-SELEX. Rather than considering these errors as a nuisance, we demonstrated their utility for guiding aptamer discovery. Our approach builds on two main advancements in aptamer analysis: AptaMut—a novel technique allowing for the identification of polymerase errors conferring an improved binding affinity relative to the ‘parent’ sequence and AptaCluster—an aptamer clustering algorithm which is to our best knowledge, the only currently available tool capable of efficiently clustering entire aptamer pools. We applied these methods to an HT-SELEX experiment developing aptamers against Interleukin 10 receptor alpha chain (IL-10RA) and experimentally confirmed our predictions thus validating our computational methods. PMID:25870409

Big data to smart data in Alzheimer's disease: The brain health modeling initiative to foster actionable knowledge.

PubMed

Geerts, Hugo; Dacks, Penny A; Devanarayan, Viswanath; Haas, Magali; Khachaturian, Zaven S; Gordon, Mark Forrest; Maudsley, Stuart; Romero, Klaus; Stephenson, Diane

2016-09-01

Massive investment and technological advances in the collection of extensive and longitudinal information on thousands of Alzheimer patients results in large amounts of data. These "big-data" databases can potentially advance CNS research and drug development. However, although necessary, they are not sufficient, and we posit that they must be matched with analytical methods that go beyond retrospective data-driven associations with various clinical phenotypes. Although these empirically derived associations can generate novel and useful hypotheses, they need to be organically integrated in a quantitative understanding of the pathology that can be actionable for drug discovery and development. We argue that mechanism-based modeling and simulation approaches, where existing domain knowledge is formally integrated using complexity science and quantitative systems pharmacology can be combined with data-driven analytics to generate predictive actionable knowledge for drug discovery programs, target validation, and optimization of clinical development. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

[Challenges and strategies of drug innovation].

PubMed

Guo, Zong-Ru; Zhao, Hong-Yu

2013-07-01

Drug research involves scientific discovery, technological inventions and product development. This multiple dimensional effort embodies both high risk and high reward and is considered one of the most complicated human activities. Prior to the initiation of a program, an in-depth analysis of "what to do" and "how to do it" must be conducted. On the macro level, market prospects, capital required, risk assessment, necessary human resources, etc. need to be evaluated critically. For execution, drug candidates need to be optimized in multiple properties such as potency, selectivity, pharmacokinetics, safety, formulation, etc., all with the constraint of finite amount of time and resources, to maximize the probability of success in clinical development. Drug discovery is enormously complicated, both in terms of technological innovation and organizing capital and other resources. A deep understanding of the complexity of drug research and our competitive edge is critical for success. Our unique government-enterprise-academia system represents a distinct advantage. As a new player, we have not heavily invested in any particular discovery paradigm, which allows us to select the optimal approach with little organizational burden. Virtue R&D model using CROs has gained momentum lately and China is a global leader in CRO market. Essentially all technological support for drug discovery can be found in China, which greatly enables domestic R&D efforts. The information technology revolution ensures the globalization of drug discovery knowledge, which has bridged much of the gap between China and the developed countries. The blockbuster model and the target-centric drug discovery paradigm have overlooked the research in several important fields such as injectable drugs, orphan drugs, and following high quality therapeutic leads, etc. Prejudice against covalent ligands, prodrugs, nondrug-like ligands can also be taken advantage of to find novel medicines. This article will discuss the current challenges and future opportunities for drug innovation in China.

Using key performance indicators as knowledge-management tools at a regional health-care authority level.

PubMed

Berler, Alexander; Pavlopoulos, Sotiris; Koutsouris, Dimitris

2005-06-01

The advantages of the introduction of information and communication technologies in the complex health-care sector are already well-known and well-stated in the past. It is, nevertheless, paradoxical that although the medical community has embraced with satisfaction most of the technological discoveries allowing the improvement in patient care, this has not happened when talking about health-care informatics. Taking the above issue of concern, our work proposes an information model for knowledge management (KM) based upon the use of key performance indicators (KPIs) in health-care systems. Based upon the use of the balanced scorecard (BSC) framework (Kaplan/Norton) and quality assurance techniques in health care (Donabedian), this paper is proposing a patient journey centered approach that drives information flow at all levels of the day-to-day process of delivering effective and managed care, toward information assessment and knowledge discovery. In order to persuade health-care decision-makers to assess the added value of KM tools, those should be used to propose new performance measurement and performance management techniques at all levels of a health-care system. The proposed KPIs are forming a complete set of metrics that enable the performance management of a regional health-care system. In addition, the performance framework established is technically applied by the use of state-of-the-art KM tools such as data warehouses and business intelligence information systems. In that sense, the proposed infrastructure is, technologically speaking, an important KM tool that enables knowledge sharing amongst various health-care stakeholders and between different health-care groups. The use of BSC is an enabling framework toward a KM strategy in health care.

Mapping the Sloan Digital Sky Survey's Global Impact

NASA Astrophysics Data System (ADS)

Chen, Chaomei; Zhang, Jian; Vogeley, Michael S.

2009-07-01

The scientific capacity of a country is essential in todayâ's increasingly globalized science and technology ecosystem. Scientific capacity has four increasingly advanced levels of capabilities: absorbing, applying, creating, and retaining scientific knowledge. Moving to a advanced level requires additional skills and training. For example, it requires more specialized skills to apply scientific knowledge than to absorb knowledge. Similarly, making new discoveries requires more knowledge than applying existing procedures. Research has shown the importance of addressing specific, local problems while tapping into globally available expertise and resources. Accessing scientific knowledge is the first step towards absorbing knowledge. Low-income countries have increased their access to scientific literature on the Internet, but to what extent has this access led to more advanced levels of scientific capacity? Interdisciplinary and international collaboration may hold the key to creating and retaining knowledge. For example, creative ideas tend to be associated with inspirations originated from a diverse range of perspectives On the other hand, not all collaborations are productive. Assessing global science and technology needs to address both successes and failures and reasons behind them.

ESIP's Earth Science Knowledge Graph (ESKG) Testbed Project: An Automatic Approach to Building Interdisciplinary Earth Science Knowledge Graphs to Improve Data Discovery

NASA Astrophysics Data System (ADS)

McGibbney, L. J.; Jiang, Y.; Burgess, A. B.

2017-12-01

Big Earth observation data have been produced, archived and made available online, but discovering the right data in a manner that precisely and efficiently satisfies user needs presents a significant challenge to the Earth Science (ES) community. An emerging trend in information retrieval community is to utilize knowledge graphs to assist users in quickly finding desired information from across knowledge sources. This is particularly prevalent within the fields of social media and complex multimodal information processing to name but a few, however building a domain-specific knowledge graph is labour-intensive and hard to keep up-to-date. In this work, we update our progress on the Earth Science Knowledge Graph (ESKG) project; an ESIP-funded testbed project which provides an automatic approach to building a dynamic knowledge graph for ES to improve interdisciplinary data discovery by leveraging implicit, latent existing knowledge present within across several U.S Federal Agencies e.g. NASA, NOAA and USGS. ESKG strengthens ties between observations and user communities by: 1) developing a knowledge graph derived from various sources e.g. Web pages, Web Services, etc. via natural language processing and knowledge extraction techniques; 2) allowing users to traverse, explore, query, reason and navigate ES data via knowledge graph interaction. ESKG has the potential to revolutionize the way in which ES communities interact with ES data in the open world through the entity, spatial and temporal linkages and characteristics that make it up. This project enables the advancement of ESIP collaboration areas including both Discovery and Semantic Technologies by putting graph information right at our fingertips in an interactive, modern manner and reducing the efforts to constructing ontology. To demonstrate the ESKG concept, we will demonstrate use of our framework across NASA JPL's PO.DAAC, NOAA's Earth Observation Requirements Evaluation System (EORES) and various USGS systems.

Knowledge Discovery from Databases: An Introductory Review.

ERIC Educational Resources Information Center

Vickery, Brian

1997-01-01

Introduces new procedures being used to extract knowledge from databases and discusses rationales for developing knowledge discovery methods. Methods are described for such techniques as classification, clustering, and the detection of deviations from pre-established norms. Examines potential uses of knowledge discovery in the information field.…

Developing Capacities for Teaching Responsible Science in the MENA Region: Refashioning Scientific Dialogue

ERIC Educational Resources Information Center

National Academies Press, 2013

2013-01-01

Spurred on by new discoveries and rapid technological advances, the capacity for life science research is expanding across the globe-and with it comes concerns about the unintended impacts of research on the physical and biological environment, human well-being, or the deliberate misuse of knowledge, tools, and techniques to cause harm. This…

Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

PubMed Central

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N.; Carter, Jeff; Dalby, Andrew B.; Eaton, Bruce E.; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R.; Kim, Nancy; Koch, Tad H.; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K.; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M.; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I.; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D.; Vrkljan, Mike; Walker, Jeffrey J.; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K.; Wolfson, Alexey; Wolk, Steven K.; Zhang, Chi; Zichi, Dom

2010-01-01

Background The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. Methodology/Principal Findings We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. Conclusions/Significance We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine. PMID:21165148

Aptamer-based multiplexed proteomic technology for biomarker discovery.

PubMed

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

2010-12-07

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

PubMed Central

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

The relation between prior knowledge and students' collaborative discovery learning processes

NASA Astrophysics Data System (ADS)

Gijlers, Hannie; de Jong, Ton

2005-03-01

In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication between students was recorded and the interaction with the environment was logged. Based on students' individual judgments of the truth-value and testability of a series of domain-specific propositions, a detailed description of the knowledge configuration for each dyad was created before they entered the learning environment. Qualitative analyses of two dialogues illustrated that prior knowledge influences the discovery learning processes, and knowledge development in a pair of students. Assessments of student and dyad definitional (domain-specific) knowledge, generic (mathematical and graph) knowledge, and generic (discovery) skills were related to the students' dialogue in different discovery learning processes. Results show that a high level of definitional prior knowledge is positively related to the proportion of communication regarding the interpretation of results. Heterogeneity with respect to generic prior knowledge was positively related to the number of utterances made in the discovery process categories hypotheses generation and experimentation. Results of the qualitative analyses indicated that collaboration between extremely heterogeneous dyads is difficult when the high achiever is not willing to scaffold information and work in the low achiever's zone of proximal development.

Evolution of the “Drivers” of Translational Cancer Epidemiology: Analysis of Funded Grants and the Literature

PubMed Central

Lam, Tram Kim; Chang, Christine Q.; Rogers, Scott D.; Khoury, Muin J.; Schully, Sheri D.

2015-01-01

Concurrently with a workshop sponsored by the National Cancer Institute, we identified key “drivers” for accelerating cancer epidemiology across the translational research continuum in the 21st century: emerging technologies, a multilevel approach, knowledge integration, and team science. To map the evolution of these “drivers” and translational phases (T0–T4) in the past decade, we analyzed cancer epidemiology grants funded by the National Cancer Institute and published literature for 2000, 2005, and 2010. For each year, we evaluated the aims of all new/competing grants and abstracts of randomly selected PubMed articles. Compared with grants based on a single institution, consortium-based grants were more likely to incorporate contemporary technologies (P = 0.012), engage in multilevel analyses (P = 0.010), and incorporate elements of knowledge integration (P = 0.036). Approximately 74% of analyzed grants and publications involved discovery (T0) or characterization (T1) research, suggesting a need for more translational (T2–T4) research. Our evaluation indicated limited research in 1) a multilevel approach that incorporates molecular, individual, social, and environmental determinants and 2) knowledge integration that evaluates the robustness of scientific evidence. Cancer epidemiology is at the cusp of a paradigm shift, and the field will need to accelerate the pace of translating scientific discoveries in order to impart population health benefits. While multi-institutional and technology-driven collaboration is happening, concerted efforts to incorporate other key elements are warranted for the discipline to meet future challenges. PMID:25767265

Romans to Mars

NASA Technical Reports Server (NTRS)

Bents, D. J.

1990-01-01

The key role played by technology advancement with respect to the anticipated era of discovery and exploration (in space) is illustrated: how bold new initiatives may or may not be enabled. A truly enabling technology not only renders the proposed missions technically feasible, but also makes them viable economically; that is, low enough in cost (relative to the economy supporting them) that urgent national need is not required for justification, low enough in cost that high risk can be programmatically tolerated. A fictional parallel is drawn to the Roman Empire of the second century A.D., shown to have possessed by that time the necessary knowledge, motivation, means, and technical capability of mounting, through the use of innovative mission planning, an initiative similar to Columbus' voyage. They failed to do so because they lacked the advanced technology necessary to make it an acceptable proposition economically. Speculation, based on the historical perspective, is made on the outcome of contemporary plans for future exploration showing how they will be subjected to the same historical forces, within limits imposed by the state of technology development, that shaped the timing of that previous era of discovery and exploration.

[Current situation and development trend of Chinese medicine information research].

PubMed

Dong, Yan; Cui, Meng

2013-04-01

Literature resource service was the main service that Chinese medicine (CM) information offered. But in recent years users have started to request the health information knowledge service. The CM information researches and application service mainly included: (1) the need of strength studies on theory, application of technology, information retrieval, and information standard development; (2) Information studies need to support clinical decision making, new drug research; (3) Quick response based on the network monitoring and support to emergency countermeasures. CM information researches have the following treads: (1) developing the theory system structure of CM information; (2) studying the methodology system of CM information; (3) knowledge discovery and knowledge innovation.

Genalogical approaches to ethical implications of informational assimilative integrated discovery systems (AIDS) in business

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pharhizgar, K.D.; Lunce, S.E.

1994-12-31

Development of knowledge-based technological acquisition techniques and customers` information profiles are known as assimilative integrated discovery systems (AIDS) in modern organizations. These systems have access through processing to both deep and broad domains of information in modern societies. Through these systems organizations and individuals can predict future trend probabilities and events concerning their customers. AIDSs are new techniques which produce new information which informants can use without the help of the knowledge sources because of the existence of highly sophisticated computerized networks. This paper has analyzed the danger and side effects of misuse of information through the illegal, unethical andmore » immoral access to the data-base in an integrated and assimilative information system as described above. Cognivistic mapping, pragmatistic informational design gathering, and holistic classifiable and distributive techniques are potentially abusive systems whose outputs can be easily misused by businesses when researching the firm`s customers.« less

Information Fusion for Natural and Man-Made Disasters

DTIC Science & Technology

2007-01-31

comprehensively large, and metaphysically accurate model of situations, through which specific tasks such as situation assessment, knowledge discovery , or the...significance” is always context specific. Event discovery is a very important element of the HLF process, which can lead to knowledge discovery about...expected, given the current state of knowledge . Examples of such behavior may include discovery of a new aggregate or situation, a specific pattern of

A Technology-Enriched Active Learning Space for a New Gateway Education Programme in Hong Kong: A Platform for Nurturing Student Innovations

ERIC Educational Resources Information Center

Chiu, Pit Ho Patrio

2016-01-01

A Gateway Education Programme is established in Hong Kong that aims to broaden students' interdisciplinary knowledge and nurture student innovations under the Discovery-enriched Curriculum. To support the initiative, a novel idea was proposed for the creation of a Gateway Education Laboratory (GE Lab) with a highly configurable layout equipped…

Ethnophytotechnology: Harnessing the Power of Ethnobotany with Biotechnology.

PubMed

de la Parra, John; Quave, Cassandra L

2017-09-01

Ethnobotany (the scientific study of traditional plant knowledge) has aided the discovery of important medicines. However, as single-molecule drugs or synergistic mixtures, these remedies have faced obstacles in production and analysis. Now, advances in bioreactor technology, metabolic engineering, and analytical instrumentation are improving the production, manipulation, and scientific understanding of such remedies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Semantically enabling pharmacogenomic data for the realization of personalized medicine

PubMed Central

Samwald, Matthias; Coulet, Adrien; Huerga, Iker; Powers, Robert L; Luciano, Joanne S; Freimuth, Robert R; Whipple, Frederick; Pichler, Elgar; Prud’hommeaux, Eric; Dumontier, Michel; Marshall, M Scott

2014-01-01

Understanding how each individual’s genetics and physiology influences pharmaceutical response is crucial to the realization of personalized medicine and the discovery and validation of pharmacogenomic biomarkers is key to its success. However, integration of genotype and phenotype knowledge in medical information systems remains a critical challenge. The inability to easily and accurately integrate the results of biomolecular studies with patients’ medical records and clinical reports prevents us from realizing the full potential of pharmacogenomic knowledge for both drug development and clinical practice. Herein, we describe approaches using Semantic Web technologies, in which pharmacogenomic knowledge relevant to drug development and medical decision support is represented in such a way that it can be efficiently accessed both by software and human experts. We suggest that this approach increases the utility of data, and that such computational technologies will become an essential part of personalized medicine, alongside diagnostics and pharmaceutical products. PMID:22256869

Metallic iron for safe drinking water provision: Considering a lost knowledge.

PubMed

Mwakabona, Hezron T; Ndé-Tchoupé, Arnaud Igor; Njau, Karoli N; Noubactep, Chicgoua; Wydra, Kerstin D

2017-06-15

Around year 1890, the technology of using metallic iron (Fe 0 ) for safe drinking water provision was already established in Europe. The science and technology to manufacture suitable Fe 0 materials were known and further developed in this period. Scientists had then developed skills to (i) explore the suitability of individual Fe 0 materials (e.g. iron filling, sponge iron) for selected applications, and (ii) establish treatment processes for households and water treatment plants. The recent (1990) discovery of Fe 0 as reactive agent for environmental remediation and water treatment has not yet considered this ancient knowledge. In the present work, some key aspects of the ancient knowledge are presented together with some contemporised interpretations, in an attempt to demonstrate the scientific truth contained therein. It appears that the ancient knowledge is an independent validation of the scientific concept that in water treatment (Fe 0 /H 2 O system) Fe 0 materials are generators of contaminant collectors. Copyright © 2017 Elsevier Ltd. All rights reserved.

The lessons of Varsovian's reconnaissance

NASA Technical Reports Server (NTRS)

Bents, D. J.

1990-01-01

The role played by advanced technology is illustrated with respect to the anticipated era of discovery and exploration (in space): how bold new exploration initiatives may or may not be enabled. Enabling technology makes the mission feasible. To be truly enabling, however, the technology must not only render the proposed mission technically feasible, but also make it viable economically; that is, low enough in cost (relative to the economy supporting it) that urgent national need is not required for justification, low enough that risks can be programmatically tolerated. An allegorical parallel is drawn to the Roman Empire of the second century AD, shown to have possessed by that time the necessary knowledge, motivation, means, and technical capability of mounting, through the use of innovative mission planning, an initiative similar to Columbus' voyage. They failed to do so; not because they lacked the vision, but because their technology was not advanced enough to make it an acceptable proposition economically. Speculation, based on the historical perspective, is made on the outcome of contemporary plans for future exploration showing how they will be subjected to the same historical forces, within limits imposed by the state of technology development, that shaped the timing of that previous era of discovery and exploration.

A New System To Support Knowledge Discovery: Telemakus.

ERIC Educational Resources Information Center

Revere, Debra; Fuller, Sherrilynne S.; Bugni, Paul F.; Martin, George M.

2003-01-01

The Telemakus System builds on the areas of concept representation, schema theory, and information visualization to enhance knowledge discovery from scientific literature. This article describes the underlying theories and an overview of a working implementation designed to enhance the knowledge discovery process through retrieval, visual and…

Emergence of Chinese drug discovery research: impact of hit and lead identification.

PubMed

Zhou, Caihong; Zhou, Yan; Wang, Jia; Zhu, Yue; Deng, Jiejie; Wang, Ming-Wei

2015-03-01

The identification of hits and the generation of viable leads is an early and yet crucial step in drug discovery. In the West, the main players of drug discovery are pharmaceutical and biotechnology companies, while in China, academic institutions remain central in the field of drug discovery. There has been a tremendous amount of investment from the public as well as private sectors to support infrastructure buildup and expertise consolidation relative to drug discovery and development in the past two decades. A large-scale compound library has been established in China, and a series of high-impact discoveries of lead compounds have been made by integrating information obtained from different technology-based strategies. Natural products are a major source in China's drug discovery efforts. Knowledge has been enhanced via disruptive breakthroughs such as the discovery of Boc5 as a nonpeptidic agonist of glucagon-like peptide 1 receptor (GLP-1R), one of the class B G protein-coupled receptors (GPCRs). Most of the original hit identification and lead generation were carried out by academic institutions, including universities and specialized research institutes. The Chinese pharmaceutical industry is gradually transforming itself from manufacturing low-end generics and active pharmaceutical ingredients to inventing new drugs. © 2014 Society for Laboratory Automation and Screening.

GalenOWL: Ontology-based drug recommendations discovery

PubMed Central

2012-01-01

Background Identification of drug-drug and drug-diseases interactions can pose a difficult problem to cope with, as the increasingly large number of available drugs coupled with the ongoing research activities in the pharmaceutical domain, make the task of discovering relevant information difficult. Although international standards, such as the ICD-10 classification and the UNII registration, have been developed in order to enable efficient knowledge sharing, medical staff needs to be constantly updated in order to effectively discover drug interactions before prescription. The use of Semantic Web technologies has been proposed in earlier works, in order to tackle this problem. Results This work presents a semantic-enabled online service, named GalenOWL, capable of offering real time drug-drug and drug-diseases interaction discovery. For enabling this kind of service, medical information and terminology had to be translated to ontological terms and be appropriately coupled with medical knowledge of the field. International standards such as the aforementioned ICD-10 and UNII, provide the backbone of the common representation of medical data, while the medical knowledge of drug interactions is represented by a rule base which makes use of the aforementioned standards. Details of the system architecture are presented while also giving an outline of the difficulties that had to be overcome. A comparison of the developed ontology-based system with a similar system developed using a traditional business logic rule engine is performed, giving insights on the advantages and drawbacks of both implementations. Conclusions The use of Semantic Web technologies has been found to be a good match for developing drug recommendation systems. Ontologies can effectively encapsulate medical knowledge and rule-based reasoning can capture and encode the drug interactions knowledge. PMID:23256945

Knowledge Discovery as an Aid to Organizational Creativity.

ERIC Educational Resources Information Center

Siau, Keng

2000-01-01

This article presents the concept of knowledge discovery, a process of searching for associations in large volumes of computer data, as an aid to creativity. It then discusses the various techniques in knowledge discovery. Mednick's associative theory of creative thought serves as the theoretical foundation for this research. (Contains…

Advances in Knowledge Discovery and Data Mining 21st Pacific Asia Conference, PAKDD 2017 Held in Jeju, South Korea, May 23 26, 2017. Proceedings Part I, Part II.

DTIC Science & Technology

2017-06-27

From - To) 05-27-2017 Final 17-03-2017 - 15-03-2018 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER FA2386-17-1-0102 Advances in Knowledge Discovery and...Springer; Switzerland. 14. ABSTRACT The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference...in the areas of knowledge discovery and data mining (KDD). We had three keynote speeches, delivered by Sang Cha from Seoul National University

Semantically-enabled Knowledge Discovery in the Deep Carbon Observatory

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.; Ma, X.; Erickson, J. S.; West, P.; Fox, P. A.

2013-12-01

The Deep Carbon Observatory (DCO) is a decadal effort aimed at transforming scientific and public understanding of carbon in the complex deep earth system from the perspectives of Deep Energy, Deep Life, Extreme Physics and Chemistry, and Reservoirs and Fluxes. Over the course of the decade DCO scientific activities will generate a massive volume of data across a variety of disciplines, presenting significant challenges in terms of data integration, management, analysis and visualization, and ultimately limiting the ability of scientists across disciplines to make insights and unlock new knowledge. The DCO Data Science Team (DCO-DS) is applying Semantic Web methodologies to construct a knowledge representation focused on the DCO Earth science disciplines, and use it together with other technologies (e.g. natural language processing and data mining) to create a more expressive representation of the distributed corpus of DCO artifacts including datasets, metadata, instruments, sensors, platforms, deployments, researchers, organizations, funding agencies, grants and various awards. The embodiment of this knowledge representation is the DCO Data Science Infrastructure, in which unique entities within the DCO domain and the relations between them are recognized and explicitly identified. The DCO-DS Infrastructure will serve as a platform for more efficient and reliable searching, discovery, access, and publication of information and knowledge for the DCO scientific community and beyond.

Technology Transfer - A Look at the Federal Sector.

DTIC Science & Technology

1978-03-01

with need s at the other by means of a complex “br okerage process. ” At the technology end , ther e is a body of knowledge which resul t s fr om...sive right to their respective writing s and discoveries . ” [Ref. 40 , p. 3] The first patent law was enacted in 1790. Through the years the patent laws...Advisor: 3. W. Creig htor i Approved for public release; distribution unlimited / Unc la s si.fied SECURITY CLA ISIPICAYIOW OP THIS PAGE (U~uIn 0.1

Development of Proteomics-Based Fungicides: New Strategies for Environmentally Friendly Control of Fungal Plant Diseases

PubMed Central

Acero, Francisco Javier Fernández; Carbú, María; El-Akhal, Mohamed Rabie; Garrido, Carlos; González-Rodríguez, Victoria E.; Cantoral, Jesús M.

2011-01-01

Proteomics has become one of the most relevant high-throughput technologies. Several approaches have been used for studying, for example, tumor development, biomarker discovery, or microbiology. In this “post-genomic” era, the relevance of these studies has been highlighted as the phenotypes determined by the proteins and not by the genotypes encoding them that is responsible for the final phenotypes. One of the most interesting outcomes of these technologies is the design of new drugs, due to the discovery of new disease factors that may be candidates for new therapeutic targets. To our knowledge, no commercial fungicides have been developed from targeted molecular research, this review will shed some light on future prospects. We will summarize previous research efforts and discuss future innovations, focused on the fight against one of the main agents causing a devastating crops disease, fungal phytopathogens. PMID:21340014

Pros and cons of healthcare information technology implementation: the pros win.

PubMed

Maffei, Roxana

2006-01-01

Countless studies and investigations have been performed siding either for or against the implementation of technology in the healthcare setting. This article presents both sides of this debate, with an obvious conclusion that the pros of this debate win. The practice of information technology in the medical domain lags behind its knowledge and discovery by at least 7 years. The key to closing this gap is to show, through various studies, how information technology systems provide decision support to users at the point in time when decisions are needed. What the reader will obtain from this article is that the pros for information technology implementation in healthcare settings weigh much more and have a greater effect than the cons.

Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts.

PubMed

Ng; Wong

1999-01-01

We are entering a new era of research where the latest scientific discoveries are often first reported online and are readily accessible by scientists worldwide. This rapid electronic dissemination of research breakthroughs has greatly accelerated the current pace in genomics and proteomics research. The race to the discovery of a gene or a drug has now become increasingly dependent on how quickly a scientist can scan through voluminous amount of information available online to construct the relevant picture (such as protein-protein interaction pathways) as it takes shape amongst the rapidly expanding pool of globally accessible biological data (e.g. GENBANK) and scientific literature (e.g. MEDLINE). We describe a prototype system for automatic pathway discovery from on-line text abstracts, combining technologies that (1) retrieve research abstracts from online sources, (2) extract relevant information from the free texts, and (3) present the extracted information graphically and intuitively. Our work demonstrates that this framework allows us to routinely scan online scientific literature for automatic discovery of knowledge, giving modern scientists the necessary competitive edge in managing the information explosion in this electronic age.

The Relation between Prior Knowledge and Students' Collaborative Discovery Learning Processes

ERIC Educational Resources Information Center

Gijlers, Hannie; de Jong, Ton

2005-01-01

In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication between students was recorded and the interaction…

Bioinformatics in protein kinases regulatory network and drug discovery.

PubMed

Chen, Qingfeng; Luo, Haiqiong; Zhang, Chengqi; Chen, Yi-Ping Phoebe

2015-04-01

Protein kinases have been implicated in a number of diseases, where kinases participate many aspects that control cell growth, movement and death. The deregulated kinase activities and the knowledge of these disorders are of great clinical interest of drug discovery. The most critical issue is the development of safe and efficient disease diagnosis and treatment for less cost and in less time. It is critical to develop innovative approaches that aim at the root cause of a disease, not just its symptoms. Bioinformatics including genetic, genomic, mathematics and computational technologies, has become the most promising option for effective drug discovery, and has showed its potential in early stage of drug-target identification and target validation. It is essential that these aspects are understood and integrated into new methods used in drug discovery for diseases arisen from deregulated kinase activity. This article reviews bioinformatics techniques for protein kinase data management and analysis, kinase pathways and drug targets and describes their potential application in pharma ceutical industry. Copyright © 2015 Elsevier Inc. All rights reserved.

Molecular genetics of early-onset Alzheimer's disease revisited.

PubMed

Cacace, Rita; Sleegers, Kristel; Van Broeckhoven, Christine

2016-06-01

As the discovery of the Alzheimer's disease (AD) genes, APP, PSEN1, and PSEN2, in families with autosomal dominant early-onset AD (EOAD), gene discovery in familial EOAD came more or less to a standstill. Only 5% of EOAD patients are carrying a pathogenic mutation in one of the AD genes or a apolipoprotein E (APOE) risk allele ε4, most of EOAD patients remain unexplained. Here, we aimed at summarizing the current knowledge of EOAD genetics and its role in ongoing approaches to understand the biology of AD and disease symptomatology as well as developing new therapeutics. Next, we explored the possible molecular mechanisms that might underlie the missing genetic etiology of EOAD and discussed how the use of massive parallel sequencing technologies triggered novel gene discoveries. To conclude, we commented on the relevance of reinvestigating EOAD patients as a means to explore potential new avenues for translational research and therapeutic discoveries. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

PubMed

DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

Longitudinal Patent Analysis for Nanoscale Science and Engineering: Country, Institution and Technology Field

NASA Astrophysics Data System (ADS)

Huang, Zan; Chen, Hsinchun; Yip, Alan; Ng, Gavin; Guo, Fei; Chen, Zhi-Kai; Roco, Mihail C.

2003-08-01

Nanoscale science and engineering (NSE) and related areas have seen rapid growth in recent years. The speed and scope of development in the field have made it essential for researchers to be informed on the progress across different laboratories, companies, industries and countries. In this project, we experimented with several analysis and visualization techniques on NSE-related United States patent documents to support various knowledge tasks. This paper presents results on the basic analysis of nanotechnology patents between 1976 and 2002, content map analysis and citation network analysis. The data have been obtained on individual countries, institutions and technology fields. The top 10 countries with the largest number of nanotechnology patents are the United States, Japan, France, the United Kingdom, Taiwan, Korea, the Netherlands, Switzerland, Italy and Australia. The fastest growth in the last 5 years has been in chemical and pharmaceutical fields, followed by semiconductor devices. The results demonstrate potential of information-based discovery and visualization technologies to capture knowledge regarding nanotechnology performance, transfer of knowledge and trends of development through analyzing the patent documents.

SemaTyP: a knowledge graph based literature mining method for drug discovery.

PubMed

Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

2018-05-30

Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

Lipidomics from an analytical perspective.

PubMed

Sandra, Koen; Sandra, Pat

2013-10-01

The global non-targeted analysis of various biomolecules in a variety of sample sources gained momentum in recent years. Defined as the study of the full lipid complement of cells, tissues and organisms, lipidomics is currently evolving out of the shadow of the more established omics sciences including genomics, transcriptomics, proteomics and metabolomics. In analogy to the latter, lipidomics has the potential to impact on biomarker discovery, drug discovery/development and system knowledge, amongst others. The tools developed by lipid researchers in the past, complemented with the enormous advancements made in recent years in mass spectrometry and chromatography, and the implementation of sophisticated (bio)-informatics tools form the basis of current lipidomics technologies. Copyright © 2013 Elsevier Ltd. All rights reserved.

A New Student Performance Analysing System Using Knowledge Discovery in Higher Educational Databases

ERIC Educational Resources Information Center

Guruler, Huseyin; Istanbullu, Ayhan; Karahasan, Mehmet

2010-01-01

Knowledge discovery is a wide ranged process including data mining, which is used to find out meaningful and useful patterns in large amounts of data. In order to explore the factors having impact on the success of university students, knowledge discovery software, called MUSKUP, has been developed and tested on student data. In this system a…

Leveraging ecological theory to guide natural product discovery.

PubMed

Smanski, Michael J; Schlatter, Daniel C; Kinkel, Linda L

2016-03-01

Technological improvements have accelerated natural product (NP) discovery and engineering to the point that systematic genome mining for new molecules is on the horizon. NP biosynthetic potential is not equally distributed across organisms, environments, or microbial life histories, but instead is enriched in a number of prolific clades. Also, NPs are not equally abundant in nature; some are quite common and others markedly rare. Armed with this knowledge, random 'fishing expeditions' for new NPs are increasingly harder to justify. Understanding the ecological and evolutionary pressures that drive the non-uniform distribution of NP biosynthesis provides a rational framework for the targeted isolation of strains enriched in new NP potential. Additionally, ecological theory leads to testable hypotheses regarding the roles of NPs in shaping ecosystems. Here we review several recent strain prioritization practices and discuss the ecological and evolutionary underpinnings for each. Finally, we offer perspectives on leveraging microbial ecology and evolutionary biology for future NP discovery.

A Road Map for Precision Medicine in the Epilepsies

PubMed Central

2015-01-01

Summary Technological advances have paved the way for accelerated genomic discovery and are bringing precision medicine clearly into view. Epilepsy research in particular is well-suited to serve as a model for the development and deployment of targeted therapeutics in precision medicine because of the rapidly expanding genetic knowledge base in epilepsy, the availability of good in vitro and in vivo model systems to efficiently study the biological consequences of genetic mutations, the ability to turn these models into effective drug screening platforms, and the establishment of collaborative research groups. Moving forward, it is critical that we strengthen these collaborations, particularly through integrated research platforms to provide robust analyses both for accurate personal genome analysis and gene and drug discovery. Similarly, the implementation of clinical trial networks will allow the expansion of patient sample populations with genetically defined epilepsy so that drug discovery can be translated into clinical practice. PMID:26416172

The Graduate Training Programme "Molecular Imaging for the Analysis of Gene and Protein Expression": A Case Study with an Insight into the Participation of Universities of Applied Sciences

ERIC Educational Resources Information Center

Hafner, Mathias

2008-01-01

Cell biology and molecular imaging technologies have made enormous progress in basic research. However, the transfer of this knowledge to the pharmaceutical drug discovery process, or even therapeutic improvements for disorders such as neuronal diseases, is still in its infancy. This transfer needs scientists who can integrate basic research with…

Energy-Water Nexus Knowledge Discovery Framework, Experts’ Meeting Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhaduri, Budhendra L.; Simon, AJ; Allen, Melissa R.

Energy and water generation and delivery systems are inherently interconnected. With worldwide demandfor energy growing, the energy sector is experiencing increasing competition for water. With increasingpopulation and changing environmental, socioeconomic, and demographic scenarios, new technology andinvestment decisions must be made for optimized and sustainable energy-water resource management. These decisions require novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales.

Knowledge Discovery in Databases.

ERIC Educational Resources Information Center

Norton, M. Jay

1999-01-01

Knowledge discovery in databases (KDD) revolves around the investigation and creation of knowledge, processes, algorithms, and mechanisms for retrieving knowledge from data collections. The article is an introductory overview of KDD. The rationale and environment of its development and applications are discussed. Issues related to database design…

Panacea, a semantic-enabled drug recommendations discovery framework.

PubMed

Doulaverakis, Charalampos; Nikolaidis, George; Kleontas, Athanasios; Kompatsiaris, Ioannis

2014-03-06

Personalized drug prescription can be benefited from the use of intelligent information management and sharing. International standard classifications and terminologies have been developed in order to provide unique and unambiguous information representation. Such standards can be used as the basis of automated decision support systems for providing drug-drug and drug-disease interaction discovery. Additionally, Semantic Web technologies have been proposed in earlier works, in order to support such systems. The paper presents Panacea, a semantic framework capable of offering drug-drug and drug-diseases interaction discovery. For enabling this kind of service, medical information and terminology had to be translated to ontological terms and be appropriately coupled with medical knowledge of the field. International standard classifications and terminologies, provide the backbone of the common representation of medical data while the medical knowledge of drug interactions is represented by a rule base which makes use of the aforementioned standards. Representation is based on a lightweight ontology. A layered reasoning approach is implemented where at the first layer ontological inference is used in order to discover underlying knowledge, while at the second layer a two-step rule selection strategy is followed resulting in a computationally efficient reasoning approach. Details of the system architecture are presented while also giving an outline of the difficulties that had to be overcome. Panacea is evaluated both in terms of quality of recommendations against real clinical data and performance. The quality recommendation gave useful insights regarding requirements for real world deployment and revealed several parameters that affected the recommendation results. Performance-wise, Panacea is compared to a previous published work by the authors, a service for drug recommendations named GalenOWL, and presents their differences in modeling and approach to the problem, while also pinpointing the advantages of Panacea. Overall, the paper presents a framework for providing an efficient drug recommendations service where Semantic Web technologies are coupled with traditional business rule engines.

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species.

PubMed

Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species

PubMed Central

Irizarry, Kristopher J. L.; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L.; Barrett, Gini; Barr, Margaret C.

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management. PMID:27376076

Workflow based framework for life science informatics.

PubMed

Tiwari, Abhishek; Sekhar, Arvind K T

2007-10-01

Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

An Integrative Bioinformatics Approach for Knowledge Discovery

NASA Astrophysics Data System (ADS)

Peña-Castillo, Lourdes; Phan, Sieu; Famili, Fazel

The vast amount of data being generated by large scale omics projects and the computational approaches developed to deal with this data have the potential to accelerate the advancement of our understanding of the molecular basis of genetic diseases. This better understanding may have profound clinical implications and transform the medical practice; for instance, therapeutic management could be prescribed based on the patient’s genetic profile instead of being based on aggregate data. Current efforts have established the feasibility and utility of integrating and analysing heterogeneous genomic data to identify molecular associations to pathogenesis. However, since these initiatives are data-centric, they either restrict the research community to specific data sets or to a certain application domain, or force researchers to develop their own analysis tools. To fully exploit the potential of omics technologies, robust computational approaches need to be developed and made available to the community. This research addresses such challenge and proposes an integrative approach to facilitate knowledge discovery from diverse datasets and contribute to the advancement of genomic medicine.

Explicitly searching for useful inventions: dynamic relatedness and the costs of connecting versus synthesizing

PubMed Central

2010-01-01

Inventions combine technological features. When features are barely related, burdensomely broad knowledge is required to identify the situations that they share. When features are overly related, burdensomely broad knowledge is required to identify the situations that distinguish them. Thus, according to my first hypothesis, when features are moderately related, the costs of connecting and costs of synthesizing are cumulatively minimized, and the most useful inventions emerge. I also hypothesize that continued experimentation with a specific set of features is likely to lead to the discovery of decreasingly useful inventions; the earlier-identified connections reflect the more common consumer situations. Covering data from all industries, the empirical analysis provides broad support for the first hypothesis. Regressions to test the second hypothesis are inconclusive when examining industry types individually. Yet, this study represents an exploratory investigation, and future research should test refined hypotheses with more sophisticated data, such as that found in literature-based discovery research. PMID:21297855

Communicating the Science from NASA's Astrophysics Missions

NASA Astrophysics Data System (ADS)

Hasan, Hashima; Smith, Denise A.

2015-01-01

Communicating science from NASA's Astrophysics missions has multiple objectives, which leads to a multi-faceted approach. While a timely dissemination of knowledge to the scientific community follows the time-honored process of publication in peer reviewed journals, NASA delivers newsworthy research result to the public through news releases, its websites and social media. Knowledge in greater depth is infused into the educational system by the creation of educational material and teacher workshops that engage students and educators in cutting-edge NASA Astrophysics discoveries. Yet another avenue for the general public to learn about the science and technology through NASA missions is through exhibits at museums, science centers, libraries and other public venues. Examples of the variety of ways NASA conveys the excitement of its scientific discoveries to students, educators and the general public will be discussed in this talk. A brief overview of NASA's participation in the International Year of Light will also be given, as well as of the celebration of the twenty-fifth year of the launch of the Hubble Space Telescope.

Ontology-Based Search of Genomic Metadata.

PubMed

Fernandez, Javier D; Lenzerini, Maurizio; Masseroli, Marco; Venco, Francesco; Ceri, Stefano

2016-01-01

The Encyclopedia of DNA Elements (ENCODE) is a huge and still expanding public repository of more than 4,000 experiments and 25,000 data files, assembled by a large international consortium since 2007; unknown biological knowledge can be extracted from these huge and largely unexplored data, leading to data-driven genomic, transcriptomic, and epigenomic discoveries. Yet, search of relevant datasets for knowledge discovery is limitedly supported: metadata describing ENCODE datasets are quite simple and incomplete, and not described by a coherent underlying ontology. Here, we show how to overcome this limitation, by adopting an ENCODE metadata searching approach which uses high-quality ontological knowledge and state-of-the-art indexing technologies. Specifically, we developed S.O.S. GeM (http://www.bioinformatics.deib.polimi.it/SOSGeM/), a system supporting effective semantic search and retrieval of ENCODE datasets. First, we constructed a Semantic Knowledge Base by starting with concepts extracted from ENCODE metadata, matched to and expanded on biomedical ontologies integrated in the well-established Unified Medical Language System. We prove that this inference method is sound and complete. Then, we leveraged the Semantic Knowledge Base to semantically search ENCODE data from arbitrary biologists' queries. This allows correctly finding more datasets than those extracted by a purely syntactic search, as supported by the other available systems. We empirically show the relevance of found datasets to the biologists' queries.

International Drug Discovery Science and Technology--BIT's Seventh Annual Congress.

PubMed

Bodovitz, Steven

2010-01-01

BIT's Seventh Annual International Drug Discovery Science and Technology Congress, held in Shanghai, included topics covering new therapeutic and technological developments in the field of drug discovery. This conference report highlights selected presentations on open-access approaches to R&D, novel and multifactorial targets, and technologies that assist drug discovery. Investigational drugs discussed include the anticancer agents astuprotimut-r (GlaxoSmithKline plc) and AS-1411 (Antisoma plc).

The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside

PubMed Central

2011-01-01

Background Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. Results We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action. Conclusions This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine. Availability TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql. PMID:21624155

A Knowledge Discovery framework for Planetary Defense

NASA Astrophysics Data System (ADS)

Jiang, Y.; Yang, C. P.; Li, Y.; Yu, M.; Bambacus, M.; Seery, B.; Barbee, B.

2016-12-01

Planetary Defense, a project funded by NASA Goddard and the NSF, is a multi-faceted effort focused on the mitigation of Near Earth Object (NEO) threats to our planet. Currently, there exists a dispersion of information concerning NEO's amongst different organizations and scientists, leading to a lack of a coherent system of information to be used for efficient NEO mitigation. In this paper, a planetary defense knowledge discovery engine is proposed to better assist the development and integration of a NEO responding system. Specifically, we have implemented an organized information framework by two means: 1) the development of a semantic knowledge base, which provides a structure for relevant information. It has been developed by the implementation of web crawling and natural language processing techniques, which allows us to collect and store the most relevant structured information on a regular basis. 2) the development of a knowledge discovery engine, which allows for the efficient retrieval of information from our knowledge base. The knowledge discovery engine has been built on the top of Elasticsearch, an open source full-text search engine, as well as cutting-edge machine learning ranking and recommendation algorithms. This proposed framework is expected to advance the knowledge discovery and innovation in planetary science domain.

Progress and Prospects for Stem Cell Engineering

PubMed Central

Ashton, Randolph S.; Keung, Albert J.; Peltier, Joseph; Schaffer, David V.

2018-01-01

Stem cells offer tremendous biomedical potential owing to their abilities to self-renew and differentiate into cell types of multiple adult tissues. Researchers and engineers have increasingly developed novel discovery technologies, theoretical approaches, and cell culture systems to investigate microenvironmental cues and cellular signaling events that control stem cell fate. Many of these technologies facilitate high-throughput investigation of microenvironmental signals and the intracellular signaling networks and machinery processing those signals into cell fate decisions. As our aggregate empirical knowledge of stem cell regulation grows, theoretical modeling with systems and computational biology methods has and will continue to be important for developing our ability to analyze and extract important conceptual features of stem cell regulation from complex data. Based on this body of knowledge, stem cell engineers will continue to develop technologies that predictably control stem cell fate with the ultimate goal of being able to accurately and economically scale up these systems for clinical-grade production of stem cell therapeutics. PMID:22432628

The confluence of ancient wisdom and future technology in our profession

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, D.P.

1997-10-01

The theme of this year`s Annual Meeting is ``Ancient Wisdom-Future Technology.`` The panel assembled for this session has been asked to think metaphorically about the theme and how it relates to their profession of human factors and ergonomics. Originally conceived as a debate centering around the older technologies and research techniques versus the newer ways of finding answers, it was soon realized that there was no dichotomy, but more of a synergy between the old and the new. If human factors is truly a philosophy of design rather than simply a body of knowledge, then one would expect consistency inmore » approach regardless of field of application or new discoveries of human performance. Just as when two or more rivers combine to become a force mightier than the simple summation, the synergistic power of established techniques or knowledge and recent innovation is available to everyone in the profession. The invited panelists represent diverse perspectives in human factors and ergonomics, and this made for a stimulating discussion.« less

Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs

PubMed Central

Chen, Haijian; Han, Dongmei; Zhao, Lina

2015-01-01

In recent years, Massive Open Online Courses (MOOCs) are very popular among college students and have a powerful impact on academic institutions. In the MOOCs environment, knowledge discovery and knowledge sharing are very important, which currently are often achieved by ontology techniques. In building ontology, automatic extraction technology is crucial. Because the general methods of text mining algorithm do not have obvious effect on online course, we designed automatic extracting course knowledge points (AECKP) algorithm for online course. It includes document classification, Chinese word segmentation, and POS tagging for each document. Vector Space Model (VSM) is used to calculate similarity and design the weight to optimize the TF-IDF algorithm output values, and the higher scores will be selected as knowledge points. Course documents of “C programming language” are selected for the experiment in this study. The results show that the proposed approach can achieve satisfactory accuracy rate and recall rate. PMID:26448738

Intellectual property rights and research disclosure in the university environment: preserving the commercialization option and optimizing market interest.

PubMed

Patino, Robert

2009-03-01

Clinical and basic scientists at academic medical and biomedical research institutions often form ideas that could have both monetary and human health benefits if developed and applied to improvement of human wellbeing. However, such ideas lose much of their potential value in both regards if they are disclosed in traditional knowledge-sharing forums such as abstracts, posters, and oral presentations at research meetings. Learning the basics about intellectual property protection and obtaining professional guidance in the management of intellectual property from a knowledgeable technology management professional or intellectual property attorney can avoid such losses yet pose a minimal burden of confidentiality on the investigator. Knowing how to successfully navigate the early stages of intellectual property protection can greatly increase the likelihood that discoveries and knowledge will become available for the public good without diminishing the important mandate of disseminating knowledge through traditional knowledge-sharing forums.

Nanotechnology applications in hematological malignancies (Review).

PubMed

Samir, Ahmed; Elgamal, Basma M; Gabr, Hala; Sabaawy, Hatem E

2015-09-01

A major limitation to current cancer therapies is the development of therapy-related side-effects and dose limiting complications. Moreover, a better understanding of the biology of cancer cells and the mechanisms of resistance to therapy is rapidly developing. The translation of advanced knowledge and discoveries achieved at the molecular level must be supported by advanced diagnostic, therapeutic and delivery technologies to translate these discoveries into useful tools that are essential in achieving progress in the war against cancer. Nanotechnology can play an essential role in this aspect providing a transforming technology that can translate the basic and clinical findings into novel diagnostic, therapeutic and preventive tools useful in different types of cancer. Hematological malignancies represent a specific class of cancer, which attracts special attention in the applications of nanotechnology for cancer diagnosis and treatment. The aim of the present review is to elucidate the emerging applications of nanotechnology in cancer management and describe the potentials of nanotechnology in changing the key fundamental aspects of hematological malignancy diagnosis, treatment and follow-up.

Cognitive methodology for forecasting oil and gas industry using pattern-based neural information technologies

NASA Astrophysics Data System (ADS)

Gafurov, O.; Gafurov, D.; Syryamkin, V.

2018-05-01

The paper analyses a field of computer science formed at the intersection of such areas of natural science as artificial intelligence, mathematical statistics, and database theory, which is referred to as "Data Mining" (discovery of knowledge in data). The theory of neural networks is applied along with classical methods of mathematical analysis and numerical simulation. The paper describes the technique protected by the patent of the Russian Federation for the invention “A Method for Determining Location of Production Wells during the Development of Hydrocarbon Fields” [1–3] and implemented using the geoinformation system NeuroInformGeo. There are no analogues in domestic and international practice. The paper gives an example of comparing the forecast of the oil reservoir quality made by the geophysicist interpreter using standard methods and the forecast of the oil reservoir quality made using this technology. The technical result achieved shows the increase of efficiency, effectiveness, and ecological compatibility of development of mineral deposits and discovery of a new oil deposit.

Autonomy enables new science missions

NASA Astrophysics Data System (ADS)

Doyle, Richard J.; Gor, Victoria; Man, Guy K.; Stolorz, Paul E.; Chapman, Clark; Merline, William J.; Stern, Alan

1997-01-01

The challenge of space flight in NASA's future is to enable smaller, more frequent and intensive space exploration at much lower total cost without substantially decreasing mission reliability, capability, or the scientific return on investment. The most effective way to achieve this goal is to build intelligent capabilities into the spacecraft themselves. Our technological vision for meeting the challenge of returning quality science through limited communication bandwidth will actually put scientists in a more direct link with the spacecraft than they have enjoyed to date. Technologies such as pattern recognition and machine learning can place a part of the scientist's awareness onboard the spacecraft to prioritize downlink or to autonomously trigger time-critical follow-up observations-particularly important in flyby missions-without ground interaction. Onboard knowledge discovery methods can be used to include candidate discoveries in each downlink for scientists' scrutiny. Such capabilities will allow scientists to quickly reprioritize missions in a much more intimate and efficient manner than is possible today. Ultimately, new classes of exploration missions will be enabled.

Nanotechnology applications in hematological malignancies (Review)

PubMed Central

SAMIR, AHMED; ELGAMAL, BASMA M; GABR, HALA; SABAAWY, HATEM E

2015-01-01

A major limitation to current cancer therapies is the development of therapy-related side-effects and dose limiting complications. Moreover, a better understanding of the biology of cancer cells and the mechanisms of resistance to therapy is rapidly developing. The translation of advanced knowledge and discoveries achieved at the molecular level must be supported by advanced diagnostic, therapeutic and delivery technologies to translate these discoveries into useful tools that are essential in achieving progress in the war against cancer. Nanotechnology can play an essential role in this aspect providing a transforming technology that can translate the basic and clinical findings into novel diagnostic, therapeutic and preventive tools useful in different types of cancer. Hematological malignancies represent a specific class of cancer, which attracts special attention in the applications of nanotechnology for cancer diagnosis and treatment. The aim of the present review is to elucidate the emerging applications of nanotechnology in cancer management and describe the potentials of nanotechnology in changing the key fundamental aspects of hematological malignancy diagnosis, treatment and follow-up. PMID:26134389

Board on Research Data and Information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sztein, A. Ester; Boright, John

2015-08-14

The Board on Research Data and Information (BRDI) has planned and undertaken numerous activities regarding data citation, attribution, management, policy, publishing, centers, access, curation, sharing, and infrastructure; and international collaboration and cooperation. Some of these activities resulted in National Research Council reports (For Attribution: Developing Data Attribution and Citation Practices and Standards (2012), The Case for International Scientific Data Sharing: A Focus on Developing Countries (2012), and The Future of Scientific Knowledge Discovery in Open Networked Environments (2012); and a peer-reviewed paper (Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation ofmore » Data, 2013). BRDI held symposia, workshops and sessions in the U.S. and abroad on diverse topics such as global scientific data infrastructures, discovery of data online, privacy in a big data world, and data citation principles, among other timely data-related subjects. In addition, BRDI effects the representation of the United States before the International Council for Science’s International Committee on Data for Science and Technology (CODATA).« less

Knowledge Discovery from Biomedical Ontologies in Cross Domains.

PubMed

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies.

Knowledge Discovery from Biomedical Ontologies in Cross Domains

PubMed Central

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies. PMID:27548262

Knowledge discovery with classification rules in a cardiovascular dataset.

PubMed

Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

2005-12-01

In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

Need to Knowledge (NtK) Model: an evidence-based framework for generating technological innovations with socio-economic impacts.

PubMed

Flagg, Jennifer L; Lane, Joseph P; Lockett, Michelle M

2013-02-15

Traditional government policies suggest that upstream investment in scientific research is necessary and sufficient to generate technological innovations. The expected downstream beneficial socio-economic impacts are presumed to occur through non-government market mechanisms. However, there is little quantitative evidence for such a direct and formulaic relationship between public investment at the input end and marketplace benefits at the impact end. Instead, the literature demonstrates that the technological innovation process involves a complex interaction between multiple sectors, methods, and stakeholders. The authors theorize that accomplishing the full process of technological innovation in a deliberate and systematic manner requires an operational-level model encompassing three underlying methods, each designed to generate knowledge outputs in different states: scientific research generates conceptual discoveries; engineering development generates prototype inventions; and industrial production generates commercial innovations. Given the critical roles of engineering and business, the entire innovation process should continuously consider the practical requirements and constraints of the commercial marketplace.The Need to Knowledge (NtK) Model encompasses the activities required to successfully generate innovations, along with associated strategies for effectively communicating knowledge outputs in all three states to the various stakeholders involved. It is intentionally grounded in evidence drawn from academic analysis to facilitate objective and quantitative scrutiny, and industry best practices to enable practical application. The Need to Knowledge (NtK) Model offers a practical, market-oriented approach that avoids the gaps, constraints and inefficiencies inherent in undirected activities and disconnected sectors. The NtK Model is a means to realizing increased returns on public investments in those science and technology programs expressly intended to generate beneficial socio-economic impacts.

Need to Knowledge (NtK) Model: an evidence-based framework for generating technological innovations with socio-economic impacts

PubMed Central

2013-01-01

Background Traditional government policies suggest that upstream investment in scientific research is necessary and sufficient to generate technological innovations. The expected downstream beneficial socio-economic impacts are presumed to occur through non-government market mechanisms. However, there is little quantitative evidence for such a direct and formulaic relationship between public investment at the input end and marketplace benefits at the impact end. Instead, the literature demonstrates that the technological innovation process involves a complex interaction between multiple sectors, methods, and stakeholders. Discussion The authors theorize that accomplishing the full process of technological innovation in a deliberate and systematic manner requires an operational-level model encompassing three underlying methods, each designed to generate knowledge outputs in different states: scientific research generates conceptual discoveries; engineering development generates prototype inventions; and industrial production generates commercial innovations. Given the critical roles of engineering and business, the entire innovation process should continuously consider the practical requirements and constraints of the commercial marketplace. The Need to Knowledge (NtK) Model encompasses the activities required to successfully generate innovations, along with associated strategies for effectively communicating knowledge outputs in all three states to the various stakeholders involved. It is intentionally grounded in evidence drawn from academic analysis to facilitate objective and quantitative scrutiny, and industry best practices to enable practical application. Summary The Need to Knowledge (NtK) Model offers a practical, market-oriented approach that avoids the gaps, constraints and inefficiencies inherent in undirected activities and disconnected sectors. The NtK Model is a means to realizing increased returns on public investments in those science and technology programs expressly intended to generate beneficial socio-economic impacts. PMID:23414369

Progress in Biomedical Knowledge Discovery: A 25-year Retrospective

PubMed Central

Sacchi, L.

2016-01-01

Summary Objectives We sought to explore, via a systematic review of the literature, the state of the art of knowledge discovery in biomedical databases as it existed in 1992, and then now, 25 years later, mainly focused on supervised learning. Methods We performed a rigorous systematic search of PubMed and latent Dirichlet allocation to identify themes in the literature and trends in the science of knowledge discovery in and between time periods and compare these trends. We restricted the result set using a bracket of five years previous, such that the 1992 result set was restricted to articles published between 1987 and 1992, and the 2015 set between 2011 and 2015. This was to reflect the current literature available at the time to researchers and others at the target dates of 1992 and 2015. The search term was framed as: Knowledge Discovery OR Data Mining OR Pattern Discovery OR Pattern Recognition, Automated. Results A total 538 and 18,172 documents were retrieved for 1992 and 2015, respectively. The number and type of data sources increased dramatically over the observation period, primarily due to the advent of electronic clinical systems. The period 1992-2015 saw the emergence of new areas of research in knowledge discovery, and the refinement and application of machine learning approaches that were nascent or unknown in 1992. Conclusions Over the 25 years of the observation period, we identified numerous developments that impacted the science of knowledge discovery, including the availability of new forms of data, new machine learning algorithms, and new application domains. Through a bibliometric analysis we examine the striking changes in the availability of highly heterogeneous data resources, the evolution of new algorithmic approaches to knowledge discovery, and we consider from legal, social, and political perspectives possible explanations of the growth of the field. Finally, we reflect on the achievements of the past 25 years to consider what the next 25 years will bring with regard to the availability of even more complex data and to the methods that could be, and are being now developed for the discovery of new knowledge in biomedical data. PMID:27488403

Progress in Biomedical Knowledge Discovery: A 25-year Retrospective.

PubMed

Sacchi, L; Holmes, J H

2016-08-02

We sought to explore, via a systematic review of the literature, the state of the art of knowledge discovery in biomedical databases as it existed in 1992, and then now, 25 years later, mainly focused on supervised learning. We performed a rigorous systematic search of PubMed and latent Dirichlet allocation to identify themes in the literature and trends in the science of knowledge discovery in and between time periods and compare these trends. We restricted the result set using a bracket of five years previous, such that the 1992 result set was restricted to articles published between 1987 and 1992, and the 2015 set between 2011 and 2015. This was to reflect the current literature available at the time to researchers and others at the target dates of 1992 and 2015. The search term was framed as: Knowledge Discovery OR Data Mining OR Pattern Discovery OR Pattern Recognition, Automated. A total 538 and 18,172 documents were retrieved for 1992 and 2015, respectively. The number and type of data sources increased dramatically over the observation period, primarily due to the advent of electronic clinical systems. The period 1992- 2015 saw the emergence of new areas of research in knowledge discovery, and the refinement and application of machine learning approaches that were nascent or unknown in 1992. Over the 25 years of the observation period, we identified numerous developments that impacted the science of knowledge discovery, including the availability of new forms of data, new machine learning algorithms, and new application domains. Through a bibliometric analysis we examine the striking changes in the availability of highly heterogeneous data resources, the evolution of new algorithmic approaches to knowledge discovery, and we consider from legal, social, and political perspectives possible explanations of the growth of the field. Finally, we reflect on the achievements of the past 25 years to consider what the next 25 years will bring with regard to the availability of even more complex data and to the methods that could be, and are being now developed for the discovery of new knowledge in biomedical data.

Communication in Collaborative Discovery Learning

ERIC Educational Resources Information Center

Saab, Nadira; van Joolingen, Wouter R.; van Hout-Wolters, Bernadette H. A. M.

2005-01-01

Background: Constructivist approaches to learning focus on learning environments in which students have the opportunity to construct knowledge themselves, and negotiate this knowledge with others. "Discovery learning" and "collaborative learning" are examples of learning contexts that cater for knowledge construction processes. We introduce a…

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

PubMed Central

DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society

NASA Astrophysics Data System (ADS)

Roco, Mihail C.; Bainbridge, William S.

2013-09-01

Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the twenty-first century. CKTS is defined as the escalating and transformative interactions among seemingly different disciplines, technologies, communities, and domains of human activity to achieve mutual compatibility, synergism, and integration, and through this process to create added value and branch out to meet shared goals. Convergence has been progressing by stages over the past several decades, beginning with nanotechnology for the material world, followed by convergence of nanotechnology, biotechnology, information, and cognitive science (NBIC) for emerging technologies. CKTS is the third level of convergence. It suggests a general process to advance creativity, innovation, and societal progress based on five general purpose principles: (1) the interdependence of all components of nature and society, (2) decision analysis for research, development, and applications based on dynamic system-logic deduction, (3) enhancement of creativity and innovation through evolutionary processes of convergence that combines existing principles and divergence that generates new ones, (4) the utility of higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) the value of vision-inspired basic research embodied in grand challenges. CKTS is a general purpose approach in knowledge society. It allows society to answer questions and resolve problems that isolated capabilities cannot, as well as to create new competencies, knowledge, and technologies on this basis. Possible solutions are outlined for key societal challenges in the next decade, including support for foundational emerging technologies NBIC to penetrate essential platforms of human activity and create new industries and jobs, improve lifelong wellness and human potential, achieve personalized and integrated healthcare and education, and secure a sustainable quality of life for all. This paper provides a 10-year "NBIC2" vision within a longer-term framework for converging technology and human progress outlined in a previous study of unifying principles across "NBIC" fields that began with nanotechnology, biotechnology, information technology, and technologies based on and enabling cognitive science (Roco and Bainbridge, Converging technologies for improving human performance: nanotechnology, biotechnology, information technology and cognitive sciences, 2003).

Practice-Based Knowledge Discovery for Comparative Effectiveness Research: An Organizing Framework

PubMed Central

Lucero, Robert J.; Bakken, Suzanne

2014-01-01

Electronic health information systems can increase the ability of health-care organizations to investigate the effects of clinical interventions. The authors present an organizing framework that integrates outcomes and informatics research paradigms to guide knowledge discovery in electronic clinical databases. They illustrate its application using the example of hospital acquired pressure ulcers (HAPU). The Knowledge Discovery through Informatics for Comparative Effectiveness Research (KDI-CER) framework was conceived as a heuristic to conceptualize study designs and address potential methodological limitations imposed by using a single research perspective. Advances in informatics research can play a complementary role in advancing the field of outcomes research including CER. The KDI-CER framework can be used to facilitate knowledge discovery from routinely collected electronic clinical data. PMID:25278645

Interactive knowledge discovery with the doctor-in-the-loop: a practical example of cerebral aneurysms research.

PubMed

Girardi, Dominic; Küng, Josef; Kleiser, Raimund; Sonnberger, Michael; Csillag, Doris; Trenkler, Johannes; Holzinger, Andreas

2016-09-01

Established process models for knowledge discovery find the domain-expert in a customer-like and supervising role. In the field of biomedical research, it is necessary to move the domain-experts into the center of this process with far-reaching consequences for both their research output and the process itself. In this paper, we revise the established process models for knowledge discovery and propose a new process model for domain-expert-driven interactive knowledge discovery. Furthermore, we present a research infrastructure which is adapted to this new process model and demonstrate how the domain-expert can be deeply integrated even into the highly complex data-mining process and data-exploration tasks. We evaluated this approach in the medical domain for the case of cerebral aneurysms research.

A semantic web ontology for small molecules and their biological targets.

PubMed

Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

2010-05-24

A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

Basic statistics with Microsoft Excel: a review.

PubMed

Divisi, Duilio; Di Leonardo, Gabriella; Zaccagna, Gino; Crisci, Roberto

2017-06-01

The scientific world is enriched daily with new knowledge, due to new technologies and continuous discoveries. The mathematical functions explain the statistical concepts particularly those of mean, median and mode along with those of frequency and frequency distribution associated to histograms and graphical representations, determining elaborative processes on the basis of the spreadsheet operations. The aim of the study is to highlight the mathematical basis of statistical models that regulate the operation of spreadsheets in Microsoft Excel.

Basic statistics with Microsoft Excel: a review

PubMed Central

Di Leonardo, Gabriella; Zaccagna, Gino; Crisci, Roberto

2017-01-01

The scientific world is enriched daily with new knowledge, due to new technologies and continuous discoveries. The mathematical functions explain the statistical concepts particularly those of mean, median and mode along with those of frequency and frequency distribution associated to histograms and graphical representations, determining elaborative processes on the basis of the spreadsheet operations. The aim of the study is to highlight the mathematical basis of statistical models that regulate the operation of spreadsheets in Microsoft Excel. PMID:28740690

High Performance Visualization using Query-Driven Visualizationand Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethel, E. Wes; Campbell, Scott; Dart, Eli

2006-06-15

Query-driven visualization and analytics is a unique approach for high-performance visualization that offers new capabilities for knowledge discovery and hypothesis testing. The new capabilities akin to finding needles in haystacks are the result of combining technologies from the fields of scientific visualization and scientific data management. This approach is crucial for rapid data analysis and visualization in the petascale regime. This article describes how query-driven visualization is applied to a hero-sized network traffic analysis problem.

Plant metabolic clusters - from genetics to genomics.

PubMed

Nützmann, Hans-Wilhelm; Huang, Ancheng; Osbourn, Anne

2016-08-01

Contents 771 I. 771 II. 772 III. 780 IV. 781 V. 786 786 References 786 SUMMARY: Plant natural products are of great value for agriculture, medicine and a wide range of other industrial applications. The discovery of new plant natural product pathways is currently being revolutionized by two key developments. First, breakthroughs in sequencing technology and reduced cost of sequencing are accelerating the ability to find enzymes and pathways for the biosynthesis of new natural products by identifying the underlying genes. Second, there are now multiple examples in which the genes encoding certain natural product pathways have been found to be grouped together in biosynthetic gene clusters within plant genomes. These advances are now making it possible to develop strategies for systematically mining multiple plant genomes for the discovery of new enzymes, pathways and chemistries. Increased knowledge of the features of plant metabolic gene clusters - architecture, regulation and assembly - will be instrumental in expediting natural product discovery. This review summarizes progress in this area. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Analytical considerations for mass spectrometry profiling in serum biomarker discovery.

PubMed

Whiteley, Gordon R; Colantonio, Simona; Sacconi, Andrea; Saul, Richard G

2009-03-01

The potential of using mass spectrometry profiling as a diagnostic tool has been demonstrated for a wide variety of diseases. Various cancers and cancer-related diseases have been the focus of much of this work because of both the paucity of good diagnostic markers and the knowledge that early diagnosis is the most powerful weapon in treating cancer. The implementation of mass spectrometry as a routine diagnostic tool has proved to be difficult, however, primarily because of the stringent controls that are required for the method to be reproducible. The method is evolving as a powerful guide to the discovery of biomarkers that could, in turn, be used either individually or in an array or panel of tests for early disease detection. Using proteomic patterns to guide biomarker discovery and the possibility of deployment in the clinical laboratory environment on current instrumentation or in a hybrid technology has the possibility of being the early diagnosis tool that is needed.

Advanced biological and chemical discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world.

PubMed

Agrafiotis, Dimitris K; Alex, Simson; Dai, Heng; Derkinderen, An; Farnum, Michael; Gates, Peter; Izrailev, Sergei; Jaeger, Edward P; Konstant, Paul; Leung, Albert; Lobanov, Victor S; Marichal, Patrick; Martin, Douglas; Rassokhin, Dmitrii N; Shemanarev, Maxim; Skalkin, Andrew; Stong, John; Tabruyn, Tom; Vermeiren, Marleen; Wan, Jackson; Xu, Xiang Yang; Yao, Xiang

2007-01-01

We present ABCD, an integrated drug discovery informatics platform developed at Johnson & Johnson Pharmaceutical Research & Development, L.L.C. ABCD is an attempt to bridge multiple continents, data systems, and cultures using modern information technology and to provide scientists with tools that allow them to analyze multifactorial SAR and make informed, data-driven decisions. The system consists of three major components: (1) a data warehouse, which combines data from multiple chemical and pharmacological transactional databases, designed for supreme query performance; (2) a state-of-the-art application suite, which facilitates data upload, retrieval, mining, and reporting, and (3) a workspace, which facilitates collaboration and data sharing by allowing users to share queries, templates, results, and reports across project teams, campuses, and other organizational units. Chemical intelligence, performance, and analytical sophistication lie at the heart of the new system, which was developed entirely in-house. ABCD is used routinely by more than 1000 scientists around the world and is rapidly expanding into other functional areas within the J&J organization.

Knowledge Discovery in Textual Documentation: Qualitative and Quantitative Analyses.

ERIC Educational Resources Information Center

Loh, Stanley; De Oliveira, Jose Palazzo M.; Gastal, Fabio Leite

2001-01-01

Presents an application of knowledge discovery in texts (KDT) concerning medical records of a psychiatric hospital. The approach helps physicians to extract knowledge about patients and diseases that may be used for epidemiological studies, for training professionals, and to support physicians to diagnose and evaluate diseases. (Author/AEF)

JAKs and STATs in Immunoregulation and Immune-Mediated Disease

PubMed Central

O’Shea, John J.; Plenge, Robert

2012-01-01

Summary A landmark in cell biology, the discovery of the JAK-STAT pathway provided a simple mechanism for gene regulation that dramatically advanced our understanding of the action of hormones, interferons, colony stimulating factors, and interleukins. As we learn more about the complexities of immune responses, new insights into the functions of this pathway continue to be revealed, aided by technology that permits genomewide views. As we celebrate the 20th anniversary of the discovery of this paradigm in cell signaling, it is particularly edifying to see how this knowledge has rapidly been translated to human immune disease. Not only have genomewide association studies demonstrated that this pathway is highly relevant to human autoimmunity but targeting JAKs is now a reality in immune-mediated disease. PMID:22520847

Malfolded Protein Structure and Proteostasis in Lung Diseases

PubMed Central

Balch, William E.; Sznajder, Jacob I.; Budinger, Scott; Finley, Daniel; Laposky, Aaron D.; Cuervo, Ana Maria; Benjamin, Ivor J.; Barreiro, Esther; Morimoto, Richard I.; Postow, Lisa; Weissman, Allan M.; Gail, Dorothy; Banks-Schlegel, Susan; Croxton, Thomas

2014-01-01

Recent discoveries indicate that disorders of protein folding and degradation play a particularly important role in the development of lung diseases and their associated complications. The overarching purpose of the National Heart, Lung, and Blood Institute workshop on “Malformed Protein Structure and Proteostasis in Lung Diseases” was to identify mechanistic and clinical research opportunities indicated by these recent discoveries in proteostasis science that will advance our molecular understanding of lung pathobiology and facilitate the development of new diagnostic and therapeutic strategies for the prevention and treatment of lung disease. The workshop's discussion focused on identifying gaps in scientific knowledge with respect to proteostasis and lung disease, discussing new research advances and opportunities in protein folding science, and highlighting novel technologies with potential therapeutic applications for diagnosis and treatment. PMID:24033344

Malfolded protein structure and proteostasis in lung diseases.

PubMed

Balch, William E; Sznajder, Jacob I; Budinger, Scott; Finley, Daniel; Laposky, Aaron D; Cuervo, Ana Maria; Benjamin, Ivor J; Barreiro, Esther; Morimoto, Richard I; Postow, Lisa; Weissman, Allan M; Gail, Dorothy; Banks-Schlegel, Susan; Croxton, Thomas; Gan, Weiniu

2014-01-01

Recent discoveries indicate that disorders of protein folding and degradation play a particularly important role in the development of lung diseases and their associated complications. The overarching purpose of the National Heart, Lung, and Blood Institute workshop on "Malformed Protein Structure and Proteostasis in Lung Diseases" was to identify mechanistic and clinical research opportunities indicated by these recent discoveries in proteostasis science that will advance our molecular understanding of lung pathobiology and facilitate the development of new diagnostic and therapeutic strategies for the prevention and treatment of lung disease. The workshop's discussion focused on identifying gaps in scientific knowledge with respect to proteostasis and lung disease, discussing new research advances and opportunities in protein folding science, and highlighting novel technologies with potential therapeutic applications for diagnosis and treatment.

Biosignature Discovery for Substance Use Disorders Using Statistical Learning.

PubMed

Baurley, James W; McMahan, Christopher S; Ervin, Carolyn M; Pardamean, Bens; Bergen, Andrew W

2018-02-01

There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of Discovery, Iteration, and Collaboration in Laboratory Courses on Undergraduates' Research Career Intentions Fully Mediated by Student Ownership.

PubMed

Corwin, Lisa A; Runyon, Christopher R; Ghanem, Eman; Sandy, Moriah; Clark, Greg; Palmer, Gregory C; Reichler, Stuart; Rodenbusch, Stacia E; Dolan, Erin L

2018-06-01

Course-based undergraduate research experiences (CUREs) provide a promising avenue to attract a larger and more diverse group of students into research careers. CUREs are thought to be distinctive in offering students opportunities to make discoveries, collaborate, engage in iterative work, and develop a sense of ownership of their lab course work. Yet how these elements affect students' intentions to pursue research-related careers remain unexplored. To address this knowledge gap, we collected data on three design features thought to be distinctive of CUREs (discovery, iteration, collaboration) and on students' levels of ownership and career intentions from ∼800 undergraduates who had completed CURE or inquiry courses, including courses from the Freshman Research Initiative (FRI), which has a demonstrated positive effect on student retention in college and in science, technology, engineering, and mathematics. We used structural equation modeling to test relationships among the design features and student ownership and career intentions. We found that discovery, iteration, and collaboration had small but significant effects on students' intentions; these effects were fully mediated by student ownership. Students in FRI courses reported significantly higher levels of discovery, iteration, and ownership than students in other CUREs. FRI research courses alone had a significant effect on students' career intentions.

A collaborative filtering-based approach to biomedical knowledge discovery.

PubMed

Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

2018-02-15

The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Building Faculty Capacity through the Learning Sciences

ERIC Educational Resources Information Center

Moy, Elizabeth; O'Sullivan, Gerard; Terlecki, Melissa; Jernstedt, Christian

2014-01-01

Discoveries in the learning sciences (especially in neuroscience) have yielded a rich and growing body of knowledge about how students learn, yet this knowledge is only half of the story. The other half is "know how," i.e. the application of this knowledge. For faculty members, that means applying the discoveries of the learning sciences…

Mathematical Basis of Knowledge Discovery and Autonomous Intelligent Architectures - Technology for the Creation of Virtual objects in the Real World

DTIC Science & Technology

2005-12-14

control of position/orientation of mobile TV cameras. 9 Unit 9 Force interaction system Unit 6 Helmet mounted displays robot like device drive...joints of the master arm (see Unit 1) which joint coordinates are tracked by the virtual manipulator. Unit 6 . Two displays built in the helmet...special device for simulating the tactile- kinaesthetic effect of immersion. When virtual body is a manipulator it comprises: − master arm with 6

Impact of scientific and technological advances.

PubMed

Dragan, I F; Dalessandri, D; Johnson, L A; Tucker, A; Walmsley, A D

2018-03-01

Advancements in research and technology are transforming our world. The dental profession is changing too, in the light of scientific discoveries that are advancing biological technology-from new biomaterials to unravelling the genetic make-up of the human being. As health professionals, we embrace a model of continuous quality improvement and lifelong learning. Our pedagogical approach to incorporating the plethora of scientific-technological advancements calls for us to shift our paradigm from emphasis on skill acquisition to knowledge application. The 2017 ADEE/ADEA workshop provided a forum to explore and discuss strategies to ensure faculty, students and, ultimately, patients are best positioned to exploit the opportunities that arise from integrating new technological advances and research outcomes. Participants discussed methods of incorporating the impact of new technologies and research findings into the education of our dental students. This report serves as a signpost of the way forward and how to promote incorporation of research and technology advances and lifelong learning into the dental education curriculum. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Current Technologies Based on the Knowledge of the Stem Cells Microenvironments.

PubMed

Mawad, Damia; Figtree, Gemma; Gentile, Carmine

2017-01-01

The stem cell microenvironment or niche plays a critical role in the regulation of survival, differentiation and behavior of stem cells and their progenies. Recapitulating each aspect of the stem cell niche is therefore essential for their optimal use in in vitro studies and in vivo as future therapeutics in humans. Engineering of optimal conditions for three-dimensional stem cell culture includes multiple transient and dynamic physiological stimuli, such as blood flow and tissue stiffness. Bioprinting and microfluidics technologies, including organs-on-a-chip, are among the most recent approaches utilized to replicate the three-dimensional stem cell niche for human tissue fabrication that allow the integration of multiple levels of tissue complexity, including blood flow. This chapter focuses on the physico-chemical and genetic cues utilized to engineer the stem cell niche and provides an overview on how both bioprinting and microfluidics technologies are improving our knowledge in this field for both disease modeling and tissue regeneration, including drug discovery and toxicity high-throughput assays and stem cell-based therapies in humans.

Discovery of Implementation Factors That Lead to Technology Adoption in Long-Term Care.

PubMed

Schoville, Rhonda R

2017-10-01

The current exploratory, qualitative study discovered and clarified implementation factors that led to technology adoption in long-term care (LTC). The Integrated Technology Implementation model guided the study of an electronic health record used in three LTC settings. Thirty key stakeholders (i.e., directors of nursing, nurses, and certified nurse aides) participated in focus groups or interviews. Findings indicated experiences were more similar than different among groups and facilities. Five major implementation themes supported by a variety of minor themes were identified. Implications for nursing include that leaders must be knowledgeable and committed to the change and engage staff throughout the implementation process. In addition, various communication and education strategies are required. [Journal of Gerontological Nursing, 43(10), 21-26.]. Copyright 2017, SLACK Incorporated.

Mentor-mentee Relationship: A Win-Win Contract In Graduate Medical Education.

PubMed

Toklu, Hale Z; Fuller, Jacklyn C

2017-12-05

Scholarly activities (i.e., the discovery of new knowledge; development of new technologies, methods, materials, or uses; integration of knowledge leading to new understanding) are intended to measure the quality and quantity of dissemination of knowledge. A successful mentorship program is necessary during residency to help residents achieve the six core competencies (patient care, medical knowledge, practice-based learning and improvement, systems-based practice, professionalism, interpersonal and communication skills) required by the Accreditation Council for Graduate Medical Education (ACGME). The role of the mentor in this process is pivotal in the advancement of the residents' knowledge about evidence-based medicine. With this process, while mentees become more self-regulated, exhibit confidence in their performance, and demonstrate more insight and aptitude in their jobs, mentors also achieve elevated higher self-esteem, enhanced leadership skills, and personal gratification. As such, we may conclude that mentoring is a two-sided relationship; i.e., a 'win-win' style of commitment between the mentor and mentee. Hence, both parties will eventually advance academically, as well as professionally.

The center for causal discovery of biomedical knowledge from big data

PubMed Central

Bahar, Ivet; Becich, Michael J; Benos, Panayiotis V; Berg, Jeremy; Espino, Jeremy U; Glymour, Clark; Jacobson, Rebecca Crowley; Kienholz, Michelle; Lee, Adrian V; Lu, Xinghua; Scheines, Richard

2015-01-01

The Big Data to Knowledge (BD2K) Center for Causal Discovery is developing and disseminating an integrated set of open source tools that support causal modeling and discovery of biomedical knowledge from large and complex biomedical datasets. The Center integrates teams of biomedical and data scientists focused on the refinement of existing and the development of new constraint-based and Bayesian algorithms based on causal Bayesian networks, the optimization of software for efficient operation in a supercomputing environment, and the testing of algorithms and software developed using real data from 3 representative driving biomedical projects: cancer driver mutations, lung disease, and the functional connectome of the human brain. Associated training activities provide both biomedical and data scientists with the knowledge and skills needed to apply and extend these tools. Collaborative activities with the BD2K Consortium further advance causal discovery tools and integrate tools and resources developed by other centers. PMID:26138794

FY10 Engineering Innovations, Research and Technology Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lane, M A; Aceves, S M; Paulson, C N

This report summarizes key research, development, and technology advancements in Lawrence Livermore National Laboratory's Engineering Directorate for FY2010. These efforts exemplify Engineering's nearly 60-year history of developing and applying the technology innovations needed for the Laboratory's national security missions, and embody Engineering's mission to ''Enable program success today and ensure the Laboratory's vitality tomorrow.'' Leading off the report is a section featuring compelling engineering innovations. These innovations range from advanced hydrogen storage that enables clean vehicles, to new nuclear material detection technologies, to a landmine detection system using ultra-wideband ground-penetrating radar. Many have been recognized with R&D Magazine's prestigious R&Dmore » 100 Award; all are examples of the forward-looking application of innovative engineering to pressing national problems and challenging customer requirements. Engineering's capability development strategy includes both fundamental research and technology development. Engineering research creates the competencies of the future where discovery-class groundwork is required. Our technology development (or reduction to practice) efforts enable many of the research breakthroughs across the Laboratory to translate from the world of basic research to the national security missions of the Laboratory. This portfolio approach produces new and advanced technological capabilities, and is a unique component of the value proposition of the Lawrence Livermore Laboratory. The balance of the report highlights this work in research and technology, organized into thematic technical areas: Computational Engineering; Micro/Nano-Devices and Structures; Measurement Technologies; Engineering Systems for Knowledge Discovery; and Energy Manipulation. Our investments in these areas serve not only known programmatic requirements of today and tomorrow, but also anticipate the breakthrough engineering innovations that will be needed in the future.« less

Mississippi Curriculum Framework for Technology Discovery (9th Grade). CIP: 00.0253.

ERIC Educational Resources Information Center

Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

This document, which is intended for technology educators in Mississippi, outlines a technology discovery course in which a modular instruction approach allows ninth graders to experience various workplace technologies within four career cluster areas: agriculture/natural resources technology, business/marketing technology, health/human services…

The Effect of Rules and Discovery in the Retention and Retrieval of Braille Inkprint Letter Pairs.

ERIC Educational Resources Information Center

Nagengast, Daniel L.; And Others

The effects of rule knowledge were investigated using Braille inkprint pairs. Both recognition and recall were studied in three groups of subjects: rule knowledge, rule discovery, and no rule. Two hypotheses were tested: (1) that the group exposed to the rule would score better than would a discovery group and a control group; and (2) that all…

Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

PubMed

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.

Towards microfluidic technology-based MALDI-MS platforms for drug discovery: a review.

PubMed

Winkle, Richard F; Nagy, Judit M; Cass, Anthony Eg; Sharma, Sanjiv

2008-11-01

Microfluidic methods have found applications in various disciplines. It has been predicted that the microfluidic technology would be useful in performing routine steps in drug discovery ranging from target identification to lead optimisation in which the number of compounds evaluated in this regard determines the success of combinatorial screening. The sheer size of the parameter space that can be explored often poses an enormous challenge. We set out to find how close we are towards the use of integrated matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) microfluidic systems for drug discovery. In this article we review the latest applications of microfluidic technology in the area of MALDI-MS and drug discovery. Our literature survey revealed microfluidic technologies-based approaches for various stages of drug discovery; however, they are in still in developmental stages. Furthermore, we speculate on how these technologies could be used in the future.

Discovering Knowledge from AIS Database for Application in VTS

NASA Astrophysics Data System (ADS)

Tsou, Ming-Cheng

The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

Academic College of Emergency Experts in India's INDO-US Joint Working Group and OPUS12 Foundation Consensus Statement on Creating A Coordinated, Multi-Disciplinary, Patient-Centered, Global Point-of-Care Biomarker Discovery Network.

PubMed

Stawicki, Stanislaw P; Stoltzfus, Jill C; Aggarwal, Praveen; Bhoi, Sanjeev; Bhatt, Shashi; Kalra, O P; Bhalla, Ashish; Hoey, Brian A; Galwankar, Sagar C; Paladino, Lorenzo; Papadimos, Thomas J

2014-07-01

Biomarker science brings great promise to clinical medicine. This is especially true in the era of technology miniaturization, rapid dissemination of knowledge, and point-of-care (POC) implementation of novel diagnostics. Despite this tremendous progress, the journey from a candidate biomarker to a scientifically validated biomarker continues to be an arduous one. In addition to substantial financial resources, biomarker research requires considerable expertise and a multidisciplinary approach. Investigational designs must also be taken into account, with the randomized controlled trial remaining the "gold standard". The authors present a condensed overview of biomarker science and associated investigational methods, followed by specific examples from clinical areas where biomarker development and/or implementation resulted in tangible enhancements in patient care. This manuscript also serves as a call to arms for the establishment of a truly global, well-coordinated infrastructure dedicated to biomarker research and development, with focus on delivery of the latest discoveries directly to the patient via point-of-care technology.

Surgical data science: The new knowledge domain

PubMed Central

Vedula, S. Swaroop; Hager, Gregory D.

2017-01-01

Healthcare in general, and surgery/interventional care in particular, is evolving through rapid advances in technology and increasing complexity of care with the goal of maximizing quality and value of care. While innovations in diagnostic and therapeutic technologies have driven past improvements in quality of surgical care, future transformation in care will be enabled by data. Conventional methodologies, such as registry studies, are limited in their scope for discovery and research, extent and complexity of data, breadth of analytic techniques, and translation or integration of research findings into patient care. We foresee the emergence of Surgical/Interventional Data Science (SDS) as a key element to addressing these limitations and creating a sustainable path toward evidence-based improvement of interventional healthcare pathways. SDS will create tools to measure, model and quantify the pathways or processes within the context of patient health states or outcomes, and use information gained to inform healthcare decisions, guidelines, best practices, policy, and training, thereby improving the safety and quality of healthcare and its value. Data is pervasive throughout the surgical care pathway; thus, SDS can impact various aspects of care including prevention, diagnosis, intervention, or post-operative recovery. Existing literature already provides preliminary results suggesting how a data science approach to surgical decision-making could more accurately predict severe complications using complex data from pre-, intra-, and post-operative contexts, how it could support intra-operative decision-making using both existing knowledge and continuous data streams throughout the surgical care pathway, and how it could enable effective collaboration between human care providers and intelligent technologies. In addition, SDS is poised to play a central role in surgical education, for example, through objective assessments, automated virtual coaching, and robot-assisted active learning of surgical skill. However, the potential for transforming surgical care and training through SDS may only be realized through a cultural shift that not only institutionalizes technology to seamlessly capture data but also assimilates individuals with expertise in data science into clinical research teams. Furthermore, collaboration with industry partners from the inception of the discovery process promotes optimal design of data products as well as their efficient translation and commercialization. As surgery continues to evolve through advances in technology that enhance delivery of care, SDS represents a new knowledge domain to engineer surgical care of the future. PMID:28936475

Surgical data science: The new knowledge domain.

PubMed

Vedula, S Swaroop; Hager, Gregory D

2017-04-01

Healthcare in general, and surgery/interventional care in particular, is evolving through rapid advances in technology and increasing complexity of care with the goal of maximizing quality and value of care. While innovations in diagnostic and therapeutic technologies have driven past improvements in quality of surgical care, future transformation in care will be enabled by data. Conventional methodologies, such as registry studies, are limited in their scope for discovery and research, extent and complexity of data, breadth of analytic techniques, and translation or integration of research findings into patient care. We foresee the emergence of Surgical/Interventional Data Science (SDS) as a key element to addressing these limitations and creating a sustainable path toward evidence-based improvement of interventional healthcare pathways. SDS will create tools to measure, model and quantify the pathways or processes within the context of patient health states or outcomes, and use information gained to inform healthcare decisions, guidelines, best practices, policy, and training, thereby improving the safety and quality of healthcare and its value. Data is pervasive throughout the surgical care pathway; thus, SDS can impact various aspects of care including prevention, diagnosis, intervention, or post-operative recovery. Existing literature already provides preliminary results suggesting how a data science approach to surgical decision-making could more accurately predict severe complications using complex data from pre-, intra-, and post-operative contexts, how it could support intra-operative decision-making using both existing knowledge and continuous data streams throughout the surgical care pathway, and how it could enable effective collaboration between human care providers and intelligent technologies. In addition, SDS is poised to play a central role in surgical education, for example, through objective assessments, automated virtual coaching, and robot-assisted active learning of surgical skill. However, the potential for transforming surgical care and training through SDS may only be realized through a cultural shift that not only institutionalizes technology to seamlessly capture data but also assimilates individuals with expertise in data science into clinical research teams. Furthermore, collaboration with industry partners from the inception of the discovery process promotes optimal design of data products as well as their efficient translation and commercialization. As surgery continues to evolve through advances in technology that enhance delivery of care, SDS represents a new knowledge domain to engineer surgical care of the future.

Modern drug discovery technologies: opportunities and challenges in lead discovery.

PubMed

Guido, Rafael V C; Oliva, Glaucius; Andricopulo, Adriano D

2011-12-01

The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets. Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges.

STEM Girls Night In at Goddard

NASA Image and Video Library

2016-11-05

Girls Night In was held at Goddard on Nov 4-5, 2016. This is a pilot program which reinvigorates, inspires, and engages high school girls who may be struggling or not fully engaged in STEM (Science, Technology Engineering and Math) education. The program allowed NASA women to share and demonstrate the work they do, provide the girls an opportunity to completely immerse themselves in Goddard science, technology, engineering and math as well as provide them activities that will challenge and promote knowledge and discovery. Goddard invites other NASA centers tolearn from this pilot program and work towards a simultaneous multicenter event in the future. Participating schools were: DuVal, Crossland, Flowers, High Point, Northwestern and Oxon Hill

STEM Girls Night In at Goddard

NASA Image and Video Library

2016-11-04

Girls Night In was held at Goddard on Nov 4-5, 2016. This is a pilot program which reinvigorates, inspires, and engages high school girls who may be struggling or not fully engaged in STEM (Science, Technology Engineering and Math) education. The program allowed NASA women to share and demonstrate the work they do, provide the girls an opportunity to completely immerse themselves in Goddard science, technology, engineering and math as well as provide them activities that will challenge and promote knowledge and discovery. Goddard invites other NASA centers tolearn from this pilot program and work towards a simultaneous multicenter event in the future. Participating schools were: DuVal, Crossland, Flowers, High Point, Northwestern and Oxon Hill

Application of Ontologies for Big Earth Data

NASA Astrophysics Data System (ADS)

Huang, T.; Chang, G.; Armstrong, E. M.; Boening, C.

2014-12-01

Connected data is smarter data! Earth Science research infrastructure must do more than just being able to support temporal, geospatial discovery of satellite data. As the Earth Science data archives continue to expand across NASA data centers, the research communities are demanding smarter data services. A successful research infrastructure must be able to present researchers the complete picture, that is, datasets with linked citations, related interdisciplinary data, imageries, current events, social media discussions, and scientific data tools that are relevant to the particular dataset. The popular Semantic Web for Earth and Environmental Terminology (SWEET) ontologies is a collection of ontologies and concepts designed to improve discovery and application of Earth Science data. The SWEET ontologies collection was initially developed to capture the relationships between keywords in the NASA Global Change Master Directory (GCMD). Over the years this popular ontologies collection has expanded to cover over 200 ontologies and 6000 concepts to enable scalable classification of Earth system science concepts and Space science. This presentation discusses the semantic web technologies as the enabling technology for data-intensive science. We will discuss the application of the SWEET ontologies as a critical component in knowledge-driven research infrastructure for some of the recent projects, which include the DARPA Ontological System for Context Artifact and Resources (OSCAR), 2013 NASA ACCESS Virtual Quality Screening Service (VQSS), and the 2013 NASA Sea Level Change Portal (SLCP) projects. The presentation will also discuss the benefits in using semantic web technologies in developing research infrastructure for Big Earth Science Data in an attempt to "accommodate all domains and provide the necessary glue for information to be cross-linked, correlated, and discovered in a semantically rich manner." [1] [1] Savas Parastatidis: A platform for all that we know: creating a knowledge-driven research infrastructure. The Fourth Paradigm 2009: 165-172

Concept Formation in Scientific Knowledge Discovery from a Constructivist View

NASA Astrophysics Data System (ADS)

Peng, Wei; Gero, John S.

The central goal of scientific knowledge discovery is to learn cause-effect relationships among natural phenomena presented as variables and the consequences their interactions. Scientific knowledge is normally expressed as scientific taxonomies and qualitative and quantitative laws [1]. This type of knowledge represents intrinsic regularities of the observed phenomena that can be used to explain and predict behaviors of the phenomena. It is a generalization that is abstracted and externalized from a set of contexts and applicable to a broader scope. Scientific knowledge is a type of third-person knowledge, i.e., knowledge that independent of a specific enquirer. Artificial intelligence approaches, particularly data mining algorithms that are used to identify meaningful patterns from large data sets, are approaches that aim to facilitate the knowledge discovery process [2]. A broad spectrum of algorithms has been developed in addressing classification, associative learning, and clustering problems. However, their linkages to people who use them have not been adequately explored. Issues in relation to supporting the interpretation of the patterns, the application of prior knowledge to the data mining process and addressing user interactions remain challenges for building knowledge discovery tools [3]. As a consequence, scientists rely on their experience to formulate problems, evaluate hypotheses, reason about untraceable factors and derive new problems. This type of knowledge which they have developed during their career is called “first-person” knowledge. The formation of scientific knowledge (third-person knowledge) is highly influenced by the enquirer’s first-person knowledge construct, which is a result of his or her interactions with the environment. There have been attempts to craft automatic knowledge discovery tools but these systems are limited in their capabilities to handle the dynamics of personal experience. There are now trends in developing approaches to assist scientists applying their expertise to model formation, simulation, and prediction in various domains [4], [5]. On the other hand, first-person knowledge becomes third-person theory only if it proves general by evidence and is acknowledged by a scientific community. Researchers start to focus on building interactive cooperation platforms [1] to accommodate different views into the knowledge discovery process. There are some fundamental questions in relation to scientific knowledge development. What aremajor components for knowledge construction and how do people construct their knowledge? How is this personal construct assimilated and accommodated into a scientific paradigm? How can one design a computational system to facilitate these processes? This chapter does not attempt to answer all these questions but serves as a basis to foster thinking along this line. A brief literature review about how people develop their knowledge is carried out through a constructivist view. A hydrological modeling scenario is presented to elucidate the approach.

Concept Formation in Scientific Knowledge Discovery from a Constructivist View

NASA Astrophysics Data System (ADS)

Peng, Wei; Gero, John S.

The central goal of scientific knowledge discovery is to learn cause-effect relationships among natural phenomena presented as variables and the consequences their interactions. Scientific knowledge is normally expressed as scientific taxonomies and qualitative and quantitative laws [1]. This type of knowledge represents intrinsic regularities of the observed phenomena that can be used to explain and predict behaviors of the phenomena. It is a generalization that is abstracted and externalized from a set of contexts and applicable to a broader scope. Scientific knowledge is a type of third-person knowledge, i.e., knowledge that independent of a specific enquirer. Artificial intelligence approaches, particularly data mining algorithms that are used to identify meaningful patterns from large data sets, are approaches that aim to facilitate the knowledge discovery process [2]. A broad spectrum of algorithms has been developed in addressing classification, associative learning, and clustering problems. However, their linkages to people who use them have not been adequately explored. Issues in relation to supporting the interpretation of the patterns, the application of prior knowledge to the data mining process and addressing user interactions remain challenges for building knowledge discovery tools [3]. As a consequence, scientists rely on their experience to formulate problems, evaluate hypotheses, reason about untraceable factors and derive new problems. This type of knowledge which they have developed during their career is called "first-person" knowledge. The formation of scientific knowledge (third-person knowledge) is highly influenced by the enquirer's first-person knowledge construct, which is a result of his or her interactions with the environment. There have been attempts to craft automatic knowledge discovery tools but these systems are limited in their capabilities to handle the dynamics of personal experience. There are now trends in developing approaches to assist scientists applying their expertise to model formation, simulation, and prediction in various domains [4], [5]. On the other hand, first-person knowledge becomes third-person theory only if it proves general by evidence and is acknowledged by a scientific community. Researchers start to focus on building interactive cooperation platforms [1] to accommodate different views into the knowledge discovery process. There are some fundamental questions in relation to scientific knowledge development. What aremajor components for knowledge construction and how do people construct their knowledge? How is this personal construct assimilated and accommodated into a scientific paradigm? How can one design a computational system to facilitate these processes? This chapter does not attempt to answer all these questions but serves as a basis to foster thinking along this line. A brief literature review about how people develop their knowledge is carried out through a constructivist view. A hydrological modeling scenario is presented to elucidate the approach.

"Seeing is believing": perspectives of applying imaging technology in discovery toxicology.

PubMed

Xu, Jinghai James; Dunn, Margaret Condon; Smith, Arthur Russell

2009-11-01

Efficiency and accuracy in addressing drug safety issues proactively are critical in minimizing late-stage drug attritions. Discovery toxicology has become a specialty subdivision of toxicology seeking to effectively provide early predictions and safety assessment in the drug discovery process. Among the many technologies utilized to select safer compounds for further development, in vitro imaging technology is one of the best characterized and validated to provide translatable biomarkers towards clinically-relevant outcomes of drug safety. By carefully applying imaging technologies in genetic, hepatic, and cardiac toxicology, and integrating them with the rest of the drug discovery processes, it was possible to demonstrate significant impact of imaging technology on drug research and development and substantial returns on investment.

Knowledge Discovery and Data Mining: An Overview

NASA Technical Reports Server (NTRS)

Fayyad, U.

1995-01-01

The process of knowledge discovery and data mining is the process of information extraction from very large databases. Its importance is described along with several techniques and considerations for selecting the most appropriate technique for extracting information from a particular data set.

12 CFR 263.53 - Discovery depositions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 4 2014-01-01 2014-01-01 false Discovery depositions. 263.53 Section 263.53... Discovery depositions. (a) In general. In addition to the discovery permitted in subpart A of this part, limited discovery by means of depositions shall be allowed for individuals with knowledge of facts...

12 CFR 263.53 - Discovery depositions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 4 2012-01-01 2012-01-01 false Discovery depositions. 263.53 Section 263.53... Discovery depositions. (a) In general. In addition to the discovery permitted in subpart A of this part, limited discovery by means of depositions shall be allowed for individuals with knowledge of facts...

Big data in healthcare - the promises, challenges and opportunities from a research perspective: A case study with a model database.

PubMed

Adibuzzaman, Mohammad; DeLaurentis, Poching; Hill, Jennifer; Benneyworth, Brian D

2017-01-01

Recent advances in data collection during routine health care in the form of Electronic Health Records (EHR), medical device data (e.g., infusion pump informatics, physiological monitoring data, and insurance claims data, among others, as well as biological and experimental data, have created tremendous opportunities for biological discoveries for clinical application. However, even with all the advancement in technologies and their promises for discoveries, very few research findings have been translated to clinical knowledge, or more importantly, to clinical practice. In this paper, we identify and present the initial work addressing the relevant challenges in three broad categories: data, accessibility, and translation. These issues are discussed in the context of a widely used detailed database from an intensive care unit, Medical Information Mart for Intensive Care (MIMIC III) database.

Novel therapeutic approaches: Rett syndrome and human induced pluripotent stem cell technology

PubMed Central

Gomathi, Mohan

2017-01-01

Recent advances in induced pluripotent stem cell (iPSC) technology target screening and discovering of therapeutic agents for the possible cure of human diseases. Human induced pluripotent stem cells (hiPSC) are the right kind of platform for testing potency of specific active compounds. Ayurveda, the Indian traditional system of medicine developed between 2,500 and 500 BC, is a science involving the intelligent formulations of herbs and minerals. It can serve as a “goldmine” for novel neuroprotective agents used for centuries to treat neurological disorders. This review discusses limitations in screening drugs for neurological disorders and the advantages offered by hiPSC integrated with Indian traditional system of medicine. We begin by describing the current state of hiPSC technology in research on Rett syndrome (RTT) followed by the current controversies in RTT research combined with the emergence of patient-specific hiPSC that indicate an urgent need for researchers to understand the etiology and drug mechanism. We conclude by offering recommendations to reinforce the screening of active compounds present in the ayurvedic medicines using the human induced pluripotent neural model system for research involving drug discovery for RTT. This integrative approach will fill the current knowledge gap in the traditional medicines and drug discovery. PMID:28447035

Global Health Innovation Technology Models.

PubMed

Harding, Kimberly

2016-01-01

Chronic technology and business process disparities between High Income, Low Middle Income and Low Income (HIC, LMIC, LIC) research collaborators directly prevent the growth of sustainable Global Health innovation for infectious and rare diseases. There is a need for an Open Source-Open Science Architecture Framework to bridge this divide. We are proposing such a framework for consideration by the Global Health community, by utilizing a hybrid approach of integrating agnostic Open Source technology and healthcare interoperability standards and Total Quality Management principles. We will validate this architecture framework through our programme called Project Orchid. Project Orchid is a conceptual Clinical Intelligence Exchange and Virtual Innovation platform utilizing this approach to support clinical innovation efforts for multi-national collaboration that can be locally sustainable for LIC and LMIC research cohorts. The goal is to enable LIC and LMIC research organizations to accelerate their clinical trial process maturity in the field of drug discovery, population health innovation initiatives and public domain knowledge networks. When sponsored, this concept will be tested by 12 confirmed clinical research and public health organizations in six countries. The potential impact of this platform is reduced drug discovery and public health innovation lag time and improved clinical trial interventions, due to reliable clinical intelligence and bio-surveillance across all phases of the clinical innovation process.

Global Health Innovation Technology Models

PubMed Central

Harding, Kimberly

2016-01-01

Chronic technology and business process disparities between High Income, Low Middle Income and Low Income (HIC, LMIC, LIC) research collaborators directly prevent the growth of sustainable Global Health innovation for infectious and rare diseases. There is a need for an Open Source-Open Science Architecture Framework to bridge this divide. We are proposing such a framework for consideration by the Global Health community, by utilizing a hybrid approach of integrating agnostic Open Source technology and healthcare interoperability standards and Total Quality Management principles. We will validate this architecture framework through our programme called Project Orchid. Project Orchid is a conceptual Clinical Intelligence Exchange and Virtual Innovation platform utilizing this approach to support clinical innovation efforts for multi-national collaboration that can be locally sustainable for LIC and LMIC research cohorts. The goal is to enable LIC and LMIC research organizations to accelerate their clinical trial process maturity in the field of drug discovery, population health innovation initiatives and public domain knowledge networks. When sponsored, this concept will be tested by 12 confirmed clinical research and public health organizations in six countries. The potential impact of this platform is reduced drug discovery and public health innovation lag time and improved clinical trial interventions, due to reliable clinical intelligence and bio-surveillance across all phases of the clinical innovation process.

Energy-Water Nexus Knowledge Discovery Framework

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Foster, I.; Chandola, V.; Chen, B.; Sanyal, J.; Allen, M.; McManamay, R.

2017-12-01

As demand for energy grows, the energy sector is experiencing increasing competition for water. With increasing population and changing environmental, socioeconomic scenarios, new technology and investment decisions must be made for optimized and sustainable energy-water resource management. This requires novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales. An integrated data driven modeling, analysis, and visualization capability is needed to understand, design, and develop efficient local and regional practices for the energy-water infrastructure components that can be guided with strategic (federal) policy decisions to ensure national energy resilience. To meet this need of the energy-water nexus (EWN) community, an Energy-Water Knowledge Discovery Framework (EWN-KDF) is being proposed to accomplish two objectives: Development of a robust data management and geovisual analytics platform that provides access to disparate and distributed physiographic, critical infrastructure, and socioeconomic data, along with emergent ad-hoc sensor data to provide a powerful toolkit of analysis algorithms and compute resources to empower user-guided data analysis and inquiries; and Demonstration of knowledge generation with selected illustrative use cases for the implications of climate variability for coupled land-water-energy systems through the application of state-of-the art data integration, analysis, and synthesis. Oak Ridge National Laboratory (ORNL), in partnership with Argonne National Laboratory (ANL) and researchers affiliated with the Center for International Earth Science Information Partnership (CIESIN) at Columbia University and State University of New York-Buffalo (SUNY), propose to develop this Energy-Water Knowledge Discovery Framework to generate new, critical insights regarding the complex dynamics of the EWN and its interactions with climate variability and change. An overarching objective of this project is to integrate impacts, adaptation, and vulnerability (IAV) science with emerging data science to meet the data analysis needs of the U.S. Department of Energy and partner federal agencies with respect to the EWN.

Systems Engineering Using Heritage Spacecraft Technology: Lessons Learned from Discovery and New Frontiers Deep Space Missions

NASA Technical Reports Server (NTRS)

Barley, Bryan; Newhouse, Marilyn; Clardy, Dennon

2011-01-01

In the design and development of complex spacecraft missions, project teams frequently assume the use of advanced technology or heritage systems to enable a mission or reduce the overall mission risk and cost. As projects proceed through the development life cycle, increasingly detailed knowledge of the advanced or heritage systems and the system environment identifies unanticipated issues that result in cost overruns or schedule impacts. The Discovery & New Frontiers (D&NF) Program Office recently studied cost overruns and schedule delays resulting from advanced technology or heritage assumptions for 6 D&NF missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that the cost and schedule growth did not result from technical hurdles requiring significant technology development. Instead, systems engineering processes did not identify critical issues early enough in the design cycle to ensure project schedules and estimated costs address the inherent risks. In general, the overruns were traceable to: inadequate understanding of the heritage system s behavior within the proposed spacecraft design and mission environment; an insufficient level of experience with the heritage system; or an inadequate scoping of the system-wide impacts necessary to implement the heritage or advanced technology. This presentation summarizes the study s findings and offers suggestions for improving the project s ability to identify and manage the risks inherent in the technology and heritage design solution.

Data Mining.

ERIC Educational Resources Information Center

Benoit, Gerald

2002-01-01

Discusses data mining (DM) and knowledge discovery in databases (KDD), taking the view that KDD is the larger view of the entire process, with DM emphasizing the cleaning, warehousing, mining, and visualization of knowledge discovery in databases. Highlights include algorithms; users; the Internet; text mining; and information extraction.…

Early repositioning through compound set enrichment analysis: a knowledge-recycling strategy.

PubMed

Temesi, Gergely; Bolgár, Bence; Arany, Adám; Szalai, Csaba; Antal, Péter; Mátyus, Péter

2014-04-01

Despite famous serendipitous drug repositioning success stories, systematic projects have not yet delivered the expected results. However, repositioning technologies are gaining ground in different phases of routine drug development, together with new adaptive strategies. We demonstrate the power of the compound information pool, the ever-growing heterogeneous information repertoire of approved drugs and candidates as an invaluable catalyzer in this transition. Systematic, computational utilization of this information pool for candidates in early phases is an open research problem; we propose a novel application of the enrichment analysis statistical framework for fusion of this information pool, specifically for the prediction of indications. Pharmaceutical consequences are formulated for a systematic and continuous knowledge recycling strategy, utilizing this information pool throughout the drug-discovery pipeline.

Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

PubMed

Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

2009-01-01

In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

The development of high-content screening (HCS) technology and its importance to drug discovery.

PubMed

Fraietta, Ivan; Gasparri, Fabio

2016-01-01

High-content screening (HCS) was introduced about twenty years ago as a promising analytical approach to facilitate some critical aspects of drug discovery. Its application has spread progressively within the pharmaceutical industry and academia to the point that it today represents a fundamental tool in supporting drug discovery and development. Here, the authors review some of significant progress in the HCS field in terms of biological models and assay readouts. They highlight the importance of high-content screening in drug discovery, as testified by its numerous applications in a variety of therapeutic areas: oncology, infective diseases, cardiovascular and neurodegenerative diseases. They also dissect the role of HCS technology in different phases of the drug discovery pipeline: target identification, primary compound screening, secondary assays, mechanism of action studies and in vitro toxicology. Recent advances in cellular assay technologies, such as the introduction of three-dimensional (3D) cultures, induced pluripotent stem cells (iPSCs) and genome editing technologies (e.g., CRISPR/Cas9), have tremendously expanded the potential of high-content assays to contribute to the drug discovery process. Increasingly predictive cellular models and readouts, together with the development of more sophisticated and affordable HCS readers, will further consolidate the role of HCS technology in drug discovery.

The BRAIN Initiative: developing technology to catalyse neuroscience discovery.

PubMed

Jorgenson, Lyric A; Newsome, William T; Anderson, David J; Bargmann, Cornelia I; Brown, Emery N; Deisseroth, Karl; Donoghue, John P; Hudson, Kathy L; Ling, Geoffrey S F; MacLeish, Peter R; Marder, Eve; Normann, Richard A; Sanes, Joshua R; Schnitzer, Mark J; Sejnowski, Terrence J; Tank, David W; Tsien, Roger Y; Ugurbil, Kamil; Wingfield, John C

2015-05-19

The evolution of the field of neuroscience has been propelled by the advent of novel technological capabilities, and the pace at which these capabilities are being developed has accelerated dramatically in the past decade. Capitalizing on this momentum, the United States launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to develop and apply new tools and technologies for revolutionizing our understanding of the brain. In this article, we review the scientific vision for this initiative set forth by the National Institutes of Health and discuss its implications for the future of neuroscience research. Particular emphasis is given to its potential impact on the mapping and study of neural circuits, and how this knowledge will transform our understanding of the complexity of the human brain and its diverse array of behaviours, perceptions, thoughts and emotions.

The BRAIN Initiative: developing technology to catalyse neuroscience discovery

PubMed Central

Jorgenson, Lyric A.; Newsome, William T.; Anderson, David J.; Bargmann, Cornelia I.; Brown, Emery N.; Deisseroth, Karl; Donoghue, John P.; Hudson, Kathy L.; Ling, Geoffrey S. F.; MacLeish, Peter R.; Marder, Eve; Normann, Richard A.; Sanes, Joshua R.; Schnitzer, Mark J.; Sejnowski, Terrence J.; Tank, David W.; Tsien, Roger Y.; Ugurbil, Kamil; Wingfield, John C.

2015-01-01

The evolution of the field of neuroscience has been propelled by the advent of novel technological capabilities, and the pace at which these capabilities are being developed has accelerated dramatically in the past decade. Capitalizing on this momentum, the United States launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to develop and apply new tools and technologies for revolutionizing our understanding of the brain. In this article, we review the scientific vision for this initiative set forth by the National Institutes of Health and discuss its implications for the future of neuroscience research. Particular emphasis is given to its potential impact on the mapping and study of neural circuits, and how this knowledge will transform our understanding of the complexity of the human brain and its diverse array of behaviours, perceptions, thoughts and emotions. PMID:25823863

Chemical Informatics and the Drug Discovery Knowledge Pyramid

PubMed Central

Lushington, Gerald H.; Dong, Yinghua; Theertham, Bhargav

2012-01-01

The magnitude of the challenges in preclinical drug discovery is evident in the large amount of capital invested in such efforts in pursuit of a small static number of eventually successful marketable therapeutics. An explosion in the availability of potentially drug-like compounds and chemical biology data on these molecules can provide us with the means to improve the eventual success rates for compounds being considered at the preclinical level, but only if the community is able to access available information in an efficient and meaningful way. Thus, chemical database resources are critical to any serious drug discovery effort. This paper explores the basic principles underlying the development and implementation of chemical databases, and examines key issues of how molecular information may be encoded within these databases so as to enhance the likelihood that users will be able to extract meaningful information from data queries. In addition to a broad survey of conventional data representation and query strategies, key enabling technologies such as new context-sensitive chemical similarity measures and chemical cartridges are examined, with recommendations on how such resources may be integrated into a practical database environment. PMID:23782037

The Expanding Diversity of Mycobacterium tuberculosis Drug Targets.

PubMed

Wellington, Samantha; Hung, Deborah T

2018-05-11

After decades of relative inactivity, a large increase in efforts to discover antitubercular therapeutics has brought insights into the biology of Mycobacterium tuberculosis (Mtb) and promising new drugs such as bedaquiline, which inhibits ATP synthase, and the nitroimidazoles delamanid and pretomanid, which inhibit both mycolic acid synthesis and energy production. Despite these advances, the drug discovery pipeline remains underpopulated. The field desperately needs compounds with novel mechanisms of action capable of inhibiting multi- and extensively drug -resistant Mtb (M/XDR-TB) and, potentially, nonreplicating Mtb with the hope of shortening the duration of required therapy. New knowledge about Mtb, along with new methods and technologies, has driven exploration into novel target areas, such as energy production and central metabolism, that diverge from the classical targets in macromolecular synthesis. Here, we review new small molecule drug candidates that act on these novel targets to highlight the methods and perspectives advancing the field. These new targets bring with them the aspiration of shortening treatment duration as well as a pipeline of effective regimens against XDR-TB, positioning Mtb drug discovery to become a model for anti-infective discovery.

Resource Discovery within the Networked "Hybrid" Library.

ERIC Educational Resources Information Center

Leigh, Sally-Anne

This paper focuses on the development, adoption, and integration of resource discovery, knowledge management, and/or knowledge sharing interfaces such as interactive portals, and the use of the library's World Wide Web presence to increase the availability and usability of information services. The introduction addresses changes in library…

A biological compression model and its applications.

PubMed

Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

2011-01-01

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

Opportunities and challenges of current electrophysiology research: a plea to establish 'translational electrophysiology' curricula.

PubMed

Lau, Dennis H; Volders, Paul G A; Kohl, Peter; Prinzen, Frits W; Zaza, Antonio; Kääb, Stefan; Oto, Ali; Schotten, Ulrich

2015-05-01

Cardiac electrophysiology has evolved into an important subspecialty in cardiovascular medicine. This is in part due to the significant advances made in our understanding and treatment of heart rhythm disorders following more than a century of scientific discoveries and research. More recently, the rapid development of technology in cellular electrophysiology, molecular biology, genetics, computer modelling, and imaging have led to the exponential growth of knowledge in basic cardiac electrophysiology. The paradigm of evidence-based medicine has led to a more comprehensive decision-making process and most likely to improved outcomes in many patients. However, implementing relevant basic research knowledge in a system of evidence-based medicine appears to be challenging. Furthermore, the current economic climate and the restricted nature of research funding call for improved efficiency of translation from basic discoveries to healthcare delivery. Here, we aim to (i) appraise the broad challenges of translational research in cardiac electrophysiology, (ii) highlight the need for improved strategies in the training of translational electrophysiologists, and (iii) discuss steps towards building a favourable translational research environment and culture. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

Adventure into space.

PubMed

Burbidge, E M

1983-07-29

The exploration of the universe has captured mankind's interest since the earliest attempts to understand the sun, moon, planets, comets, and stars. The last few decades have seen explosive advances of knowledge, sparked by technological advances and by our entry into the space age. Achievements in solar system exploration, discoveries both in the Milky Way and in the farther universe, and challenges for the future are discussed. Of major concern worldwide is the need for people of goodwill in all nations to concentrate on the peaceful uses of outer space and on international collaboration.

KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain

PubMed Central

2013-01-01

Background Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. Results A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. Conclusions The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework. PMID:23763826

KNODWAT: a scientific framework application for testing knowledge discovery methods for the biomedical domain.

PubMed

Holzinger, Andreas; Zupan, Mario

2013-06-13

Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework.

Citizen Science Initiatives: Engaging the Public and Demystifying Science

PubMed Central

Van Vliet, Kim; Moore, Claybourne

2016-01-01

The Internet and smart phone technologies have opened up new avenues for collaboration among scientists around the world. These technologies have also expanded citizen science opportunities and public participation in scientific research (PPSR). Here we discuss citizen science, what it is, who does it, and the variety of projects and methods used to increase scientific knowledge and scientific literacy. We describe a number of different types of citizen-science projects. These greatly increase the number of people involved, helping to speed the pace of data analysis and allowing science to advance more rapidly. As a result of the numerous advantages of citizen-science projects, these opportunities are likely to expand in the future and increase the rate of novel discoveries. PMID:27047582

Citizen Science Initiatives: Engaging the Public and Demystifying Science.

PubMed

Van Vliet, Kim; Moore, Claybourne

2016-03-01

The Internet and smart phone technologies have opened up new avenues for collaboration among scientists around the world. These technologies have also expanded citizen science opportunities and public participation in scientific research (PPSR). Here we discuss citizen science, what it is, who does it, and the variety of projects and methods used to increase scientific knowledge and scientific literacy. We describe a number of different types of citizen-science projects. These greatly increase the number of people involved, helping to speed the pace of data analysis and allowing science to advance more rapidly. As a result of the numerous advantages of citizen-science projects, these opportunities are likely to expand in the future and increase the rate of novel discoveries.

Evaluation of solar electric propulsion technologies for discovery class missions

NASA Technical Reports Server (NTRS)

Oh, David Y.

2005-01-01

A detailed study examines the potential benefits that advanced electric propulsion (EP) technologies offer to the cost-capped missions in NASA's Discovery program. The study looks at potential cost and performance benefits provided by three EP technologies that are currently in development: NASA's Evolutionary Xenon Thruster (NEXT), an Enhanced NSTAR system, and a Low Power Hall effect thruster. These systems are analyzed on three straw man Discovery class missions and their performance is compared to a state of the art system using the NSTAR ion thruster. An electric propulsion subsystem cost model is used to conduct a cost-benefit analysis for each option. The results show that each proposed technology offers a different degree of performance and/or cost benefit for Discovery class missions.

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

The discovery of HTLV-1, the first pathogenic human retrovirus.

PubMed

Coffin, John M

2015-12-22

After the discovery of retroviral reverse transcriptase in 1970, there was a flurry of activity, sparked by the "War on Cancer," to identify human cancer retroviruses. After many false claims resulting from various artifacts, most scientists abandoned the search, but the Gallo laboratory carried on, developing both specific assays and new cell culture methods that enabled them to report, in the accompanying 1980 PNAS paper, identification and partial characterization of human T-cell leukemia virus (HTLV; now known as HTLV-1) produced by a T-cell line from a lymphoma patient. Follow-up studies, including collaboration with the group that first identified a cluster of adult T-cell leukemia (ATL) cases in Japan, provided conclusive evidence that HTLV was the cause of this disease. HTLV-1 is now known to infect at least 4-10 million people worldwide, about 5% of whom will develop ATL. Despite intensive research, knowledge of the viral etiology has not led to improvement in treatment or outcome of ATL. However, the technology for discovery of HTLV and acknowledgment of the existence of pathogenic human retroviruses laid the technical and intellectual foundation for the discovery of the cause of AIDS soon afterward. Without this advance, our ability to diagnose and treat HIV infection most likely would have been long delayed.

Using a Historical Lens to Envision the Next Generation of Genomic Translation Research.

PubMed

McBride, Colleen M; Abrams, Leah R; Koehly, Laura M

2015-01-01

The past 20 years have witnessed successive and exponential advances in genomic discovery and technology, with a broad scientific imperative pushing for continual advancements. The most consistent critique of these advances is that they have vastly outpaced translation of new knowledge into improvements in public health and medicine. We employ a historical and epistemological analysis to characterize how prevailing scientific meta-narratives have shaped the pace and priorities of research applying genomics to health promotion. We use four 'pivotal events' - the genetic characterization of Down syndrome, the launch of the Human Genome Research Project, the discovery of BRCA1, and the emergence of direct-to- consumer genetic testing - to illustrate how these scientific meta-narratives have inhibited genomic translation research. The notion that discovery should precede translation research has over-focused translation research on the latest genetic testing platform. The idea that genetic-related research has an exceptional potential for public harm has encouraged research on worst case scenarios. The perceived competition between genetics and social determinants of health has discouraged a unified research agenda to move genomic translation forward. We make a case for creating new scientific meta-narratives in which discovery and translation research agendas are envisioned as an interdependent enterprise. © 2015 S. Karger AG, Basel.

Form-Focused Discovery Activities in English Classes

ERIC Educational Resources Information Center

Ogeyik, Muhlise Cosgun

2011-01-01

Form-focused discovery activities allow language learners to grasp various aspects of a target language by contributing implicit knowledge by using discovered explicit knowledge. Moreover, such activities can assist learners to perceive and discover the features of their language input. In foreign language teaching environments, they can be used…

Integrated Approaches to Drug Discovery for Oxidative Stress-Related Retinal Diseases.

PubMed

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.

Integrated Approaches to Drug Discovery for Oxidative Stress-Related Retinal Diseases

PubMed Central

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

75 FR 66766 - NIAID Blue Ribbon Panel Meeting on Adjuvant Discovery and Development

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-29

..., identifies gaps in knowledge and capabilities, and defines NIAID's goals for the continued discovery... DEPARTMENT OF HEALTH AND HUMAN SERVICES NIAID Blue Ribbon Panel Meeting on Adjuvant Discovery and... agenda for the discovery, development and clinical evaluation of adjuvants for use with preventive...

12 CFR 263.53 - Discovery depositions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 3 2011-01-01 2011-01-01 false Discovery depositions. 263.53 Section 263.53... depositions. (a) In general. In addition to the discovery permitted in subpart A of this part, limited discovery by means of depositions shall be allowed for individuals with knowledge of facts material to the...

12 CFR 19.170 - Discovery depositions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 1 2010-01-01 2010-01-01 false Discovery depositions. 19.170 Section 19.170... PROCEDURE Discovery Depositions and Subpoenas § 19.170 Discovery depositions. (a) General rule. In any... deposition of an expert, or of a person, including another party, who has direct knowledge of matters that...

12 CFR 19.170 - Discovery depositions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 1 2011-01-01 2011-01-01 false Discovery depositions. 19.170 Section 19.170... PROCEDURE Discovery Depositions and Subpoenas § 19.170 Discovery depositions. (a) General rule. In any... deposition of an expert, or of a person, including another party, who has direct knowledge of matters that...

12 CFR 263.53 - Discovery depositions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 3 2010-01-01 2010-01-01 false Discovery depositions. 263.53 Section 263.53... depositions. (a) In general. In addition to the discovery permitted in subpart A of this part, limited discovery by means of depositions shall be allowed for individuals with knowledge of facts material to the...

Mentor-mentee Relationship: A Win-Win Contract In Graduate Medical Education

PubMed Central

Fuller, Jacklyn C

2017-01-01

Scholarly activities (i.e., the discovery of new knowledge; development of new technologies, methods, materials, or uses; integration of knowledge leading to new understanding) are intended to measure the quality and quantity of dissemination of knowledge. A successful mentorship program is necessary during residency to help residents achieve the six core competencies (patient care, medical knowledge, practice-based learning and improvement, systems-based practice, professionalism, interpersonal and communication skills) required by the Accreditation Council for Graduate Medical Education (ACGME). The role of the mentor in this process is pivotal in the advancement of the residents’ knowledge about evidence-based medicine. With this process, while mentees become more self-regulated, exhibit confidence in their performance, and demonstrate more insight and aptitude in their jobs, mentors also achieve elevated higher self-esteem, enhanced leadership skills, and personal gratification. As such, we may conclude that mentoring is a two-sided relationship; i.e., a 'win-win' style of commitment between the mentor and mentee. Hence, both parties will eventually advance academically, as well as professionally. PMID:29435394

Taking stock of current societal, political and academic stakeholders in the Canadian healthcare knowledge translation agenda

PubMed Central

Newton, Mandi S; Scott-Findlay, Shannon

2007-01-01

Background In the past 15 years, knowledge translation in healthcare has emerged as a multifaceted and complex agenda. Theoretical and polemical discussions, the development of a science to study and measure the effects of translating research evidence into healthcare, and the role of key stakeholders including academe, healthcare decision-makers, the public, and government funding bodies have brought scholarly, organizational, social, and political dimensions to the agenda. Objective This paper discusses the current knowledge translation agenda in Canadian healthcare and how elements in this agenda shape the discovery and translation of health knowledge. Discussion The current knowledge translation agenda in Canadian healthcare involves the influence of values, priorities, and people; stakes which greatly shape the discovery of research knowledge and how it is or is not instituted in healthcare delivery. As this agenda continues to take shape and direction, ensuring that it is accountable for its influences is essential and should be at the forefront of concern to the Canadian public and healthcare community. This transparency will allow for scrutiny, debate, and improvements in health knowledge discovery and health services delivery. PMID:17916256

Concept of operations for knowledge discovery from Big Data across enterprise data warehouses

NASA Astrophysics Data System (ADS)

Sukumar, Sreenivas R.; Olama, Mohammed M.; McNair, Allen W.; Nutaro, James J.

2013-05-01

The success of data-driven business in government, science, and private industry is driving the need for seamless integration of intra and inter-enterprise data sources to extract knowledge nuggets in the form of correlations, trends, patterns and behaviors previously not discovered due to physical and logical separation of datasets. Today, as volume, velocity, variety and complexity of enterprise data keeps increasing, the next generation analysts are facing several challenges in the knowledge extraction process. Towards addressing these challenges, data-driven organizations that rely on the success of their analysts have to make investment decisions for sustainable data/information systems and knowledge discovery. Options that organizations are considering are newer storage/analysis architectures, better analysis machines, redesigned analysis algorithms, collaborative knowledge management tools, and query builders amongst many others. In this paper, we present a concept of operations for enabling knowledge discovery that data-driven organizations can leverage towards making their investment decisions. We base our recommendations on the experience gained from integrating multi-agency enterprise data warehouses at the Oak Ridge National Laboratory to design the foundation of future knowledge nurturing data-system architectures.

Technology Opens Doors to Scientific Discovery, Portrait Unveiled of Former NLM Director Lindberg | NIH MedlinePlus the ...

MedlinePlus

... version of this page please turn JavaScript on. Technology Opens Doors to Scientific Discovery Past Issues / Spring 2016 Table of Contents Susannah Fox, chief technology officer of the U.S. Department of Health and ...

The center for causal discovery of biomedical knowledge from big data.

PubMed

Cooper, Gregory F; Bahar, Ivet; Becich, Michael J; Benos, Panayiotis V; Berg, Jeremy; Espino, Jeremy U; Glymour, Clark; Jacobson, Rebecca Crowley; Kienholz, Michelle; Lee, Adrian V; Lu, Xinghua; Scheines, Richard

2015-11-01

The Big Data to Knowledge (BD2K) Center for Causal Discovery is developing and disseminating an integrated set of open source tools that support causal modeling and discovery of biomedical knowledge from large and complex biomedical datasets. The Center integrates teams of biomedical and data scientists focused on the refinement of existing and the development of new constraint-based and Bayesian algorithms based on causal Bayesian networks, the optimization of software for efficient operation in a supercomputing environment, and the testing of algorithms and software developed using real data from 3 representative driving biomedical projects: cancer driver mutations, lung disease, and the functional connectome of the human brain. Associated training activities provide both biomedical and data scientists with the knowledge and skills needed to apply and extend these tools. Collaborative activities with the BD2K Consortium further advance causal discovery tools and integrate tools and resources developed by other centers. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Conference report: Bioanalysis highlights from the 2012 American Association of Pharmaceutical Scientists National Biotechnology Conference.

PubMed

Crisino, Rebecca M; Geist, Brian; Li, Jian

2012-09-01

The American Association of Pharmaceutical Scientists (AAPS) is an international forum for the exchange of knowledge among scientists to enhance their contributions to drug development. The annual National Biotechnology Conference, organized by the AAPS on 21-23 May 2012 in San Diego, CA, USA, brings together experts from various disciplines representing private industry, academia and governing institutions dedicated toward advancing the scientific and technological progress related to discovery, development and manufacture of medical biotechnology products. Over 300 scientific poster presentations and approximately 50 oral presentation and discussion sessions examined a breadth of topics pertaining to biotechnology drug development, such as the advancement of vaccines and biosimilars, emerging and innovative technologies, nonclinical and clinical bioanalysis, and regulatory updates. This conference report highlights the existing challenges with ligand-binding assays, emerging challenges, innovative integration of various technology platforms and applicable regulatory considerations as they relate to immunogenicity and pharmacokinetic bioanalytical assessments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

,

The reports included in this report are for project activities that occurred from October 2011 through September 2012. These reports describe in detail the discoveries, achievements, and challenges encountered by our talented and enthusiastic principal investigators (PIs). Many of the reports describe R&D efforts that were “successful” in their pursuits and resulted in a positive outcome or technology realization. As we’ve stated before, and continue to stress, in some cases the result is a “negative” finding, for instance a technology is currently impractical or out of reach. This can often be viewed erroneously as a “failure,” but is actually amore » valid outcome in the pursuit of high-risk research, which often leads to unforeseen new paths of discovery. Either result advances our knowledge and increases our ability to identify solutions and/or likewise avoid costly paths not appropriate for the challenges presented. The SDRD program continues to provide an unfettered mechanism for innovation and development that returns multifold to the NNSS mission. Overall the program is a strong R&D innovation engine, benefited by an enhanced mission, committed resources, and sound competitiveness to yield maximum benefit. The 23 projects described exemplify the creativity and ability of a diverse scientific and engineering talent base. The efforts also showcase an impressive capability and resource that can be brought to find solutions to a broad array of technology needs and applications relevant to the NNSS mission and national security.« less

Modern astronomical knowledge as component of general education for sustainable development

NASA Astrophysics Data System (ADS)

Nurgaliev, I.

{It is shown that 1) astronomical knowledge was a foundation of emerging modern physics and natural sciences based on mathematics, 2) mathematical basis of the natural sciences serves as an orientation of progress in the true objective of social sciences. The last example for this chain of impacts is the discovery of the fundamental demographic equation (N=aN^2-bN) full of the astronomical analogy [9]. Modern age endorses new imperatives on education. Reckless exploitation of the natural resources will cause irreversible exhaustion of the agro- and bio-potential of the planet during lifetime of a few generations. The adequate respond to the challenge lies in modern technologies and educating responsible (socially oriented) professionals. That is why the importance of teaching modern technologies along with providing the students with the understanding of global long term consequences of the human industrial activities is growing. The course ``Theoretical Foundations of Modern Technologies" at the Moscow State Agricultural University (Timiryazev Academy) taught by the author is discussed. New experimental project ``Space Technologies, Ecology and Safe Energetics in School of the Future" is presented as a project of a new age in the process of implementing at the Moscow city secondary schools by the colleagues and by the author. The new cosmological models in the frame of the Newtonian and general relativistic treatments developed by the author are considered in this report as an example of immediate implementation of new astro-knowledge into the education for modern agrarian students. The centrifugal forces acting between particles rotating randomly around each other are shown to be able to reverse gravitational collapse.

NATURAL PRODUCTS: A CONTINUING SOURCE OF NOVEL DRUG LEADS

PubMed Central

Cragg, Gordon M.; Newman, David J.

2013-01-01

1. Background Nature has been a source of medicinal products for millennia, with many useful drugs developed from plant sources. Following discovery of the penicillins, drug discovery from microbial sources occurred and diving techniques in the 1970s opened the seas. Combinatorial chemistry (late 1980s), shifted the focus of drug discovery efforts from Nature to the laboratory bench. 2. Scope of Review This review traces natural products drug discovery, outlining important drugs from natural sources that revolutionized treatment of serious diseases. It is clear Nature will continue to be a major source of new structural leads, and effective drug development depends on multidisciplinary collaborations. 3. Major Conclusions The explosion of genetic information led not only to novel screens, but the genetic techniques permitted the implementation of combinatorial biosynthetic technology and genome mining. The knowledge gained has allowed unknown molecules to be identified. These novel bioactive structures can be optimized by using combinatorial chemistry generating new drug candidates for many diseases. 4 General Significance: The advent of genetic techniques that permitted the isolation / expression of biosynthetic cassettes from microbes may well be the new frontier for natural products lead discovery. It is now apparent that biodiversity may be much greater in those organisms. The numbers of potential species involved in the microbial world are many orders of magnitude greater than those of plants and multi-celled animals. Coupling these numbers to the number of currently unexpressed biosynthetic clusters now identified (>10 per species) the potential of microbial diversity remains essentially untapped. PMID:23428572

X-ray crystallography over the past decade for novel drug discovery - where are we heading next?

PubMed

Zheng, Heping; Handing, Katarzyna B; Zimmerman, Matthew D; Shabalin, Ivan G; Almo, Steven C; Minor, Wladek

2015-01-01

Macromolecular X-ray crystallography has been the primary methodology for determining the three-dimensional structures of proteins, nucleic acids and viruses. Structural information has paved the way for structure-guided drug discovery and laid the foundations for structural bioinformatics. However, X-ray crystallography still has a few fundamental limitations, some of which may be overcome and complemented using emerging methods and technologies in other areas of structural biology. This review describes how structural knowledge gained from X-ray crystallography has been used to advance other biophysical methods for structure determination (and vice versa). This article also covers current practices for integrating data generated by other biochemical and biophysical methods with those obtained from X-ray crystallography. Finally, the authors articulate their vision about how a combination of structural and biochemical/biophysical methods may improve our understanding of biological processes and interactions. X-ray crystallography has been, and will continue to serve as, the central source of experimental structural biology data used in the discovery of new drugs. However, other structural biology techniques are useful not only to overcome the major limitation of X-ray crystallography, but also to provide complementary structural data that is useful in drug discovery. The use of recent advancements in biochemical, spectroscopy and bioinformatics methods may revolutionize drug discovery, albeit only when these data are combined and analyzed with effective data management systems. Accurate and complete data management is crucial for developing experimental procedures that are robust and reproducible.

Advances in synthetic peptides reagent discovery

NASA Astrophysics Data System (ADS)

Adams, Bryn L.; Sarkes, Deborah A.; Finch, Amethist S.; Stratis-Cullum, Dimitra N.

2013-05-01

Bacterial display technology offers a number of advantages over competing display technologies (e.g, phage) for the rapid discovery and development of peptides with interaction targeted to materials ranging from biological hazards through inorganic metals. We have previously shown that discovery of synthetic peptide reagents utilizing bacterial display technology is relatively simple and rapid to make laboratory automation possible. This included extensive study of the protective antigen system of Bacillus anthracis, including development of discovery, characterization, and computational biology capabilities for in-silico optimization. Although the benefits towards CBD goals are evident, the impact is far-reaching due to our ability to understand and harness peptide interactions that are ultimately extendable to the hybrid biomaterials of the future. In this paper, we describe advances in peptide discovery including, new target systems (e.g. non-biological materials), advanced library development and clone analysis including integrated reporting.

Semiconductor technology in protein kinase research and drug discovery: sensing a revolution.

PubMed

Bhalla, Nikhil; Di Lorenzo, Mirella; Estrela, Pedro; Pula, Giordano

2017-02-01

Since the discovery of protein kinase activity in 1954, close to 600 kinases have been discovered that have crucial roles in cell physiology. In several pathological conditions, aberrant protein kinase activity leads to abnormal cell and tissue physiology. Therefore, protein kinase inhibitors are investigated as potential treatments for several diseases, including dementia, diabetes, cancer and autoimmune and cardiovascular disease. Modern semiconductor technology has recently been applied to accelerate the discovery of novel protein kinase inhibitors that could become the standard-of-care drugs of tomorrow. Here, we describe current techniques and novel applications of semiconductor technologies in protein kinase inhibitor drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Pause That Refreshes: A Study of the Discovery Corners in the National Museum of History and Technology Smithsonian Institution.

ERIC Educational Resources Information Center

Wolf, Robert L.; Tymitz, Barbara L.

This report examines the impact and effectiveness of an educational program (Discovery Corners) offered by the National Museum of History and Technology. The main objective is to offer feedback to museum personnel regarding the impact of museum exhibits and programs. The Discovery Corners program involves on-site presentations and demonstrations…

Enhancing Learning Environments through Solution-based Knowledge Discovery Tools: Forecasting for Self-Perpetuating Systemic Reform.

ERIC Educational Resources Information Center

Tsantis, Linda; Castellani, John

2001-01-01

This article explores how knowledge-discovery applications can empower educators with the information they need to provide anticipatory guidance for teaching and learning, forecast school and district needs, and find critical markers for making the best program decisions for children and youth with disabilities. Data mining for schools is…

Students and Teacher Academic Evaluation Perceptions: Methodology to Construct a Representation Based on Actionable Knowledge Discovery Framework

ERIC Educational Resources Information Center

Molina, Otilia Alejandro; Ratté, Sylvie

2017-01-01

This research introduces a method to construct a unified representation of teachers and students perspectives based on the actionable knowledge discovery (AKD) and delivery framework. The representation is constructed using two models: one obtained from student evaluations and the other obtained from teachers' reflections about their teaching…

Application of Knowledge Discovery in Databases Methodologies for Predictive Models for Pregnancy Adverse Events

ERIC Educational Resources Information Center

Taft, Laritza M.

2010-01-01

In its report "To Err is Human", The Institute of Medicine recommended the implementation of internal and external voluntary and mandatory automatic reporting systems to increase detection of adverse events. Knowledge Discovery in Databases (KDD) allows the detection of patterns and trends that would be hidden or less detectable if analyzed by…

Knowledge Discovery Process: Case Study of RNAV Adherence of Radar Track Data

NASA Technical Reports Server (NTRS)

Matthews, Bryan

2018-01-01

This talk is an introduction to the knowledge discovery process, beginning with: identifying the problem, choosing data sources, matching the appropriate machine learning tools, and reviewing the results. The overview will be given in the context of an ongoing study that is assessing RNAV adherence of commercial aircraft in the national airspace.

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

NASA Technical Reports Server (NTRS)

Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

2003-01-01

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

Ecologies, outreach, and the evolution of medical libraries.

PubMed

Shen, Bern

2005-10-01

What are some of the forces shaping the evolution of medical libraries, and where might they lead? Published literature in the fields of library and information sciences, technology, health services research, and business was consulted. Medical libraries currently have a modest footprint in most consumers' personal health ecologies, the network of resources and activities they use to improve their health. They also occupy a relatively small space in the health care, information, and business ecologies of which they are a part. Several trends in knowledge discovery, technology, and social organizations point to ways in which the roles of medical libraries might grow and become more complex. As medical libraries evolve and reach out to previously underserved communities, an ecological approach can serve as a useful organizing framework for the forces shaping this evolution.

Paediatric genomics: diagnosing rare disease in children.

PubMed

Wright, Caroline F; FitzPatrick, David R; Firth, Helen V

2018-05-01

The majority of rare diseases affect children, most of whom have an underlying genetic cause for their condition. However, making a molecular diagnosis with current technologies and knowledge is often still a challenge. Paediatric genomics is an immature but rapidly evolving field that tackles this issue by incorporating next-generation sequencing technologies, especially whole-exome sequencing and whole-genome sequencing, into research and clinical workflows. This complex multidisciplinary approach, coupled with the increasing availability of population genetic variation data, has already resulted in an increased discovery rate of causative genes and in improved diagnosis of rare paediatric disease. Importantly, for affected families, a better understanding of the genetic basis of rare disease translates to more accurate prognosis, management, surveillance and genetic advice; stimulates research into new therapies; and enables provision of better support.

RNA interference: from biology to drugs and therapeutics.

PubMed

Appasani, Krishnarao

2004-07-01

RNA interference (RNAi) is a newly discovered and popular technology platform among researchers not only in the fields of RNA biology and molecular cell biology. It has created excitement in clinical sciences such as oncology, neurology, endocrinology, infectious diseases and drug discovery. There is an urgent need to educate and connect academic and industry researchers for the purpose of knowledge transfer. Thus, GeneExpression Systems of Waltham organized its Second International Conference in Waltham City (May 2-4, 2004, MA, USA) on the theme of 'RNA interference: From Biology to Drugs & Therapeutics.' About 200 participants and 32 speakers attended this two and half-day event which was arranged in six scientific and three technology sessions and ended with a panel discussion. This report covers a few representative talks from academia, biotech and the drug industry.

Geoinformatics 2007: data to knowledge

USGS Publications Warehouse

Brady, Shailaja R.; Sinha, A. Krishna; Gundersen, Linda C.

2007-01-01

Geoinformatics is the term used to describe a variety of efforts to promote collaboration between the computer sciences and the geosciences to solve complex scientific questions. It refers to the distributed, integrated digital information system and working environment that provides innovative means for the study of the Earth systems, as well as other planets, through use of advanced information technologies. Geoinformatics activities range from major research and development efforts creating new technologies to provide high-quality, sustained production-level services for data discovery, integration and analysis, to small, discipline-specific efforts that develop earth science data collections and data analysis tools serving the needs of individual communities. The ultimate vision of Geoinformatics is a highly interconnected data system populated with high quality, freely available data, as well as, a robust set of software for analysis, visualization, and modeling.

Bioanalysis-related highlights from the 2011 AAPS National Biotechnology Conference.

PubMed

Crisino, Rebecca M; Dulanto, Beatriz

2011-08-01

The American Association of Pharmaceutical Scientists is a dynamic international forum for the exchange of knowledge among scientists to enhance their contributions to drug development. The annual National Biotechnology Conference, conducted and organized by the American Association of Pharmaceutical Scientists, is a forum dedicated to advancements in science and technology related to discovery, development and manufacture of medical biotechnology products. The 2011 National Biotechnology Conference meeting convened in San Francisco, CA, USA on 16-18 May. Over 300 abstracts were submitted and approximately 50 sessions examined topics pertaining to advances in drug development, emerging analytical technologies, bioanalysis-related issues, biosimilar therapies, updates on global regulatory documents and expectations, and other topics. The focus of this article is to highlight key developments relevant to immunogenicity and pharmacokinetic drug concentration bioanalysis.

An informatics research agenda to support precision medicine: seven key areas

PubMed Central

Avillach, Paul; Benham-Hutchins, Marge; Breitenstein, Matthew K; Crowgey, Erin L; Hoffman, Mark A; Jiang, Xia; Madhavan, Subha; Mattison, John E; Nagarajan, Radhakrishnan; Ray, Bisakha; Shin, Dmitriy; Visweswaran, Shyam; Zhao, Zhongming; Freimuth, Robert R

2016-01-01

The recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to the forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue to evolve and datasets grow in magnitude, a strong computational infrastructure will be essential to realize PM’s vision of improved healthcare derived from personal data. In addition, informatics research and innovation affords a tremendous opportunity to drive the science underlying PM. The informatics community must lead the development of technologies and methodologies that will increase the discovery and application of biomedical knowledge through close collaboration between researchers, clinicians, and patients. This perspective highlights seven key areas that are in need of further informatics research and innovation to support the realization of PM. PMID:27107452

Empowering Accelerated Personal, Professional and Scholarly Discovery among Information Seekers: An Educational Vision

ERIC Educational Resources Information Center

Harmon, Glynn

2013-01-01

The term discovery applies herein to the successful outcome of inquiry in which a significant personal, professional or scholarly breakthrough or insight occurs, and which is individually or socially acknowledged as a key contribution to knowledge. Since discoveries culminate at fixed points in time, discoveries can serve as an outcome metric for…

A Framework of Knowledge Integration and Discovery for Supporting Pharmacogenomics Target Predication of Adverse Drug Events: A Case Study of Drug-Induced Long QT Syndrome.

PubMed

Jiang, Guoqian; Wang, Chen; Zhu, Qian; Chute, Christopher G

2013-01-01

Knowledge-driven text mining is becoming an important research area for identifying pharmacogenomics target genes. However, few of such studies have been focused on the pharmacogenomics targets of adverse drug events (ADEs). The objective of the present study is to build a framework of knowledge integration and discovery that aims to support pharmacogenomics target predication of ADEs. We integrate a semantically annotated literature corpus Semantic MEDLINE with a semantically coded ADE knowledgebase known as ADEpedia using a semantic web based framework. We developed a knowledge discovery approach combining a network analysis of a protein-protein interaction (PPI) network and a gene functional classification approach. We performed a case study of drug-induced long QT syndrome for demonstrating the usefulness of the framework in predicting potential pharmacogenomics targets of ADEs.

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Integrative Convergence in Neuroscience: Trajectories, Problems, and the Need for a Progressive Neurobioethics

NASA Astrophysics Data System (ADS)

Giordano, J.

The advanced integrative scientific convergence (AISC) model represents a viable approach to neuroscience. Beyond simple multi-disciplinarity, the AISC model unifies constituent scientific and technological fields to foster innovation, invention and new ways of addressing seemingly intractable questions. In this way, AISC can yield novel methods and foster new trajectories of knowledge and discovery, and yield new epistemologies. As stand-alone disciplines, each and all of the constituent fields generate practical and ethical issues, and their convergence may establish a unique set of both potential benefits and problems. To effectively attend to these contingencies requires pragmatic assessment of the actual capabilities and limits of neurofocal AISC, and an openness to what new knowledge and scientific/technological achievements may be produced, and how such outcomes can affect humanity, the human condition, society and the global environment. It is proposed that a progressive neurobioethics may be needed to establish both a meta-ethical framework upon which to structure ethical decisions, and a system and method of ethics that is inclusive, convergent and innovative, and in thus aligned with and meaningful to use of an AISC model in neuroscience.

Facts are the enemy of truth-reflections on serendipitous discovery and unforeseen developments in asymmetric catalysis.

PubMed

Noyori, Ryoji

2013-01-02

As Louis Pasteur said, "Chance favors only a prepared mind." Serendipitous events reorienting the pathway of science often occur through the actions of dedicated individuals with unique cultural and educational backgrounds, an original sense of values, and firm principles. Science is the fountainhead of human knowledge and possesses an indispensable cultural value. Science-based technologies and the innovations derived from them are the foundation of the civilized society in which we live today. All scientific endeavors begin with observations, or facts. However, the real goal of research activity is to convert accumulated knowledge to something with new technological, economic, or social value. Innovation is an essential aspect to assure the continued survival of humanity. And often, as my half-century of research reflects, the act of turning facts into values is facilitated by dialogue. Thus, to acquire the necessary combined wisdom, scientists must have ongoing conversations with the societies they serve, as well as with their counterparts in other nations. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Single-Cell Genomics Unravels Brain Cell-Type Complexity.

PubMed

Guillaumet-Adkins, Amy; Heyn, Holger

2017-01-01

The brain is the most complex tissue in terms of cell types that it comprises, to the extent that it is still poorly understood. Single cell genome and transcriptome profiling allow to disentangle the neuronal heterogeneity, enabling the categorization of individual neurons into groups with similar molecular signatures. Herein, we unravel the current state of knowledge in single cell neurogenomics. We describe the molecular understanding of the cellular architecture of the mammalian nervous system in health and in disease; from the discovery of unrecognized cell types to the validation of known ones, applying these state-of-the-art technologies.

Designing Vaccines for the Twenty-First Century Society

PubMed Central

Finco, Oretta; Rappuoli, Rino

2013-01-01

The history of vaccination clearly demonstrates that vaccines have been highly successful in preventing infectious diseases, reducing significantly the incidence of childhood diseases and mortality. However, many infections are still not preventable with the currently available vaccines and they represent a major cause of mortality worldwide. In the twenty-first century, the innovation brought by novel technologies in antigen discovery and formulation together with a deeper knowledge of the human immune responses are paving the way for the development of new vaccines. Final goal will be to rationally design effective vaccines where conventional approaches have failed. PMID:24478777

Calling on a million minds for community annotation in WikiProteins

PubMed Central

Mons, Barend; Ashburner, Michael; Chichester, Christine; van Mulligen, Erik; Weeber, Marc; den Dunnen, Johan; van Ommen, Gert-Jan; Musen, Mark; Cockerill, Matthew; Hermjakob, Henning; Mons, Albert; Packer, Abel; Pacheco, Roberto; Lewis, Suzanna; Berkeley, Alfred; Melton, William; Barris, Nickolas; Wales, Jimmy; Meijssen, Gerard; Moeller, Erik; Roes, Peter Jan; Borner, Katy; Bairoch, Amos

2008-01-01

WikiProteins enables community annotation in a Wiki-based system. Extracts of major data sources have been fused into an editable environment that links out to the original sources. Data from community edits create automatic copies of the original data. Semantic technology captures concepts co-occurring in one sentence and thus potential factual statements. In addition, indirect associations between concepts have been calculated. We call on a 'million minds' to annotate a 'million concepts' and to collect facts from the literature with the reward of collaborative knowledge discovery. The system is available for beta testing at . PMID:18507872

'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sukumar, Sreenivas R; Ferrell, Regina Kay

2013-01-01

As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elementsmore » of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.« less

Discovery '84: Technology for Disabled Persons. Conference Papers (Chicago, Illinois, October 1-3, 1984).

ERIC Educational Resources Information Center

Smith, Christopher, Ed.

Thirty-nine papers from the conference "Discovery '84: Technology for Disabled Persons" are presented. The conference was intended to provide an overview of the areas in which technological advances have been made, including the applications of computers and other related products and services. Conference presenters represented fields of…

Knowledge Evolution in Distributed Geoscience Datasets and the Role of Semantic Technologies

NASA Astrophysics Data System (ADS)

Ma, X.

2014-12-01

Knowledge evolves in geoscience, and the evolution is reflected in datasets. In a context with distributed data sources, the evolution of knowledge may cause considerable challenges to data management and re-use. For example, a short news published in 2009 (Mascarelli, 2009) revealed the geoscience community's concern that the International Commission on Stratigraphy's change to the definition of Quaternary may bring heavy reworking of geologic maps. Now we are in the era of the World Wide Web, and geoscience knowledge is increasingly modeled and encoded in the form of ontologies and vocabularies by using semantic technologies. Accordingly, knowledge evolution leads to a consequence called ontology dynamics. Flouris et al. (2008) summarized 10 topics of general ontology changes/dynamics such as: ontology mapping, morphism, evolution, debugging and versioning, etc. Ontology dynamics makes impacts at several stages of a data life cycle and causes challenges, such as: the request for reworking of the extant data in a data center, semantic mismatch among data sources, differentiated understanding of a same piece of dataset between data providers and data users, as well as error propagation in cross-discipline data discovery and re-use (Ma et al., 2014). This presentation will analyze the best practices in the geoscience community so far and summarize a few recommendations to reduce the negative impacts of ontology dynamics in a data life cycle, including: communities of practice and collaboration on ontology and vocabulary building, link data records to standardized terms, and methods for (semi-)automatic reworking of datasets using semantic technologies. References: Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G., 2008. Ontology change: classification and survey. The Knowledge Engineering Review 23 (2), 117-152. Ma, X., Fox, P., Rozell, E., West, P., Zednik, S., 2014. Ontology dynamics in a data life cycle: Challenges and recommendations from a Geoscience Perspective. Journal of Earth Science 25 (2), 407-412. Mascarelli, A.L., 2009. Quaternary geologists win timescale vote. Nature 459, 624.

The Underlying Social Dynamics of Paradigm Shifts.

PubMed

Rodriguez-Sickert, Carlos; Cosmelli, Diego; Claro, Francisco; Fuentes, Miguel Angel

2015-01-01

We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm.

The Underlying Social Dynamics of Paradigm Shifts

PubMed Central

Claro, Francisco; Fuentes, Miguel Angel

2015-01-01

We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm. PMID:26418255

Emerging technology becomes an opportunity for EOS

NASA Astrophysics Data System (ADS)

Fargion, Giulietta S.; Harberts, Robert; Masek, Jeffrey G.

1996-11-01

During the last decade, we have seen an explosive growth in our ability to collect and generate data. When implemented, NASA's Earth observing system data information system (EOSDIS) will receive about 50 gigabytes of remotely sensed image data per hour. This will generate an urgent need for new techniques and tools that can automatically and intelligently assist in transforming this abundance of data into useful knowledge. Some emerging technologies that address these challenges include data mining and knowledge discovery in databases (KDD). The most basic data mining application is a content-based search (examples include finding images of particular meteorological phenomena or identifying data that have been previously mined or interpreted). In order that these technologies be effectively exploited for EOSDIS development, a better understanding of data mining and the requirements for using this technology is necessary. The authors are currently undertaking a project exploring the requirements and options of content-based search and data mining for use on EOSDIS. The scope of the project is to develop a prototype with which to investigate user interface concepts, requirements, and designs relevant for EOSDIS core system (ECS) subsystem utilizing these techniques. The goal is to identify a generic handling of these functions. This prototype will help identify opportunities which the earth science community and EOSDIS can use to meet the challenges of collecting, searching, retrieving, and interacting with abundant data resources in highly productive ways.

Revisiting lab-on-a-chip technology for drug discovery.

PubMed

Neuži, Pavel; Giselbrecht, Stefan; Länge, Kerstin; Huang, Tony Jun; Manz, Andreas

2012-08-01

The field of microfluidics or lab-on-a-chip technology aims to improve and extend the possibilities of bioassays, cell biology and biomedical research based on the idea of miniaturization. Microfluidic systems allow more accurate modelling of physiological situations for both fundamental research and drug development, and enable systematic high-volume testing for various aspects of drug discovery. Microfluidic systems are in development that not only model biological environments but also physically mimic biological tissues and organs; such 'organs on a chip' could have an important role in expediting early stages of drug discovery and help reduce reliance on animal testing. This Review highlights the latest lab-on-a-chip technologies for drug discovery and discusses the potential for future developments in this field.

Predicting future discoveries from current scientific literature.

PubMed

Petrič, Ingrid; Cestnik, Bojan

2014-01-01

Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If enough scientific evidence is already published for the association of such findings, they can be considered as scientific hypotheses. In this chapter, we describe a method for the computer-aided generation of such hypotheses based on the existing scientific literature. Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.

Cultural aspects of the search for extraterrestrial intelligence

NASA Astrophysics Data System (ADS)

Billingham, J.

SETI is an acronym which stands for the Search for Extraterrestrial Intelligence. The NASA SETI High Resolution Microwave Survey Project is a new and comprehensive search for evidence of microwave signals from extraterrestrial civilizations. It will formally begin on October 12, 1992, and last to the end of the century. The discovery of another form of intelligent life would be an important milestone for our civilization. In addition to the new scientific knowledge that we might acquire on the chemistry, physiology, behavior and evolutionary history of extraterrestrial life forms, we may also learn of the cultural achievements of another civilization, or indeed of many other civilizations. It is likely that the society that we detect will be much in advance of our own, so that they may long ago have passed through the evolutionary stage we are at now. The implications of such a discovery would have important consequences for our own future. This paper presents an analysis of some of the important areas which will require study as we approach the beginning of the NASA search. There are significant questions about the ease or difficulty of incorporating the new knowledge into the belief structures of different religions. Sociological and educational changes over time may equal or exceed those of the Copernican revolution. The status of the other civilization relative to ours is a challenging question for international space law. There are institutional and international questions on who will represent Earth in any future interstellar communication endeavors that we may attempt. There may be challenges in how we absorb the knowledge of an advanced technology. In political science we may have much to learn from their history, and what influence it may have on our own future. Last but not least, there is the effect of the discovery on individual and group psychology. These are the cultural aspects of SETI. Each area warrants further study, and recommendations are made as to the mechanisms which could be used to undertake such studies.

Bioenergy Knowledge Discovery Framework Fact Sheet

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

Teachers' Journal Club: Bridging between the Dynamics of Biological Discoveries and Biology Teachers

ERIC Educational Resources Information Center

Brill, Gilat; Falk, Hedda; Yarden, Anat

2003-01-01

Since biology is one of the most dynamic research fields within the natural sciences, the gap between the accumulated knowledge in biology and the knowledge that is taught in schools, increases rapidly with time. Our long-term objective is to develop means to bridge between the dynamics of biological discoveries and the biology teachers and…

The Future Workforce in Cancer Prevention: Advancing Discovery, Research, and Technology

PubMed Central

Newhauser, Wayne. D.; Scheurer, Michael. E.; Faupel-Badger, Jessica. M.; Clague, Jessica.; Weitzel, Jeffrey.; Woods, Kendra. V.

2012-01-01

As part of a 2 day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the United States was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force’s findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: 1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and 2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation. PMID:22314794

The future workforce in cancer prevention: advancing discovery, research, and technology.

PubMed

Newhauser, Wayne D; Scheurer, Michael E; Faupel-Badger, Jessica M; Clague, Jessica; Weitzel, Jeffrey; Woods, Kendra V

2012-05-01

As part of a 2-day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the USA was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force's findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: (1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and (2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation.

eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems.

PubMed

Savonnet, Marinette; Leclercq, Eric; Naubourg, Pierre

2016-11-01

Biomedical information systems (BIS) require consideration of three types of variability: data variability induced by new high throughput technologies, schema or model variability induced by large scale studies or new fields of research, and knowledge variability resulting from new discoveries. Beyond data heterogeneity, managing variabilities in the context of BIS requires extensible and dynamic integration process. In this paper, we focus on data and schema variabilities and we propose an integration framework based on ontologies, master data, and semantic annotations. The framework addresses issues related to: 1) collaborative work through a dynamic integration process; 2) variability among studies using an annotation mechanism; and 3) quality control over data and semantic annotations. Our approach relies on two levels of knowledge: BIS-related knowledge is modeled using an application ontology coupled with UML models that allow controlling data completeness and consistency, and domain knowledge is described by a domain ontology, which ensures data coherence. A system build with the eClims framework has been implemented and evaluated in the context of a proteomic platform.

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

PubMed

Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. © The Author(s) 2016. Published by Oxford University Press.

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework

PubMed Central

Chen, Yi-An; Tripathi, Lokesh P.; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org PMID:26989145

New space technology advances knowledge of the remote polar regions. [Arctic and Antarctic regions

NASA Technical Reports Server (NTRS)

Macdonald, W. R.

1974-01-01

The application of ERTS-1 imagery is rapidly increasing man's knowledge of polar regions. Products compiled from this imagery at scales of 1:250,000, 1:500,000 and 1:1,000,000 are already providing valuable information to earth scientists working in Antarctica. Significant finds detected by these bench mark products were glaciological changes, advancement in ice fronts, discovery of new geographic features, and the repositioning of nunataks, islands, and ice tongues. Tests conducted in Antarctica have proven the feasibility of tracking Navy navigation satellites to establish ground control for positioning ERTS-1 imagery in remote areas. ERTS imagery coupled with satellite geodesy shows great promise and may prove to be the most practical and cost effective way to meet the small-scale cartographic requirements of the polar science community.

Computational functional genomics-based approaches in analgesic drug discovery and repurposing.

PubMed

Lippmann, Catharina; Kringel, Dario; Ultsch, Alfred; Lötsch, Jörn

2018-06-01

Persistent pain is a major healthcare problem affecting a fifth of adults worldwide with still limited treatment options. The search for new analgesics increasingly includes the novel research area of functional genomics, which combines data derived from various processes related to DNA sequence, gene expression or protein function and uses advanced methods of data mining and knowledge discovery with the goal of understanding the relationship between the genome and the phenotype. Its use in drug discovery and repurposing for analgesic indications has so far been performed using knowledge discovery in gene function and drug target-related databases; next-generation sequencing; and functional proteomics-based approaches. Here, we discuss recent efforts in functional genomics-based approaches to analgesic drug discovery and repurposing and highlight the potential of computational functional genomics in this field including a demonstration of the workflow using a novel R library 'dbtORA'.

Nursing Routine Data as a Basis for Association Analysis in the Domain of Nursing Knowledge

PubMed Central

Sellemann, Björn; Stausberg, Jürgen; Hübner, Ursula

2012-01-01

This paper describes the data mining method of association analysis within the framework of Knowledge Discovery in Databases (KDD) with the aim to identify standard patterns of nursing care. The approach is application-oriented and used on nursing routine data of the method LEP nursing 2. The increasing use of information technology in hospitals, especially of nursing information systems, requires the storage of large data sets, which hitherto have not always been analyzed adequately. Three association analyses for the days of admission, surgery and discharge, have been performed. The results of almost 1.5 million generated association rules indicate that it is valid to apply association analysis to nursing routine data. All rules are semantically trivial, since they reflect existing knowledge from the domain of nursing. This may be due either to the method LEP Nursing 2, or to the nursing activities themselves. Nonetheless, association analysis may in future become a useful analytical tool on the basis of structured nursing routine data. PMID:24199122

Building Learning Modules for Undergraduate Education Using LEAD Technology

NASA Astrophysics Data System (ADS)

Clark, R. D.; Yalda, S.

2006-12-01

Linked Environments for Atmospheric Discovery (LEAD) has as its goal to make meteorological data, forecast models, and analysis and visualization tools available to anyone who wants to interactively explore the weather as it evolves. LEAD advances through the development and beta-deployment of Integrated Test Beds (ITBs), which are technology build-outs that are the fruition of collaborative IT and meteorological research. As the ITBs mature, opportunities emerge for the integration of this new technological capability into the education arena. The LEAD education and outreach initiative is aimed at bringing new capabilities into classroom from the middle school level to graduate education and beyond, and ensuring the congruency of this technology with curricular. One of the principal goals of LEAD is to democratize the availability of advanced weather technologies for research and education. The degree of democratization is tied to the growth of student knowledge and skills, and is correlated with education level (though not for every student in the same way). The average high school student may experience LEAD through an environment that retains a higher level of instructor control compared to the undergraduate and graduate student. This is necessary to accommodate not only differences in knowledge and skills, but the computer capabilities in the classroom such that the "teachable moment" is not lost.Undergraduates will have the opportunity to query observation data and model output, explore and discover relationships through concept mapping using an ontology service, select domains of interest based on current weather, and employ an experiment builder within the LEAD portal as an interface to configure, launch the WRF model, monitor the workflow, and visualize results using Unidata's Integrated Data Viewer (IDV), whether it be on a local server or across the TeraGrid. Such a robust and comprehensive suite of tools and services can create new paradigms for embedding students in an authentic, contextualized environment where the knowledge domain is an extension, yet integral supplement, to the classroom experience.This presentation describes two different approaches for the use of LEAD in undergraduate education: 1) a use-case for integrating LEAD technology into undergraduate subject material; and 2) making LEAD capability available to a select group of students participating in the National Collegiate Forecasting Contest (NCFC). The use-case (1) is designed to have students explore a particular weather phenomenon (e.g., a frontal boundary, jet streak, or lake effect snow event) through self-guided inquiry, and is intended as a supplement to classroom instruction. Students will use interactive, Web-based, LEAD-to-Learn modules created specifically to build conceptual knowledge of the phenomenon, adjoin germane terminology, explore relationships between concepts and similar phenomena using the LEAD ontology, and guide them through the experiment builder and workflow orchestration process in order to establish a high-resolution WRF run over a region that exhibits the characteristics of the phenomenon they wish to study. The results of the experiment will be stored in the student's MyLEAD workspace from which it can be retrieved, visualized and analyzed for atmospheric signatures characteristic of the phenomenon. The learning process is authentic in that students will be exposed to the same process of investigation, and will have available many of the same tools, as researchers. The modules serve to build content knowledge, guide discovery, and provide assessment while the LEAD portal opens the gateway to real-time observations, model accessibility, and a variety of tools, services, and resources.

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruebel, Oliver

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research coveredmore » in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle acceleration, physicists model LWFAs computationally. The datasets produced by LWFA simulations are (i) extremely large, (ii) of varying spatial and temporal resolution, (iii) heterogeneous, and (iv) high-dimensional, making analysis and knowledge discovery from complex LWFA simulation data a challenging task. To address these challenges this thesis describes the integration of the visualization system VisIt and the state-of-the-art index/query system FastBit, enabling interactive visual exploration of extremely large three-dimensional particle datasets. Researchers are especially interested in beams of high-energy particles formed during the course of a simulation. This thesis describes novel methods for automatic detection and analysis of particle beams enabling a more accurate and efficient data analysis process. By integrating these automated analysis methods with visualization, this research enables more accurate, efficient, and effective analysis of LWFA simulation data than previously possible.« less

Advances in microfluidics for drug discovery.

PubMed

Lombardi, Dario; Dittrich, Petra S

2010-11-01

Microfluidics is considered as an enabling technology for the development of unconventional and innovative methods in the drug discovery process. The concept of micrometer-sized reaction systems in the form of continuous flow reactors, microdroplets or microchambers is intriguing, and the versatility of the technology perfectly fits with the requirements of drug synthesis, drug screening and drug testing. In this review article, we introduce key microfluidic approaches to the drug discovery process, highlighting the latest and promising achievements in this field, mainly from the years 2007 - 2010. Despite high expectations of microfluidic approaches to several stages of the drug discovery process, up to now microfluidic technology has not been able to significantly replace conventional drug discovery platforms. Our aim is to identify bottlenecks that have impeded the transfer of microfluidics into routine platforms for drug discovery and show some recent solutions to overcome these hurdles. Although most microfluidic approaches are still applied only for proof-of-concept studies, thanks to creative microfluidic research in the past years unprecedented novel capabilities of microdevices could be demonstrated, and general applicable, robust and reliable microfluidic platforms seem to be within reach.

Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System.

PubMed

Chen, Donghua; Zhang, Runtong; Liu, Kecheng; Hou, Lei

2018-06-19

Patient-reported posts in Online Health Communities (OHCs) contain various valuable information that can help establish knowledge-based online support for online patients. However, utilizing these reports to improve online patient services in the absence of appropriate medical and healthcare expert knowledge is difficult. Thus, we propose a comprehensive knowledge discovery method that is based on the Unified Medical Language System for the analysis of narrative posts in OHCs. First, we propose a domain-knowledge support framework for OHCs to provide a basis for post analysis. Second, we develop a Knowledge-Involved Topic Modeling (KI-TM) method to extract and expand explicit knowledge within the text. We propose four metrics, namely, explicit knowledge rate, latent knowledge rate, knowledge correlation rate, and perplexity, for the evaluation of the KI-TM method. Our experimental results indicate that our proposed method outperforms existing methods in terms of providing knowledge support. Our method enhances knowledge support for online patients and can help develop intelligent OHCs in the future.

Learning in the context of distribution drift

DTIC Science & Technology

2017-05-09

published in the leading data mining journal, Data Mining and Knowledge Discovery (Webb et. al., 2016)1. We have shown that the previous qualitative...learner Low-bias learner Aggregated classifier Figure 7: Architecture for learning fr m streaming data in th co text of variable or unknown...Learning limited dependence Bayesian classifiers, in Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD

A Bioinformatic Approach to Inter Functional Interactions within Protein Sequences

DTIC Science & Technology

2009-02-23

AFOSR/AOARD Reference Number: USAFAOGA07: FA4869-07-1-4050 AFOSR/AOARD Program Manager : Hiroshi Motoda, Ph.D. Period of...Conference on Knowledge Discovery and Data Mining.) In a separate study we have applied our approaches to the problem of whole genome alignment. We have...SIGKDD Conference on Knowledge Discovery and Data Mining Attached. Interactions: Please list: (a) Participation/presentations at meetings

k-neighborhood Decentralization: A Comprehensive Solution to Index the UMLS for Large Scale Knowledge Discovery

PubMed Central

Xiang, Yang; Lu, Kewei; James, Stephen L.; Borlawsky, Tara B.; Huang, Kun; Payne, Philip R.O.

2011-01-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. PMID:22154838

k-Neighborhood decentralization: a comprehensive solution to index the UMLS for large scale knowledge discovery.

PubMed

Xiang, Yang; Lu, Kewei; James, Stephen L; Borlawsky, Tara B; Huang, Kun; Payne, Philip R O

2012-04-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. Copyright © 2011 Elsevier Inc. All rights reserved.

Concept of Operations for Collaboration and Discovery from Big Data Across Enterprise Data Warehouses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olama, Mohammed M; Nutaro, James J; Sukumar, Sreenivas R

2013-01-01

The success of data-driven business in government, science, and private industry is driving the need for seamless integration of intra and inter-enterprise data sources to extract knowledge nuggets in the form of correlations, trends, patterns and behaviors previously not discovered due to physical and logical separation of datasets. Today, as volume, velocity, variety and complexity of enterprise data keeps increasing, the next generation analysts are facing several challenges in the knowledge extraction process. Towards addressing these challenges, data-driven organizations that rely on the success of their analysts have to make investment decisions for sustainable data/information systems and knowledge discovery. Optionsmore » that organizations are considering are newer storage/analysis architectures, better analysis machines, redesigned analysis algorithms, collaborative knowledge management tools, and query builders amongst many others. In this paper, we present a concept of operations for enabling knowledge discovery that data-driven organizations can leverage towards making their investment decisions. We base our recommendations on the experience gained from integrating multi-agency enterprise data warehouses at the Oak Ridge National Laboratory to design the foundation of future knowledge nurturing data-system architectures.« less

The University of New Mexico Center for Molecular Discovery

PubMed Central

Edwards, Bruce S.; Gouveia, Kristine; Oprea, Tudor I.; Sklar, Larry A.

2015-01-01

The University of New Mexico Center for Molecular Discovery (UNMCMD) is an academic research center that specializes in discovery using high throughput flow cytometry (HTFC) integrated with virtual screening, as well as knowledge mining and drug informatics. With a primary focus on identifying small molecules that can be used as chemical probes and as leads for drug discovery, it is a central core resource for research and translational activities at UNM that supports implementation and management of funded screening projects as well as “up-front” services such as consulting for project design and implementation, assistance in assay development and generation of preliminary data for pilot projects in support of competitive grant applications. The HTFC platform in current use represents advanced, proprietary technology developed at UNM that is now routinely capable of processing bioassays arrayed in 96-, 384- and 1536-well formats at throughputs of 60,000 or more wells per day. Key programs at UNMCMD include screening of research targets submitted by the international community through NIH’s Molecular Libraries Program; a multi-year effort involving translational partnerships at UNM directed towards drug repurposing - identifying new uses for clinically approved drugs; and a recently established personalized medicine initiative for advancing cancer therapy by the application of “smart” oncology drugs in selected patients based on response patterns of their cancer cells in vitro. UNMCMD discoveries, innovation, and translation have contributed to a wealth of inventions, patents, licenses and publications, as well as startup companies, clinical trials and a multiplicity of domestic and international collaborative partnerships to further the research enterprise. PMID:24409953

The University of New Mexico Center for Molecular Discovery.

PubMed

Edwards, Bruce S; Gouveia, Kristine; Oprea, Tudor I; Sklar, Larry A

2014-03-01

The University of New Mexico Center for Molecular Discovery (UNMCMD) is an academic research center that specializes in discovery using high throughput flow cytometry (HTFC) integrated with virtual screening, as well as knowledge mining and drug informatics. With a primary focus on identifying small molecules that can be used as chemical probes and as leads for drug discovery, it is a central core resource for research and translational activities at UNM that supports implementation and management of funded screening projects as well as "up-front" services such as consulting for project design and implementation, assistance in assay development and generation of preliminary data for pilot projects in support of competitive grant applications. The HTFC platform in current use represents advanced, proprietary technology developed at UNM that is now routinely capable of processing bioassays arrayed in 96-, 384- and 1536-well formats at throughputs of 60,000 or more wells per day. Key programs at UNMCMD include screening of research targets submitted by the international community through NIH's Molecular Libraries Program; a multi-year effort involving translational partnerships at UNM directed towards drug repurposing - identifying new uses for clinically approved drugs; and a recently established personalized medicine initiative for advancing cancer therapy by the application of "smart" oncology drugs in selected patients based on response patterns of their cancer cells in vitro. UNMCMD discoveries, innovation, and translation have contributed to a wealth of inventions, patents, licenses and publications, as well as startup companies, clinical trials and a multiplicity of domestic and international collaborative partnerships to further the research enterprise.

X-ray crystallography over the past decade for novel drug discovery – where are we heading next?

PubMed Central

Zheng, Heping; Handing, Katarzyna B; Zimmerman, Matthew D; Shabalin, Ivan G; Almo, Steven C; Minor, Wladek

2015-01-01

Introduction Macromolecular X-ray crystallography has been the primary methodology for determining the three-dimensional structures of proteins, nucleic acids and viruses. Structural information has paved the way for structure-guided drug discovery and laid the foundations for structural bioinformatics. However, X-ray crystallography still has a few fundamental limitations, some of which may be overcome and complemented using emerging methods and technologies in other areas of structural biology. Areas covered This review describes how structural knowledge gained from X-ray crystallography has been used to advance other biophysical methods for structure determination (and vice versa). This article also covers current practices for integrating data generated by other biochemical and biophysical methods with those obtained from X-ray crystallography. Finally, the authors articulate their vision about how a combination of structural and biochemical/biophysical methods may improve our understanding of biological processes and interactions. Expert opinion X-ray crystallography has been, and will continue to serve as, the central source of experimental structural biology data used in the discovery of new drugs. However, other structural biology techniques are useful not only to overcome the major limitation of X-ray crystallography, but also to provide complementary structural data that is useful in drug discovery. The use of recent advancements in biochemical, spectroscopy and bioinformatics methods may revolutionize drug discovery, albeit only when these data are combined and analyzed with effective data management systems. Accurate and complete data management is crucial for developing experimental procedures that are robust and reproducible. PMID:26177814

Discovery Systems

NASA Technical Reports Server (NTRS)

Pell, Barney

2003-01-01

A viewgraph presentation on NASA's Discovery Systems Project is given. The topics of discussion include: 1) NASA's Computing Information and Communications Technology Program; 2) Discovery Systems Program; and 3) Ideas for Information Integration Using the Web.

15 CFR 280.210 - Discovery.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Discovery. 280.210 Section 280.210... STANDARDS AND TECHNOLOGY, DEPARTMENT OF COMMERCE ACCREDITATION AND ASSESSMENT PROGRAMS FASTENER QUALITY Enforcement § 280.210 Discovery. (a) General. The parties are encouraged to engage in voluntary discovery...

PubChem BioAssay: A Decade's Development toward Open High-Throughput Screening Data Sharing.

PubMed

Wang, Yanli; Cheng, Tiejun; Bryant, Stephen H

2017-07-01

High-throughput screening (HTS) is now routinely conducted for drug discovery by both pharmaceutical companies and screening centers at academic institutions and universities. Rapid advance in assay development, robot automation, and computer technology has led to the generation of terabytes of data in screening laboratories. Despite the technology development toward HTS productivity, fewer efforts were devoted to HTS data integration and sharing. As a result, the huge amount of HTS data was rarely made available to the public. To fill this gap, the PubChem BioAssay database ( https://www.ncbi.nlm.nih.gov/pcassay/ ) was set up in 2004 to provide open access to the screening results tested on chemicals and RNAi reagents. With more than 10 years' development and contributions from the community, PubChem has now become the largest public repository for chemical structures and biological data, which provides an information platform to worldwide researchers supporting drug development, medicinal chemistry study, and chemical biology research. This work presents a review of the HTS data content in the PubChem BioAssay database and the progress of data deposition to stimulate knowledge discovery and data sharing. It also provides a description of the database's data standard and basic utilities facilitating information access and use for new users.

A Workflow-based Intelligent Network Data Movement Advisor with End-to-end Performance Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Michelle M.; Wu, Chase Q.

2013-11-07

Next-generation eScience applications often generate large amounts of simulation, experimental, or observational data that must be shared and managed by collaborative organizations. Advanced networking technologies and services have been rapidly developed and deployed to facilitate such massive data transfer. However, these technologies and services have not been fully utilized mainly because their use typically requires significant domain knowledge and in many cases application users are even not aware of their existence. By leveraging the functionalities of an existing Network-Aware Data Movement Advisor (NADMA) utility, we propose a new Workflow-based Intelligent Network Data Movement Advisor (WINDMA) with end-to-end performance optimization formore » this DOE funded project. This WINDMA system integrates three major components: resource discovery, data movement, and status monitoring, and supports the sharing of common data movement workflows through account and database management. This system provides a web interface and interacts with existing data/space management and discovery services such as Storage Resource Management, transport methods such as GridFTP and GlobusOnline, and network resource provisioning brokers such as ION and OSCARS. We demonstrate the efficacy of the proposed transport-support workflow system in several use cases based on its implementation and deployment in DOE wide-area networks.« less

Knowledge extraction from evolving spiking neural networks with rank order population coding.

PubMed

Soltic, Snjezana; Kasabov, Nikola

2010-12-01

This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

NASA Astrophysics Data System (ADS)

Demir, I.; Sermet, M. Y.

2017-12-01

Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

An informatics research agenda to support precision medicine: seven key areas.

PubMed

Tenenbaum, Jessica D; Avillach, Paul; Benham-Hutchins, Marge; Breitenstein, Matthew K; Crowgey, Erin L; Hoffman, Mark A; Jiang, Xia; Madhavan, Subha; Mattison, John E; Nagarajan, Radhakrishnan; Ray, Bisakha; Shin, Dmitriy; Visweswaran, Shyam; Zhao, Zhongming; Freimuth, Robert R

2016-07-01

The recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to the forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue to evolve and datasets grow in magnitude, a strong computational infrastructure will be essential to realize PM's vision of improved healthcare derived from personal data. In addition, informatics research and innovation affords a tremendous opportunity to drive the science underlying PM. The informatics community must lead the development of technologies and methodologies that will increase the discovery and application of biomedical knowledge through close collaboration between researchers, clinicians, and patients. This perspective highlights seven key areas that are in need of further informatics research and innovation to support the realization of PM. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Understanding the Cellular and Molecular Mechanisms of Physical Activity-Induced Health Benefits.

PubMed

Neufer, P Darrell; Bamman, Marcas M; Muoio, Deborah M; Bouchard, Claude; Cooper, Dan M; Goodpaster, Bret H; Booth, Frank W; Kohrt, Wendy M; Gerszten, Robert E; Mattson, Mark P; Hepple, Russell T; Kraus, William E; Reid, Michael B; Bodine, Sue C; Jakicic, John M; Fleg, Jerome L; Williams, John P; Joseph, Lyndon; Evans, Mary; Maruvada, Padma; Rodgers, Mary; Roary, Mary; Boyce, Amanda T; Drugan, Jonelle K; Koenig, James I; Ingraham, Richard H; Krotoski, Danuta; Garcia-Cazarin, Mary; McGowan, Joan A; Laughlin, Maren R

2015-07-07

The beneficial effects of physical activity (PA) are well documented, yet the mechanisms by which PA prevents disease and improves health outcomes are poorly understood. To identify major gaps in knowledge and potential strategies for catalyzing progress in the field, the NIH convened a workshop in late October 2014 entitled "Understanding the Cellular and Molecular Mechanisms of Physical Activity-Induced Health Benefits." Presentations and discussions emphasized the challenges imposed by the integrative and intermittent nature of PA, the tremendous discovery potential of applying "-omics" technologies to understand interorgan crosstalk and biological networking systems during PA, and the need to establish an infrastructure of clinical trial sites with sufficient expertise to incorporate mechanistic outcome measures into adequately sized human PA trials. Identification of the mechanisms that underlie the link between PA and improved health holds extraordinary promise for discovery of novel therapeutic targets and development of personalized exercise medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

Generation of transgenic mouse model using PTTG as an oncogene.

PubMed

Kakar, Sham S; Kakar, Cohin

2015-01-01

The close physiological similarity between the mouse and human has provided tools to understanding the biological function of particular genes in vivo by introduction or deletion of a gene of interest. Using a mouse as a model has provided a wealth of resources, knowledge, and technology, helping scientists to understand the biological functions, translocation, trafficking, and interaction of a candidate gene with other intracellular molecules, transcriptional regulation, posttranslational modification, and discovery of novel signaling pathways for a particular gene. Most importantly, the generation of the mouse model for a specific human disease has provided a powerful tool to understand the etiology of a disease and discovery of novel therapeutics. This chapter describes in detail the step-by-step generation of the transgenic mouse model, which can be helpful in guiding new investigators in developing successful models. For practical purposes, we will describe the generation of a mouse model using pituitary tumor transforming gene (PTTG) as the candidate gene of interest.

The influence of ancient Greek thought on fifteenth century anatomy: Galenic influence and Leonardo da Vinci.

PubMed

Tubbs, Richard Isaiah; Gonzales, Jocelyn; Iwanaga, Joe; Loukas, Marios; Oskouian, Rod J; Tubbs, R Shane

2018-06-01

Leonardo da Vinci (1452-1519) can be called one of the earliest contributors to the history of anatomy and, by extension, the study of medicine. He may have even overshadowed Andreas Vesalius (1514-1564), the so-called founder of human anatomy, if his works had been published within his lifetime. While some of the best illustrations of their time, with our modern knowledge of anatomy, it is clear that many of da Vinci's depictions of human anatomy are inaccurate. However, he also made significant discoveries in anatomy and remarkable predictions of facts he could not yet discover with the technology available to him. Additionally, da Vinci was largely influenced by Greek anatomists, as indicated from his ideas about anatomical structure. In this historical review, we describe da Vinci's history, influences, and discoveries in anatomical research and his depictions and errors with regards to the musculoskeletal system, cardiovascular system, nervous system, and other organs.

Case study: impact of technology investment on lead discovery at Bristol-Myers Squibb, 1998-2006.

PubMed

Houston, John G; Banks, Martyn N; Binnie, Alastair; Brenner, Stephen; O'Connell, Jonathan; Petrillo, Edward W

2008-01-01

We review strategic approaches taken over an eight-year period at BMS to implement new high-throughput approaches to lead discovery. Investments in compound management infrastructure and chemistry library production capability allowed significant growth in the size, diversity and quality of the BMS compound collection. Screening platforms were upgraded with robust automated technology to support miniaturized assay formats, while workflows and information handling technologies were streamlined for improved performance. These technology changes drove the need for a supporting organization in which critical engineering, informatics and scientific skills were more strongly represented. Taken together, these investments led to significant improvements in speed and productivity as well a greater impact of screening campaigns on the initiation of new drug discovery programs.

Developing integrated crop knowledge networks to advance candidate gene discovery.

PubMed

Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher

2016-12-01

The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

The principle of safety evaluation in medicinal drug - how can toxicology contribute to drug discovery and development as a multidisciplinary science?

PubMed

Horii, Ikuo

2016-01-01

Pharmaceutical (drug) safety assessment covers a diverse science-field in the drug discovery and development including the post-approval and post-marketing phases in order to evaluate safety and risk management. The principle in toxicological science is to be placed on both of pure and applied sciences that are derived from past/present scientific knowledge and coming new science and technology. In general, adverse drug reactions are presented as "biological responses to foreign substances." This is the basic concept of thinking about the manifestation of adverse drug reactions. Whether or not toxic expressions are extensions of the pharmacological effect, adverse drug reactions as seen from molecular targets are captured in the category of "on-target" or "off-target", and are normally expressed as a biological defense reaction. Accordingly, reactions induced by pharmaceuticals can be broadly said to be defensive reactions. Recent molecular biological conception is in line with the new, remarkable scientific and technological developments in the medical and pharmaceutical areas, and the viewpoints in the field of toxicology have shown that they are approaching toward the same direction as well. This paper refers to the basic concept of pharmaceutical toxicology, the differences for safety assessment in each stage of drug discovery and development, regulatory submission, and the concept of scientific considerations for risk assessment and management from the viewpoint of "how can multidisciplinary toxicology contribute to innovative drug discovery and development?" And also realistic translational research from preclinical to clinical application is required to have a significant risk management in post market by utilizing whole scientific data derived from basic and applied scientific research works. In addition, the significance for employing the systems toxicology based on AOP (Adverse Outcome Pathway) analysis is introduced, and coming challenges on precision medicine are to be addressed for the new aspect of efficacy and safety evaluation.

Integration of Antibody Array Technology into Drug Discovery and Development.

PubMed

Huang, Wei; Whittaker, Kelly; Zhang, Huihua; Wu, Jian; Zhu, Si-Wei; Huang, Ruo-Pan

Antibody arrays represent a high-throughput technique that enables the parallel detection of multiple proteins with minimal sample volume requirements. In recent years, antibody arrays have been widely used to identify new biomarkers for disease diagnosis or prognosis. Moreover, many academic research laboratories and commercial biotechnology companies are starting to apply antibody arrays in the field of drug discovery. In this review, some technical aspects of antibody array development and the various platforms currently available will be addressed; however, the main focus will be on the discussion of antibody array technologies and their applications in drug discovery. Aspects of the drug discovery process, including target identification, mechanisms of drug resistance, molecular mechanisms of drug action, drug side effects, and the application in clinical trials and in managing patient care, which have been investigated using antibody arrays in recent literature will be examined and the relevance of this technology in progressing this process will be discussed. Protein profiling with antibody array technology, in addition to other applications, has emerged as a successful, novel approach for drug discovery because of the well-known importance of proteins in cell events and disease development.

48 CFR 927.402-1 - General.

Code of Federal Regulations, 2010 CFR

2010-10-01

... reasonable compensation for the use of its inventions and discoveries, including related data and technology... receive reasonable compensation for the use of its inventions and discoveries, including its related data and technology. Accordingly, in contracts where access to such restricted data is to be provided to...

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE PAGES

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; ...

2013-01-01

Background . The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective . To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods . The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expertmore » knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results . The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions . Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

PubMed Central

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

2013-01-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification. PMID:24223463

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.

2013-10-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integratedmore » into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Discovery stories in the science classroom

NASA Astrophysics Data System (ADS)

Arya, Diana Jaleh

School science has been criticized for its lack of emphasis on the tentative, dynamic nature of science as a process of learning more about our world. This criticism is the guiding force for this present body of work, which focuses on the question: what are the educational benefits for middle school students of reading texts that highlight the process of science in the form of a discovery narrative? This dissertation traces my journey through a review of theoretical perspectives of narrative, an analysis of first-hand accounts of scientific discovery, the complex process of developing age-appropriate, cohesive and engaging science texts for middle school students, and a comparison study (N=209) that seeks to determine the unique benefits of the scientific discovery narrative for the interest in and retained understanding of conceptual information presented in middle school science texts. A total of 209 middle school participants in nine different classrooms from two different schools participated in the experimental study. Each subject read two science texts that differed in topic (the qualities of and uses for radioactive elements and the use of telescopic technology to see planets in space) and genre (the discovery narrative and the "conceptually known exposition" comparison text). The differences between the SDN and CKE versions for each topic were equivalent in all possible ways (initial introduction, overall conceptual accuracy, elements of human interest, coherence and readability level), save for the unique components of the discovery narrative (i.e., love for their work, acknowledgement of the known, identification of the unknown and the explorative or experimental process to discovery). Participants generally chose the discovery narrative version as the more interesting of the two texts. Additional findings from the experimental study suggest that science texts in the form of SDNs elicit greater long-term retention of key conceptual information, especially when the readers have little prior knowledge of a given topic. Further, ethnic minority groups of lower socio-economic level (i.e., Latin and African-American origins) demonstrated an even greater benefit from the SDN texts, suggesting that a scientist's story of discovery can help to close the gap in academic performance in science.

Lessons learned in deploying a cloud-based knowledge platform for the Earth Science Information Partners Federation (ESIP)

NASA Astrophysics Data System (ADS)

Pouchard, L. C.; Depriest, A.; Huhns, M.

2012-12-01

Ontologies and semantic technologies are an essential infrastructure component of systems supporting knowledge integration in the Earth Sciences. Numerous earth science ontologies exist, but are hard to discover because they tend to be hosted with the projects that develop them. There are often few quality measures and sparse metadata associated with these ontologies, such as modification dates, versioning, purpose, number of classes, and properties. Projects often develop ontologies for their own needs without considering existing ontology entities or derivations from formal and more basic ontologies. The result is mostly orthogonal ontologies, and ontologies that are not modular enough to reuse in part or adapt for new purposes, in spite of existing, standards for ontology representation. Additional obstacles to sharing and reuse include a lack of maintenance once a project is completed. The obstacles prevent the full exploitation of semantic technologies in a context where they could become needed enablers for service discovery and for matching data with services. To start addressing this gap, we have deployed BioPortal, a mature, domain-independent ontology and semantic service system developed by the National Center for Biomedical Ontologies (NCBO), on the ESIP Testbed under the governance of the ESIP Semantic Web cluster. ESIP provides a forum for a broad-based, distributed community of data and information technology practitioners and stakeholders to coordinate their efforts and develop new ideas for interoperability solutions. The Testbed provides an environment where innovations and best practices can be explored and evaluated. One objective of this deployment is to provide a community platform that would harness the organizational and cyber infrastructure provided by ESIP at minimal costs. Another objective is to host ontology services on a scalable, public cloud and investigate the business case for crowd sourcing of ontology maintenance. We deployed the system on Amazon 's Elastic Compute Cloud (EC2) where ESIP maintains an account. Our approach had three phases: 1) set up a private cloud environment at the University of South Carolina to become familiar with the complex architecture of the system and enable some basic customization, 2) coordinate the production of a Virtual Appliance for the system with NCBO and deploy it on the Amazon cloud, and 3) outreach to the ESIP community to solicit participation, populate the repository, and develop new use cases. Phase 2 is nearing completion and Phase 3 is underway. Ontologies were gathered during updates to the ESIP cluster. Discussion points included the criteria for a shareable ontology and how to determine the best size for an ontology to be reusable. Outreach highlighted that the system can start addressing an integration of discovery frameworks via linking data and services in a pull model (data and service casting), a key issue of the Discovery cluster. This work thus presents several contributions: 1) technology injection from another domain into the earth sciences, 2) the deployment of a mature knowledge platform on the EC2 cloud, and 3) the successful engagement of the community through the ESIP clusters and Testbed model.

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

Can science be a business? Lessons from biotech.

PubMed

Pisano, Gary P

2006-10-01

In 1976, Genentech, the first biotechnology company, was founded by a young venture capitalist and a university professor to exploit recombinant DNA technology. Thirty years and more than 300 billion dollars in investments later, only a handful of biotech firms have matched Genentech's success or even shown a profit. No avalanche of new drugs has hit the market, and the long-awaited breakthrough in R&D productivity has yet to materialize. This disappointing performance raises a question: Can organizations motivated by the need to make profits and please shareholders successfully conduct basic scientific research as a core activity? The question has largely been ignored, despite intense debate over whether business's invasion of basic science-long the domain of universities and nonprofit research institutions- is limiting access to discoveries, thereby slowing advances in science. Biotech has not lived up to its promise, says the author, because its anatomy, which has worked well in other high-tech sectors, can't handle the fundamental challenges facing drug R&D: profound, persistent uncertainty and high risks rooted in the limited knowledge of human biology; the need for the diverse disciplines involved in drug discovery to work together in an integrated fashion; and barriers to learning, including tacit knowledge and murky intellectual property rights, which can slow the pace of scientific advance. A more suitable anatomy would include increased vertical integration; a smaller number of closer, longer collaborations; an emphasis by universities on sharing rather than patenting scientific discoveries; more cross-disciplinary academic research; and more federal and private funding for translational research, which bridges basic and applied science. With such modifications, science can be a business.

Current status and future prospects for enabling chemistry technology in the drug discovery process.

PubMed

Djuric, Stevan W; Hutchins, Charles W; Talaty, Nari N

2016-01-01

This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of "dangerous" reagents. Also featured are advances in the "computer-assisted drug design" area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities.

[Frontiers in Live Bone Imaging Researches. Novel drug discovery by means of intravital bone imaging technology].

PubMed

Ishii, Masaru

2015-06-01

Recent advances in intravital bone imaging technology has enabled us to grasp the real cellular behaviors and functions in vivo , revolutionizing the field of drug discovery for novel therapeutics against intractable bone diseases. In this chapter, I introduce various updated information on pharmacological actions of several antibone resorptive agents, which could only be derived from advanced imaging techniques, and also discuss the future perspectives of this new trend in drug discovery.

The future (and past) of quantum theory after the Higgs boson: a quantum-informational viewpoint.

PubMed

Plotnitsky, Arkady

2016-05-28

Taking as its point of departure the discovery of the Higgs boson, this article considers quantum theory, including quantum field theory, which predicted the Higgs boson, through the combined perspective of quantum information theory and the idea of technology, while also adopting anon-realistinterpretation, in 'the spirit of Copenhagen', of quantum theory and quantum phenomena themselves. The article argues that the 'events' in question in fundamental physics, such as the discovery of the Higgs boson (a particularly complex and dramatic, but not essentially different, case), are made possible by the joint workings of three technologies: experimental technology, mathematical technology and, more recently, digital computer technology. The article will consider the role of and the relationships among these technologies, focusing on experimental and mathematical technologies, in quantum mechanics (QM), quantum field theory (QFT) and finite-dimensional quantum theory, with which quantum information theory has been primarily concerned thus far. It will do so, in part, by reassessing the history of quantum theory, beginning with Heisenberg's discovery of QM, in quantum-informational and technological terms. This history, the article argues, is defined by the discoveries of increasingly complex configurations of observed phenomena and the emergence of the increasingly complex mathematical formalism accounting for these phenomena, culminating in the standard model of elementary-particle physics, defining the current state of QFT. © 2016 The Author(s).

Requirement of scientific documentation for the development of Naturopathy.

PubMed

Rastogi, Rajiv

2006-01-01

Past few decades have witnessed explosion of knowledge in almost every field. This has resulted not only in the advancement of the subjects in particular but also have influenced the growth of various allied subjects. The present paper explains about the advancement of science through efforts made in specific areas and also through discoveries in different allied fields having an indirect influence upon the subject in proper. In Naturopathy this seems that though nothing particular is added to the basic thoughts or fundamental principles of the subject yet the entire treatment understanding is revolutionised under the influence of scientific discoveries of past few decades. Advent of information technology has further added to the boom of knowledge and many times this seems impossible to utilize these informations for the good of human being because these are not logically arranged in our minds. In the above background, the author tries to define documentation stating that we have today ocean of information and knowledge about various things- living or dead, plants, animals or human beings; the geographical conditions or changing weather and environment. What required to be done is to extract the relevant knowledge and information required to enrich the subject. The author compares documentation with churning of milk to extract butter. Documentation, in fact, is churning of ocean of information to extract the specific, most appropriate, relevant and defined information and knowledge related to the particular subject . The paper besides discussing the definition of documentation, highlights the areas of Naturopathy requiring an urgent necessity to make proper documentations. Paper also discusses the present status of Naturopathy in India, proposes short-term and long-term goals to be achieved and plans the strategies for achieving them. The most important aspect of the paper is due understanding of the limitations of Naturopathy but a constant effort to improve the same with the growth made in various discipline of science so far.

Practical Semantic Astronomy

NASA Astrophysics Data System (ADS)

Graham, Matthew; Gray, N.; Burke, D.

2010-01-01

Many activities in the era of data-intensive astronomy are predicated upon some transference of domain knowledge and expertise from human to machine. The semantic infrastructure required to support this is no longer a pipe dream of computer science but a set of practical engineering challenges, more concerned with deployment and performance details than AI abstractions. The application of such ideas promises to help in such areas as contextual data access, exploiting distributed annotation and heterogeneous sources, and intelligent data dissemination and discovery. In this talk, we will review the status and use of semantic technologies in astronomy, particularly to address current problems in astroinformatics, with such projects as SKUA and AstroCollation.

Processing-in-Memory Technology for Knowledge Discovery Algorithms

DTIC Science & Technology

2006-07-01

e MP EG 2-d ist1 EP IC -u nq ua nti ze GS M- Ca lcu lat ion Sp ee du p ov er b as el in e MIT-SLP SLP SLPCF SLPCF+SLL 15 8 our infrastructure...to non-threat groups as well. Figure 15: Summary of ARDA/Eagle Data Sets. D at as et #o f N od es (P eo pl e ) #o f L in ks A vg . F an ou t Ph...on e C al ls Te le co ns Te le co n R es po nd en ts A vg . T el ec on Pa rt

The intriguing history of vertebral fusion anomalies: the Klippel-Feil syndrome.

PubMed

Saker, Erfanul; Loukas, Marios; Oskouian, Rod J; Tubbs, R Shane

2016-09-01

Our knowledge and understanding of vertebral fusion, defined and eponymously known as Klippel-Feil syndrome in the early 1900s, have a long history. This uncommon finding has been identified as early as 500 B.C. in an Egyptian mummy. Many more examples of spinal vertebra fusion have been described by Greek historians and recovered by archeologists demonstrating this entity's rich history. Klippel-Feil syndrome is a rare skeletal anomaly characterized by abnormal fusion of two or more vertebrae. With the advent of newer molecular technology and genetic discoveries, we now have a better understanding of the etiology and possible pathogenesis of this disease.

Analyzing Tibetan Monastic Conceptions of the Universe Through Individual Drawings

NASA Astrophysics Data System (ADS)

Sonam, Tenzin; Impey, Chris David

2017-01-01

Every culture and tradition has its own representation of the universe that continues to evolve due to the influence of new technologies, discoveries, and cultural exchanges. With the recent introduction of Western science into the Tibetan Buddhist monasteries in India, this study explores monastic conceptions of the universe prior to formal instruction in astronomy. The drawings of 59 Buddhist monks and nuns were analyzed using Tversky’s three criteria for drawing analysis—segmentation, order, and hierarchical structure of knowledge. We found that 22 out of 59 monastics drew a geocentric model of the universe with the Solar System as the dominant physical system, reflecting little influence of modern astronomical knowledge. Only six monastics drew the traditional Buddhist model of the world, generally known as the Mount Meru Cosmology. The implication of the monastics' representation of the universe for their assimilation into modern science is discussed.

Combinatorial and high-throughput screening of materials libraries: review of state of the art.

PubMed

Potyrailo, Radislav; Rajan, Krishna; Stoewe, Klaus; Takeuchi, Ichiro; Chisholm, Bret; Lam, Hubert

2011-11-14

Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimization of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characterization approaches, advances in data analysis/mining, and new materials developments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and functional materials, polymer-based industrial coatings, sensing materials, and biomaterials.

RNA regulatory networks in animals and plants: a long noncoding RNA perspective.

PubMed

Bai, Youhuang; Dai, Xiaozhuan; Harrison, Andrew P; Chen, Ming

2015-03-01

A recent highlight of genomics research has been the discovery of many families of transcripts which have function but do not code for proteins. An important group is long noncoding RNAs (lncRNAs), which are typically longer than 200 nt, and whose members originate from thousands of loci across genomes. We review progress in understanding the biogenesis and regulatory mechanisms of lncRNAs. We describe diverse computational and high throughput technologies for identifying and studying lncRNAs. We discuss the current knowledge of functional elements embedded in lncRNAs as well as insights into the lncRNA-based regulatory network in animals. We also describe genome-wide studies of large amount of lncRNAs in plants, as well as knowledge of selected plant lncRNAs with a focus on biotic/abiotic stress-responsive lncRNAs. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Ontology-based content analysis of US patent applications from 2001-2010.

PubMed

Weber, Lutz; Böhme, Timo; Irmer, Matthias

2013-01-01

Ontology-based semantic text analysis methods allow to automatically extract knowledge relationships and data from text documents. In this review, we have applied these technologies for the systematic analysis of pharmaceutical patents. Hierarchical concepts from the knowledge domains of chemical compounds, diseases and proteins were used to annotate full-text US patent applications that deal with pharmacological activities of chemical compounds and filed in the years 2001-2010. Compounds claimed in these applications have been classified into their respective compound classes to review the distribution of scaffold types or general compound classes such as natural products in a time-dependent manner. Similarly, the target proteins and claimed utility of the compounds have been classified and the most relevant were extracted. The method presented allows the discovery of the main areas of innovation as well as emerging fields of patenting activities - providing a broad statistical basis for competitor analysis and decision-making efforts.

The universe unveiled : instruments and images through history

NASA Astrophysics Data System (ADS)

Stephenson, Bruce; Bolt, Marvin; Friedman, Anna Felicity

2000-11-01

The search for understanding creates more than answers; it also produces instruments, books, maps, and other tools made and used by those seeking knowledge. The Universe Unveiled uniquely focuses on these artifacts and devices resulting from the attempts to decipher the Universe from the late fifteenth to the early twentieth century. Beautiful, full-color photographs capture these extremely rare and sometimes unusual curios. Beginning with the discovery of ways to keep time, The Universe Unveiled depicts the shift from an Earth-centered understanding of the Universe to a Sun-centered view, the mapping of the stars, and the ever-expanding knowledge of the heavens using telescopes. It also examines the developing technologies of navigation and of the measuring and mapping of the Earth. In addition to rare European curios, the book is illustrated with non-Western and American works. With more than 250 full-color images, this unique volume will delight the inventive as well as the curious.

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

Analyzing Tibetan Monastics Conception of Universe Through Their Drawings

NASA Astrophysics Data System (ADS)

Sonam, Tenzin; Chris Impey

2016-06-01

Every culture and tradition has their own representation of the universe that continues to evolve through new technologies and discoveries, and as a result of cultural exchange. With the recent introduction of Western science into the Tibetan Buddhist monasteries in India, this study explores the monastics’ conception of the universe prior to their formal instruction in science. Their drawings were analyzed using Tversky’s three criteria for drawing analysis namely—segmentation, order, and hierarchical structure of knowledge. Among the sixty Buddhist monastics included in this study, we find that most of them draw a geocentric model of the universe with the Solar System as the dominant physical system, reflecting little influence of modern astronomical knowledge. A few monastics draw the traditional Buddhist model of the world. The implications of the monastics' representation of the universe for their assimilation of modern science is discussed.

Good surgeon: A search for meaning.

PubMed

Akopov, Andrey L; Artioukh, Dmitri Y

2017-01-01

The art and philosophy of surgery are not as often discussed as scientific discoveries and technological advances in the modern era of surgery. Although these are difficult to teach and pass on to the next generations of surgeons they are no less important for training good surgeons and maintaining their high standards. The authors of this review and opinion article tried to define what being a good surgeon really means and to look into the subject by analysing the essential conditions for being a good surgeon and the qualities that such a specialist should possess. In addition to a strong theoretic knowledge and practical skills and among the several described professional and personal characteristics, a good surgeon is expected to have common sense. It enables a surgeon to make a sound practical judgment independent of specialized medical knowledge and training. The possible ways of developing and/or enhancing common sense during surgical training and subsequent practice require separate analysis.

On the Growth of Scientific Knowledge: Yeast Biology as a Case Study

PubMed Central

He, Xionglei; Zhang, Jianzhi

2009-01-01

The tempo and mode of human knowledge expansion is an enduring yet poorly understood topic. Through a temporal network analysis of three decades of discoveries of protein interactions and genetic interactions in baker's yeast, we show that the growth of scientific knowledge is exponential over time and that important subjects tend to be studied earlier. However, expansions of different domains of knowledge are highly heterogeneous and episodic such that the temporal turnover of knowledge hubs is much greater than expected by chance. Familiar subjects are preferentially studied over new subjects, leading to a reduced pace of innovation. While research is increasingly done in teams, the number of discoveries per researcher is greater in smaller teams. These findings reveal collective human behaviors in scientific research and help design better strategies in future knowledge exploration. PMID:19300476

On the growth of scientific knowledge: yeast biology as a case study.

PubMed

He, Xionglei; Zhang, Jianzhi

2009-03-01

The tempo and mode of human knowledge expansion is an enduring yet poorly understood topic. Through a temporal network analysis of three decades of discoveries of protein interactions and genetic interactions in baker's yeast, we show that the growth of scientific knowledge is exponential over time and that important subjects tend to be studied earlier. However, expansions of different domains of knowledge are highly heterogeneous and episodic such that the temporal turnover of knowledge hubs is much greater than expected by chance. Familiar subjects are preferentially studied over new subjects, leading to a reduced pace of innovation. While research is increasingly done in teams, the number of discoveries per researcher is greater in smaller teams. These findings reveal collective human behaviors in scientific research and help design better strategies in future knowledge exploration.

Integrated Computational Analysis of Genes Associated with Human Hereditary Insensitivity to Pain. A Drug Repurposing Perspective

PubMed Central

Lötsch, Jörn; Lippmann, Catharina; Kringel, Dario; Ultsch, Alfred

2017-01-01

Genes causally involved in human insensitivity to pain provide a unique molecular source of studying the pathophysiology of pain and the development of novel analgesic drugs. The increasing availability of “big data” enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 20 genes causally involved in human hereditary insensitivity to pain with the knowledge about the functions of thousands of genes. An integrated computational analysis proposed that among the functions of this set of genes, the processes related to nervous system development and to ceramide and sphingosine signaling pathways are particularly important. This is in line with earlier suggestions to use these pathways as therapeutic target in pain. Following identification of the biological processes characterizing hereditary insensitivity to pain, the biological processes were used for a similarity analysis with the functions of n = 4,834 database-queried drugs. Using emergent self-organizing maps, a cluster of n = 22 drugs was identified sharing important functional features with hereditary insensitivity to pain. Several members of this cluster had been implicated in pain in preclinical experiments. Thus, the present concept of machine-learned knowledge discovery for pain research provides biologically plausible results and seems to be suitable for drug discovery by identifying a narrow choice of repurposing candidates, demonstrating that contemporary machine-learned methods offer innovative approaches to knowledge discovery from available evidence. PMID:28848388

Current status and future prospects for enabling chemistry technology in the drug discovery process

PubMed Central

Djuric, Stevan W.; Hutchins, Charles W.; Talaty, Nari N.

2016-01-01

This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of “dangerous” reagents. Also featured are advances in the “computer-assisted drug design” area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities. PMID:27781094

RNA interference for functional genomics and improvement of cotton (Gossypium species)

USDA-ARS?s Scientific Manuscript database

RNA interference (RNAi), is a powerful new technology in the discovery of genetic sequence functions, and has become a valuable tool for functional genomics of cotton (Gossypium ssp.). The rapid adoption of RNAi has replaced previous antisense technology. RNAi has aided in the discovery of function ...

Three education modules using EnviroAtlas-Exploration and Discovery Through Maps: Teaching Science with Technology

EPA Science Inventory

Session #1: Exploration and Discovery through Maps: Teaching Science with Technology (elementary school) - EnviroAtlas is a tool developed by the U.S. Environmental Protection Agency and its partners that empowers anyone with the internet to be a highly informed local decision-ma...

Applying Knowledge Discovery in Databases in Public Health Data Set: Challenges and Concerns

PubMed Central

Volrathongchia, Kanittha

2003-01-01

In attempting to apply Knowledge Discovery in Databases (KDD) to generate a predictive model from a health care dataset that is currently available to the public, the first step is to pre-process the data to overcome the challenges of missing data, redundant observations, and records containing inaccurate data. This study will demonstrate how to use simple pre-processing methods to improve the quality of input data. PMID:14728545

Exploiting Early Intent Recognition for Competitive Advantage

DTIC Science & Technology

2009-01-01

basketball [Bhan- dari et al., 1997; Jug et al., 2003], and Robocup soccer sim- ulations [Riley and Veloso, 2000; 2002; Kuhlmann et al., 2006] and non...actions (e.g. before, after, around). Jug et al. [2003] used a similar framework for offline basketball game analysis. More recently, Hess et al...and K. Ramanujam. Advanced Scout: Data mining and knowledge discovery in NBA data. Data Mining and Knowledge Discovery, 1(1):121–125, 1997. [Chang

An Alternative Time for Telling: When Conceptual Instruction Prior to Exploration Improves Mathematical Knowledge

ERIC Educational Resources Information Center

Fyfe, Emily R.; DeCaro, Marci S.; Rittle-Johnson, Bethany

2013-01-01

An emerging consensus suggests that guided discovery, which combines discovery and instruction, is a more effective educational approach than either one in isolation. The goal of this study was to examine two specific forms of guided discovery, testing whether conceptual instruction should precede or follow exploratory problem solving. In both…

Ethnobotany and Medicinal Plant Biotechnology: From Tradition to Modern Aspects of Drug Development.

PubMed

Kayser, Oliver

2018-05-24

Secondary natural products from plants are important drug leads for the development of new drug candidates for rational clinical therapy and exhibit a variety of biological activities in experimental pharmacology and serve as structural template in medicinal chemistry. The exploration of plants and discovery of natural compounds based on ethnopharmacology in combination with high sophisticated analytics is still today an important drug discovery to characterize and validate potential leads. Due to structural complexity, low abundance in biological material, and high costs in chemical synthesis, alternative ways in production like plant cell cultures, heterologous biosynthesis, and synthetic biotechnology are applied. The basis for any biotechnological process is deep knowledge in genetic regulation of pathways and protein expression with regard to todays "omics" technologies. The high number genetic techniques allowed the implementation of combinatorial biosynthesis and wide genome sequencing. Consequently, genetics allowed functional expression of biosynthetic cascades from plants and to reconstitute low-performing pathways in more productive heterologous microorganisms. Thus, de novo biosynthesis in heterologous hosts requires fundamental understanding of pathway reconstruction and multitude of genes in a foreign organism. Here, actual concepts and strategies are discussed for pathway reconstruction and genome sequencing techniques cloning tools to bridge the gap between ethnopharmaceutical drug discovery to industrial biotechnology. Georg Thieme Verlag KG Stuttgart · New York.

Patterns of Innovation in Alzheimer's Disease Drug Development: A Strategic Assessment Based on Technological Maturity.

PubMed

Beierlein, Jennifer M; McNamee, Laura M; Walsh, Michael J; Ledley, Fred D

2015-08-01

This article examines the current status of translational science for Alzheimer's disease (AD) drug discovery by using an analytical model of technology maturation. Previous studies using this model have demonstrated that nascent scientific insights and inventions generate few successful leads or new products until achieving a requisite level of maturity. This article assessed whether recent failures and successes in AD research follow patterns of innovation observed in other sectors. The bibliometric-based Technology Innovation Maturation Evaluation model was used to quantify the characteristic S-curve of growth for AD-related technologies, including acetylcholinesterase, N-methyl-d-aspartate (NMDA) receptors, B-amyloid, amyloid precursor protein, presenilin, amyloid precursor protein secretases, apolipoprotein E4, and transactive response DNA binding protein 43 kDa (TDP-43). This model quantifies the accumulation of knowledge as a metric for technological maturity, and it identifies the point of initiation of an exponential growth stage and the point at which growth slows as the technology is established. In contrast to the long-established acetylcholinesterase and NMDA receptor technologies, we found that amyloid-related technologies reached the established point only after 2000, and that the more recent technologies (eg, TDP-43) have not yet approached this point. The first approvals for new molecular entities targeting acetylcholinesterase and the NMDA receptor occurred an average of 22 years after the respective technologies were established, with only memantine (which was phenotypically discovered) entering clinical trials before this point. In contrast, the 6 lead compounds targeting the formation of amyloid plaques that failed in Phase III trials between 2009 and 2014 all entered clinical trials before the respective target technologies were established. This analysis suggests that AD drug discovery has followed a predictable pattern of innovation in which technological maturity is an important determinant of success in development. Quantitative analysis indicates that the lag in emergence of new products, and the much-heralded clinical failures of recent years, should be viewed in the context of the ongoing maturation of AD-related technologies. Although these technologies were not sufficiently mature to generate successful products a decade ago, they may be now. Analytical models of translational science can inform basic and clinical research results as well as strategic development of new therapeutic products. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Knowledge Management in Higher Education: A Knowledge Repository Approach

ERIC Educational Resources Information Center

Wedman, John; Wang, Feng-Kwei

2005-01-01

One might expect higher education, where the discovery and dissemination of new and useful knowledge is vital, to be among the first to implement knowledge management practices. Surprisingly, higher education has been slow to implement knowledge management practices (Townley, 2003). This article describes an ongoing research and development effort…

Crowdsourcing Knowledge Discovery and Innovations in Medicine

PubMed Central

2014-01-01

Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. Clinicians are typically buried in the weeds and exigencies of daily practice such that they do not recognize or act on ways to improve knowledge discovery. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. “Health hackathons” and “data marathons”, in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled. PMID:25239002

Crowdsourcing knowledge discovery and innovations in medicine.

PubMed

Celi, Leo Anthony; Ippolito, Andrea; Montgomery, Robert A; Moses, Christopher; Stone, David J

2014-09-19

Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. Clinicians are typically buried in the weeds and exigencies of daily practice such that they do not recognize or act on ways to improve knowledge discovery. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. "Health hackathons" and "data marathons", in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled.

Empirical study using network of semantically related associations in bridging the knowledge gap.

PubMed

Abedi, Vida; Yeasin, Mohammed; Zand, Ramin

2014-11-27

The data overload has created a new set of challenges in finding meaningful and relevant information with minimal cognitive effort. However designing robust and scalable knowledge discovery systems remains a challenge. Recent innovations in the (biological) literature mining tools have opened new avenues to understand the confluence of various diseases, genes, risk factors as well as biological processes in bridging the gaps between the massive amounts of scientific data and harvesting useful knowledge. In this paper, we highlight some of the findings using a text analytics tool, called ARIANA--Adaptive Robust and Integrative Analysis for finding Novel Associations. Empirical study using ARIANA reveals knowledge discovery instances that illustrate the efficacy of such tool. For example, ARIANA can capture the connection between the drug hexamethonium and pulmonary inflammation and fibrosis that caused the tragic death of a healthy volunteer in a 2001 John Hopkins asthma study, even though the abstract of the study was not part of the semantic model. An integrated system, such as ARIANA, could assist the human expert in exploratory literature search by bringing forward hidden associations, promoting data reuse and knowledge discovery as well as stimulating interdisciplinary projects by connecting information across the disciplines.

The nearly universal link between the age of past knowledge and tomorrow’s breakthroughs in science and technology: The hotspot

PubMed Central

Mukherjee, Satyam; Romero, Daniel M.; Jones, Ben; Uzzi, Brian

2017-01-01

Scientists and inventors can draw on an ever-expanding literature for the building blocks of tomorrow’s ideas, yet little is known about how combinations of past work are related to future discoveries. Our analysis parameterizes the age distribution of a work’s references and revealed three links between the age of prior knowledge and hit papers and patents. First, works that cite literature with a low mean age and high age variance are in a citation “hotspot”; these works double their likelihood of being in the top 5% or better of citations. Second, the hotspot is nearly universal in all branches of science and technology and is increasingly predictive of a work’s future citation impact. Third, a scientist or inventor is significantly more likely to write a paper in the hotspot when they are coauthoring than whey they are working alone. Our findings are based on all 28,426,345 scientific papers in the Web of Science, 1945–2013, and all 5,382,833 U.S. patents, 1950–2010, and reveal new antecedents of high-impact science and the link between prior literature and tomorrow’s breakthrough ideas. PMID:28439537

The nearly universal link between the age of past knowledge and tomorrow's breakthroughs in science and technology: The hotspot.

PubMed

Mukherjee, Satyam; Romero, Daniel M; Jones, Ben; Uzzi, Brian

2017-04-01

Scientists and inventors can draw on an ever-expanding literature for the building blocks of tomorrow's ideas, yet little is known about how combinations of past work are related to future discoveries. Our analysis parameterizes the age distribution of a work's references and revealed three links between the age of prior knowledge and hit papers and patents. First, works that cite literature with a low mean age and high age variance are in a citation "hotspot"; these works double their likelihood of being in the top 5% or better of citations. Second, the hotspot is nearly universal in all branches of science and technology and is increasingly predictive of a work's future citation impact. Third, a scientist or inventor is significantly more likely to write a paper in the hotspot when they are coauthoring than whey they are working alone. Our findings are based on all 28,426,345 scientific papers in the Web of Science, 1945-2013, and all 5,382,833 U.S. patents, 1950-2010, and reveal new antecedents of high-impact science and the link between prior literature and tomorrow's breakthrough ideas.

Conifer genomics and adaptation: at the crossroads of genetic diversity and genome function.

PubMed

Prunier, Julien; Verta, Jukka-Pekka; MacKay, John J

2016-01-01

Conifers have been understudied at the genomic level despite their worldwide ecological and economic importance but the situation is rapidly changing with the development of next generation sequencing (NGS) technologies. With NGS, genomics research has simultaneously gained in speed, magnitude and scope. In just a few years, genomes of 20-24 gigabases have been sequenced for several conifers, with several others expected in the near future. Biological insights have resulted from recent sequencing initiatives as well as genetic mapping, gene expression profiling and gene discovery research over nearly two decades. We review the knowledge arising from conifer genomics research emphasizing genome evolution and the genomic basis of adaptation, and outline emerging questions and knowledge gaps. We discuss future directions in three areas with potential inputs from NGS technologies: the evolutionary impacts of adaptation in conifers based on the adaptation-by-speciation model; the contributions of genetic variability of gene expression in adaptation; and the development of a broader understanding of genetic diversity and its impacts on genome function. These research directions promise to sustain research aimed at addressing the emerging challenges of adaptation that face conifer trees. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

High-throughput strategies for the discovery and engineering of enzymes for biocatalysis.

PubMed

Jacques, Philippe; Béchet, Max; Bigan, Muriel; Caly, Delphine; Chataigné, Gabrielle; Coutte, François; Flahaut, Christophe; Heuson, Egon; Leclère, Valérie; Lecouturier, Didier; Phalip, Vincent; Ravallec, Rozenn; Dhulster, Pascal; Froidevaux, Rénato

2017-02-01

Innovations in novel enzyme discoveries impact upon a wide range of industries for which biocatalysis and biotransformations represent a great challenge, i.e., food industry, polymers and chemical industry. Key tools and technologies, such as bioinformatics tools to guide mutant library design, molecular biology tools to create mutants library, microfluidics/microplates, parallel miniscale bioreactors and mass spectrometry technologies to create high-throughput screening methods and experimental design tools for screening and optimization, allow to evolve the discovery, development and implementation of enzymes and whole cells in (bio)processes. These technological innovations are also accompanied by the development and implementation of clean and sustainable integrated processes to meet the growing needs of chemical, pharmaceutical, environmental and biorefinery industries. This review gives an overview of the benefits of high-throughput screening approach from the discovery and engineering of biocatalysts to cell culture for optimizing their production in integrated processes and their extraction/purification.

Data mining in pharma sector: benefits.

PubMed

Ranjan, Jayanthi

2009-01-01

The amount of data getting generated in any sector at present is enormous. The information flow in the pharma industry is huge. Pharma firms are progressing into increased technology-enabled products and services. Data mining, which is knowledge discovery from large sets of data, helps pharma firms to discover patterns in improving the quality of drug discovery and delivery methods. The paper aims to present how data mining is useful in the pharma industry, how its techniques can yield good results in pharma sector, and to show how data mining can really enhance in making decisions using pharmaceutical data. This conceptual paper is written based on secondary study, research and observations from magazines, reports and notes. The author has listed the types of patterns that can be discovered using data mining in pharma data. The paper shows how data mining is useful in the pharma industry and how its techniques can yield good results in pharma sector. Although much work can be produced for discovering knowledge in pharma data using data mining, the paper is limited to conceptualizing the ideas and view points at this stage; future work may include applying data mining techniques to pharma data based on primary research using the available, famous significant data mining tools. Research papers and conceptual papers related to data mining in Pharma industry are rare; this is the motivation for the paper.

Text-based discovery in biomedicine: the architecture of the DAD-system.

PubMed

Weeber, M; Klein, H; Aronson, A R; Mork, J G; de Jong-van den Berg, L T; Vos, R

2000-01-01

Current scientific research takes place in highly specialized contexts with poor communication between disciplines as a likely consequence. Knowledge from one discipline may be useful for the other without researchers knowing it. As scientific publications are a condensation of this knowledge, literature-based discovery tools may help the individual scientist to explore new useful domains. We report on the development of the DAD-system, a concept-based Natural Language Processing system for PubMed citations that provides the biomedical researcher such a tool. We describe the general architecture and illustrate its operation by a simulation of a well-known text-based discovery: The favorable effects of fish oil on patients suffering from Raynaud's disease [1].

Which are the greatest recent discoveries and the greatest future challenges in nutrition?

PubMed

Katan, M B; Boekschoten, M V; Connor, W E; Mensink, R P; Seidell, J; Vessby, B; Willett, W

2009-01-01

Nutrition science aims to create new knowledge, but scientists rarely sit back to reflect on what nutrition research has achieved in recent decades. We report the outcome of a 1-day symposium at which the audience was asked to vote on the greatest discoveries in nutrition since 1976 and on the greatest challenges for the coming 30 years. Most of the 128 participants were Dutch scientists working in nutrition or related biomedical and public health fields. Candidate discoveries and challenges were nominated by five invited speakers and by members of the audience. Ballot forms were then prepared on which participants selected one discovery and one challenge. A total of 15 discoveries and 14 challenges were nominated. The audience elected Folic acid prevents birth defects as the greatest discovery in nutrition science since 1976. Controlling obesity and insulin resistance through activity and diet was elected as the greatest challenge for the coming 30 years. This selection was probably biased by the interests and knowledge of the speakers and the audience. For the present review, we therefore added 12 discoveries from the period 1976 to 2006 that we judged worthy of consideration, but that had not been nominated at the meeting. The meeting did not represent an objective selection process, but it did demonstrate that the past 30 years have yielded major new discoveries in nutrition and health.

The Application of the Open Pharmacological Concepts Triple Store (Open PHACTS) to Support Drug Discovery Research

PubMed Central

Ratnam, Joseline; Zdrazil, Barbara; Digles, Daniela; Cuadrado-Rodriguez, Emiliano; Neefs, Jean-Marc; Tipney, Hannah; Siebes, Ronald; Waagmeester, Andra; Bradley, Glyn; Chau, Chau Han; Richter, Lars; Brea, Jose; Evelo, Chris T.; Jacoby, Edgar; Senger, Stefan; Loza, Maria Isabel; Ecker, Gerhard F.; Chichester, Christine

2014-01-01

Integration of open access, curated, high-quality information from multiple disciplines in the Life and Biomedical Sciences provides a holistic understanding of the domain. Additionally, the effective linking of diverse data sources can unearth hidden relationships and guide potential research strategies. However, given the lack of consistency between descriptors and identifiers used in different resources and the absence of a simple mechanism to link them, gathering and combining relevant, comprehensive information from diverse databases remains a challenge. The Open Pharmacological Concepts Triple Store (Open PHACTS) is an Innovative Medicines Initiative project that uses semantic web technology approaches to enable scientists to easily access and process data from multiple sources to solve real-world drug discovery problems. The project draws together sources of publicly-available pharmacological, physicochemical and biomolecular data, represents it in a stable infrastructure and provides well-defined information exploration and retrieval methods. Here, we highlight the utility of this platform in conjunction with workflow tools to solve pharmacological research questions that require interoperability between target, compound, and pathway data. Use cases presented herein cover 1) the comprehensive identification of chemical matter for a dopamine receptor drug discovery program 2) the identification of compounds active against all targets in the Epidermal growth factor receptor (ErbB) signaling pathway that have a relevance to disease and 3) the evaluation of established targets in the Vitamin D metabolism pathway to aid novel Vitamin D analogue design. The example workflows presented illustrate how the Open PHACTS Discovery Platform can be used to exploit existing knowledge and generate new hypotheses in the process of drug discovery. PMID:25522365

Gathering and Exploring Scientific Knowledge in Pharmacovigilance

PubMed Central

Lopes, Pedro; Nunes, Tiago; Campos, David; Furlong, Laura Ines; Bauer-Mehren, Anna; Sanz, Ferran; Carrascosa, Maria Carmen; Mestres, Jordi; Kors, Jan; Singh, Bharat; van Mulligen, Erik; Van der Lei, Johan; Diallo, Gayo; Avillach, Paul; Ahlberg, Ernst; Boyer, Scott; Diaz, Carlos; Oliveira, José Luís

2013-01-01

Pharmacovigilance plays a key role in the healthcare domain through the assessment, monitoring and discovery of interactions amongst drugs and their effects in the human organism. However, technological advances in this field have been slowing down over the last decade due to miscellaneous legal, ethical and methodological constraints. Pharmaceutical companies started to realize that collaborative and integrative approaches boost current drug research and development processes. Hence, new strategies are required to connect researchers, datasets, biomedical knowledge and analysis algorithms, allowing them to fully exploit the true value behind state-of-the-art pharmacovigilance efforts. This manuscript introduces a new platform directed towards pharmacovigilance knowledge providers. This system, based on a service-oriented architecture, adopts a plugin-based approach to solve fundamental pharmacovigilance software challenges. With the wealth of collected clinical and pharmaceutical data, it is now possible to connect knowledge providers’ analysis and exploration algorithms with real data. As a result, new strategies allow a faster identification of high-risk interactions between marketed drugs and adverse events, and enable the automated uncovering of scientific evidence behind them. With this architecture, the pharmacovigilance field has a new platform to coordinate large-scale drug evaluation efforts in a unique ecosystem, publicly available at http://bioinformatics.ua.pt/euadr/. PMID:24349421

Information extraction and knowledge graph construction from geoscience literature

NASA Astrophysics Data System (ADS)

Wang, Chengbin; Ma, Xiaogang; Chen, Jianguo; Chen, Jingwen

2018-03-01

Geoscience literature published online is an important part of open data, and brings both challenges and opportunities for data analysis. Compared with studies of numerical geoscience data, there are limited works on information extraction and knowledge discovery from textual geoscience data. This paper presents a workflow and a few empirical case studies for that topic, with a focus on documents written in Chinese. First, we set up a hybrid corpus combining the generic and geology terms from geology dictionaries to train Chinese word segmentation rules of the Conditional Random Fields model. Second, we used the word segmentation rules to parse documents into individual words, and removed the stop-words from the segmentation results to get a corpus constituted of content-words. Third, we used a statistical method to analyze the semantic links between content-words, and we selected the chord and bigram graphs to visualize the content-words and their links as nodes and edges in a knowledge graph, respectively. The resulting graph presents a clear overview of key information in an unstructured document. This study proves the usefulness of the designed workflow, and shows the potential of leveraging natural language processing and knowledge graph technologies for geoscience.

Caenorhabditis elegans: nature and nurture gift to nematode parasitologists.

PubMed

Salinas, Gustavo; Risi, Gastón

2017-12-06

The free-living nematode Caenorhabditis elegans is the simplest animal model organism to work with. Substantial knowledge and tools have accumulated over 50 years of C. elegans research. The use of C. elegans relating to parasitic nematodes from a basic biology standpoint or an applied perspective has increased in recent years. The wealth of information gained on the model organism, the use of the powerful approaches and technologies that have advanced C. elegans research to parasitic nematodes and the enormous success of the omics fields have contributed to bridge the divide between C. elegans and parasite nematode researchers. We review key fields, such as genomics, drug discovery and genetics, where C. elegans and nematode parasite research have convened. We advocate the use of C. elegans as a model to study helminth metabolism, a neglected area ready to advance. How emerging technologies being used in C. elegans can pave the way for parasitic nematode research is discussed.

Brain Radiation Information Data Exchange (BRIDE): integration of experimental data from low-dose ionising radiation research for pathway discovery.

PubMed

Karapiperis, Christos; Kempf, Stefan J; Quintens, Roel; Azimzadeh, Omid; Vidal, Victoria Linares; Pazzaglia, Simonetta; Bazyka, Dimitry; Mastroberardino, Pier G; Scouras, Zacharias G; Tapio, Soile; Benotmane, Mohammed Abderrafi; Ouzounis, Christos A

2016-05-11

The underlying molecular processes representing stress responses to low-dose ionising radiation (LDIR) in mammals are just beginning to be understood. In particular, LDIR effects on the brain and their possible association with neurodegenerative disease are currently being explored using omics technologies. We describe a light-weight approach for the storage, analysis and distribution of relevant LDIR omics datasets. The data integration platform, called BRIDE, contains information from the literature as well as experimental information from transcriptomics and proteomics studies. It deploys a hybrid, distributed solution using both local storage and cloud technology. BRIDE can act as a knowledge broker for LDIR researchers, to facilitate molecular research on the systems biology of LDIR response in mammals. Its flexible design can capture a range of experimental information for genomics, epigenomics, transcriptomics, and proteomics. The data collection is available at: .

Genomics education in nursing in the United States.

PubMed

Calzone, Kathleen A; Jenkins, Jean

2011-01-01

Discovery of the genetics/genomics underpinnings of health, risk for disease, sickness, and treatment response have the prospects of improving recognition and management of at risk individuals; improving screening, prognostics, and therapeutic decision-making; expanding targeted therapies; and improving the accuracy of medication dosing and selection based on drug metabolism genetic variation. Thus, genetics/genomics science, information, and technologies influence the entire health care continuum and are fundamental to the nursing profession. Translating the benefits of genetics and genomics into health care requires that nurses are knowledgeable about and able to integrate this information and technology into their practice. This chapter explores the development of essential nursing competences in genetics and genomics and outcome indicators. Included is an overview of projects aimed at measuring and/or supporting adoption and integration of such competencies. Included as well is an update reviewing current evidence of the state of genomics nursing education in the United States and recommendations for next steps.

Distributed data mining on grids: services, tools, and applications.

PubMed

Cannataro, Mario; Congiusta, Antonio; Pugliese, Andrea; Talia, Domenico; Trunfio, Paolo

2004-12-01

Data mining algorithms are widely used today for the analysis of large corporate and scientific datasets stored in databases and data archives. Industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed and parallel systems. The grid can play a significant role in providing an effective computational support for distributed knowledge discovery applications. For the development of data mining applications on grids we designed a system called Knowledge Grid. This paper describes the Knowledge Grid framework and presents the toolset provided by the Knowledge Grid for implementing distributed knowledge discovery. The paper discusses how to design and implement data mining applications by using the Knowledge Grid tools starting from searching grid resources, composing software and data components, and executing the resulting data mining process on a grid. Some performance results are also discussed.

Building Scalable Knowledge Graphs for Earth Science

NASA Technical Reports Server (NTRS)

Ramachandran, Rahul; Maskey, Manil; Gatlin, Patrick; Zhang, Jia; Duan, Xiaoyi; Miller, J. J.; Bugbee, Kaylin; Christopher, Sundar; Freitag, Brian

2017-01-01

Knowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.

Genetic discoveries and nursing implications for complex disease prevention and management.

PubMed

Frazier, Lorraine; Meininger, Janet; Halsey Lea, Dale; Boerwinkle, Eric

2004-01-01

The purpose of this article is to examine the management of patients with complex diseases, in light of recent genetic discoveries, and to explore how these genetic discoveries will impact nursing practice and nursing research. The nursing science processes discussed are not comprehensive of all nursing practice but, instead, are concentrated in areas where genetics will have the greatest influence. Advances in genetic science will revolutionize our approach to patients and to health care in the prevention, diagnosis, and treatment of disease, raising many issues for nursing research and practice. As the scope of genetics expands to encompass multifactorial disease processes, a continuing reexamination of the knowledge base is required for nursing practice, with incorporation of genetic knowledge into the repertoire of every nurse, and with advanced knowledge for nurses who select specialty roles in the genetics area. This article explores the impact of this revolution on nursing science and practice as well as the opportunities for nursing science and practice to participate fully in this revolution. Because of the high proportion of the population at risk for complex diseases and because nurses are occupied every day in the prevention, assessment, treatment, and therapeutic intervention of patients with such diseases in practice and research, there is great opportunity for nurses to improve health care through the application (nursing practice) and discovery (nursing research) of genetic knowledge.

Space technology in the discovery and development of mineral and energy resources

NASA Technical Reports Server (NTRS)

Lowman, P. D.

1977-01-01

Space technology, applied to the discovery and extraction of mineral and energy resources, is summarized. Orbital remote sensing for geological purposes has been widely applied through the use of LANDSAT satellites. These techniques also have been of value for protection against environmental hazards and for a better understanding of crustal structure.

Medical data mining: knowledge discovery in a clinical data warehouse.

PubMed Central

Prather, J. C.; Lobach, D. F.; Goodwin, L. K.; Hales, J. W.; Hage, M. L.; Hammond, W. E.

1997-01-01

Clinical databases have accumulated large quantities of information about patients and their medical conditions. Relationships and patterns within this data could provide new medical knowledge. Unfortunately, few methodologies have been developed and applied to discover this hidden knowledge. In this study, the techniques of data mining (also known as Knowledge Discovery in Databases) were used to search for relationships in a large clinical database. Specifically, data accumulated on 3,902 obstetrical patients were evaluated for factors potentially contributing to preterm birth using exploratory factor analysis. Three factors were identified by the investigators for further exploration. This paper describes the processes involved in mining a clinical database including data warehousing, data query and cleaning, and data analysis. PMID:9357597

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

Cooperative knowledge evolution: a construction-integration approach to knowledge discovery in medicine.

PubMed

Schmalhofer, F J; Tschaitschian, B

1998-11-01

In this paper, we perform a cognitive analysis of knowledge discovery processes. As a result of this analysis, the construction-integration theory is proposed as a general framework for developing cooperative knowledge evolution systems. We thus suggest that for the acquisition of new domain knowledge in medicine, one should first construct pluralistic views on a given topic which may contain inconsistencies as well as redundancies. Only thereafter does this knowledge become consolidated into a situation-specific circumscription and the early inconsistencies become eliminated. As a proof for the viability of such knowledge acquisition processes in medicine, we present the IDEAS system, which can be used for the intelligent documentation of adverse events in clinical studies. This system provides a better documentation of the side-effects of medical drugs. Thereby, knowledge evolution occurs by achieving consistent explanations in increasingly larger contexts (i.e., more cases and more pharmaceutical substrates). Finally, it is shown how prototypes, model-based approaches and cooperative knowledge evolution systems can be distinguished as different classes of knowledge-based systems.

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

Discusses knowledge-based decision-support systems that use artificial intelligence approaches. Addresses the issue of how to create an effective case-based reasoning system for complex and evolving domains, focusing on automated methods for system optimization and domain knowledge evolution that can supplement knowledge acquired from domain…

A novel in silico approach to drug discovery via computational intelligence.

PubMed

Hecht, David; Fogel, Gary B

2009-04-01

A computational intelligence drug discovery platform is introduced as an innovative technology designed to accelerate high-throughput drug screening for generalized protein-targeted drug discovery. This technology results in collections of novel small molecule compounds that bind to protein targets as well as details on predicted binding modes and molecular interactions. The approach was tested on dihydrofolate reductase (DHFR) for novel antimalarial drug discovery; however, the methods developed can be applied broadly in early stage drug discovery and development. For this purpose, an initial fragment library was defined, and an automated fragment assembly algorithm was generated. These were combined with a computational intelligence screening tool for prescreening of compounds relative to DHFR inhibition. The entire method was assayed relative to spaces of known DHFR inhibitors and with chemical feasibility in mind, leading to experimental validation in future studies.

The impact of assay technology as applied to safety assessment in reducing compound attrition in drug discovery.

PubMed

Thomas, Craig E; Will, Yvonne

2012-02-01

Attrition in the drug industry due to safety findings remains high and requires a shift in the current safety testing paradigm. Many companies are now positioning safety assessment at each stage of the drug development process, including discovery, where an early perspective on potential safety issues is sought, often at chemical scaffold level, using a variety of emerging technologies. Given the lengthy development time frames of drugs in the pharmaceutical industry, the authors believe that the impact of new technologies on attrition is best measured as a function of the quality and timeliness of candidate compounds entering development. The authors provide an overview of in silico and in vitro models, as well as more complex approaches such as 'omics,' and where they are best positioned within the drug discovery process. It is important to take away that not all technologies should be applied to all projects. Technologies vary widely in their validation state, throughput and cost. A thoughtful combination of validated and emerging technologies is crucial in identifying the most promising candidates to move to proof-of-concept testing in humans. In spite of the challenges inherent in applying new technologies to drug discovery, the successes and recognition that we cannot continue to rely on safety assessment practices used for decades have led to rather dramatic strategy shifts and fostered partnerships across government agencies and industry. We are optimistic that these efforts will ultimately benefit patients by delivering effective and safe medications in a timely fashion.

NASA EOSDIS: Enabling Science by Improving User Knowledge

NASA Technical Reports Server (NTRS)

Lindsay, Francis; Brennan, Jennifer; Blumenfeld, Joshua

2016-01-01

Lessons learned and impacts of applying these newer methods are explained and include several examples from our current efforts such as the interactive, on-line webinars focusing on data discovery and access including tool usage, informal and informative data chats with data experts across our EOSDIS community, data user profile interviews with scientists actively using EOSDIS data in their research, and improved conference and meeting interactions via EOSDIS data interactively used during hyper-wall talks and Worldview application. The suite of internet-based, interactive capabilities and technologies has allowed our project to expand our user community by making the data and applications from numerous Earth science missions more engaging, approachable and meaningful.

From discovery to licensure, the Adjuvant System story.

PubMed

Garçon, Nathalie; Di Pasquale, Alberta

2017-01-02

Adjuvants are substances added to vaccines to improve their immunogenicity. Used for more than 80 years, aluminum, the first adjuvant in human vaccines, proved insufficient to develop vaccines that could protect against new challenging pathogens such as HIV and malaria. New adjuvants and new combinations of adjuvants (Adjuvant Systems) have opened the door to the delivery of improved and new vaccines against re-emerging and difficult pathogens. Adjuvant Systems concept started through serendipity. The access to new developments in technology, microbiology and immunology have been instrumental for the dicephering of what they do and how they do it. This knowledge opens the door to more rational vaccine design with implications for developing new and better vaccines.

Report on the 10th anniversary of international drug discovery science and technology conference, 8 - 10 november 2012, nanjing, china.

PubMed

Everett, Jeremy R

2013-03-01

The 10th Anniversary of International Drug Discovery Science and Technology (IDDST) Conference was held in Nanjing, China from 8 to 10 November 2012. The conference ran in parallel with the 2nd Annual Symposium of Drug Delivery Systems. Over 400 delegates from both conferences came together for the Opening Ceremony and Keynote Addresses but otherwise pursued separate paths in the huge facilities of the Nanjing International Expo Centre. The IDDST was arranged into 19 separate Chapters covering drug discovery biology, target validation, chemistry, rational drug design, pharmacology and toxicology, drug screening technology, 'omics' technologies, analytical, automation and enabling technologies, informatics, stem cells and regenerative medicine, bioprocessing, generics, biosimilars and biologicals and seven disease areas: cancer, CNS, respiratory and inflammation, autoimmune, emerging infectious, bone and orphan diseases. There were also two sessions of a 'Bench to Bedside to Business' Program and a Chinese Scientist programme. In each period of the IDDST conference, up to seven sessions were running in parallel. This Meeting Highlight samples just a fraction of the content of this large meeting. The talks included have as a link, the use of new approaches to drug discovery. Many other excellent talks could have been highlighted and the author has necessarily had to be selective.

A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis.

PubMed

Vafaee, Fatemeh; Diakos, Connie; Kirschner, Michaela B; Reid, Glen; Michael, Michael Z; Horvath, Lisa G; Alinejad-Rokny, Hamid; Cheng, Zhangkai Jason; Kuncic, Zdenka; Clarke, Stephen

2018-01-01

Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications. Here, we have evaluated the role of circulating microRNA as a means of predicting the prognosis of patients with colorectal cancer, which is the second leading cause of cancer-related death worldwide. We have developed a multi-objective optimisation method that effectively integrates a data-driven approach with the knowledge obtained from the microRNA-mediated regulatory network to identify robust plasma microRNA signatures which are reliable in terms of predictive power as well as functional relevance. The proposed multi-objective framework has the capacity to adjust for conflicting biomarker objectives and to incorporate heterogeneous information facilitating systems approaches to biomarker discovery. We have found a prognostic signature of colorectal cancer comprising 11 circulating microRNAs. The identified signature predicts the patients' survival outcome and targets pathways underlying colorectal cancer progression. The altered expression of the identified microRNAs was confirmed in an independent public data set of plasma samples of patients in early stage vs advanced colorectal cancer. Furthermore, the generality of the proposed method was demonstrated across three publicly available miRNA data sets associated with biomarker studies in other diseases.

FY08 Engineering Research and Technology Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minichino, C; McNichols, D

2009-02-24

This report summarizes the core research, development, and technology accomplishments in Lawrence Livermore National Laboratory's Engineering Directorate for FY2008. These efforts exemplify Engineering's more than 50-year history of developing and applying the technologies needed to support the Laboratory's national security missions. A partner in every major program and project at the Laboratory throughout its existence, Engineering has prepared for this role with a skilled workforce and technical resources developed through both internal and external venues. These accomplishments embody Engineering's mission: 'Enable program success today and ensure the Laboratory's vitality tomorrow.' Engineering's mission is carried out through basic research and technologymore » development. Research is the vehicle for creating competencies that are cutting-edge, or require discovery-class groundwork to be fully understood. Our technology efforts are discipline-oriented, preparing research breakthroughs for broader application to a variety of Laboratory needs. The term commonly used for technology-based projects is 'reduction to practice.' As we pursue this two-pronged approach, an enormous range of technological capabilities result. This report combines our work in research and technology into one volume, organized into thematic technical areas: Engineering Modeling and Simulation; Measurement Technologies; Micro/Nano-Devices and Structures; Engineering Systems for Knowledge and Inference; and Energy Manipulation. Our investments in these areas serve not only known programmatic requirements of today and tomorrow, but also anticipate the breakthrough engineering innovations that will be needed in the future.« less

To ontologise or not to ontologise: An information model for a geospatial knowledge infrastructure

NASA Astrophysics Data System (ADS)

Stock, Kristin; Stojanovic, Tim; Reitsma, Femke; Ou, Yang; Bishr, Mohamed; Ortmann, Jens; Robertson, Anne

2012-08-01

A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created. This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge. The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.

NASA's Discovery Program

NASA Astrophysics Data System (ADS)

Kicza, Mary; Bruegge, Richard Vorder

1995-01-01

NASA's Discovery Program represents an new era in planetary exploration. Discovery's primary goal: to maintain U.S. scientific leadership in planetary research by conducting a series of highly focused, cost effective missions to answer critical questions in solar system science. The Program will stimulate the development of innovative management approaches by encouraging new teaming arrangements among industry, universities and the government. The program encourages the prudent use of new technologies to enable/enhance science return and to reduce life cycle cost, and it supports the transfer of these technologies to the private sector for secondary applications. The Near-Earth Asteroid Rendezvous and Mars Pathfinder missions have been selected as the first two Discovery missions. Both will be launched in 1996. Subsequent, competitively selected missions will be conceived and proposed to NASA by teams of scientists and engineers from industry, academia, and government organizations. This paper summarizes the status of Discovery Program planning.

How molecular profiling could revolutionize drug discovery.

PubMed

Stoughton, Roland B; Friend, Stephen H

2005-04-01

Information from genomic, proteomic and metabolomic measurements has already benefited target discovery and validation, assessment of efficacy and toxicity of compounds, identification of disease subgroups and the prediction of responses of individual patients. Greater benefits can be expected from the application of these technologies on a significantly larger scale; by simultaneously collecting diverse measurements from the same subjects or cell cultures; by exploiting the steadily improving quantitative accuracy of the technologies; and by interpreting the emerging data in the context of underlying biological models of increasing sophistication. The benefits of applying molecular profiling to drug discovery and development will include much lower failure rates at all stages of the drug development pipeline, faster progression from discovery through to clinical trials and more successful therapies for patient subgroups. Upheavals in existing organizational structures in the current 'conveyor belt' models of drug discovery might be required to take full advantage of these methods.

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

PubMed

Hassani-Pak, Keywan; Rawlings, Christopher

2017-06-13

Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

Emerging therapeutic targets for treatment of leishmaniasis.

PubMed

Sundar, Shyam; Singh, Bhawana

2018-06-01

Parasitic diseases that pose a threat to human life include leishmaniasis - caused by protozoan parasite Leishmania species. Existing drugs have limitations due to deleterious side effects like teratogenicity, high cost and drug resistance. This calls for the need to have an insight into therapeutic aspects of disease. Areas covered: We have identified different drug targets via. molecular, imuunological, metabolic as well as by system biology approaches. We bring these promising drug targets into light so that they can be explored to their maximum. In an effort to bridge the gaps between existing knowledge and prospects of drug discovery, we have compiled interesting studies on drug targets, thereby paving the way for establishment of better therapeutic aspects. Expert opinion: Advancements in technology shed light on many unexplored pathways. Further probing of well established pathways led to the discovery of new drug targets. This review is a comprehensive report on current and emerging drug targets, with emphasis on several metabolic targets, organellar biochemistry, salvage pathways, epigenetics, kinome and more. Identification of new targets can contribute significantly towards strengthening the pipeline for disease elimination.

Company Profile: Selventa, Inc.

PubMed

Fryburg, David A; Latino, Louis J; Tagliamonte, John; Kenney, Renee D; Song, Diane H; Levine, Arnold J; de Graaf, David

2012-08-01

Selventa, Inc. (MA, USA) is a biomarker discovery company that enables personalized healthcare. Originally founded as Genstruct, Inc., Selventa has undergone significant evolution from a technology-based service provider to an active partner in the development of diagnostic tests, functioning as a molecular dashboard of disease activity using a unique platform. As part of that evolution, approximately 2 years ago the company was rebranded as Selventa to reflect its new identity and mission. The contributions to biomedical research by Selventa are based on in silico, reverse-engineering methods to determine biological causality. That is, given a set of in vitro or in vivo biological observations, which biological mechanisms can explain the measured results? Facilitated by a large and carefully curated knowledge base, these in silico methods generated new insights into the mechanisms driving a disease. As Selventa's methods would enable biomarker discovery and be directly applicable to generating novel diagnostics, the scientists at Selventa have focused on the development of predictive biomarkers of response in autoimmune and oncologic diseases. Selventa is presently building a portfolio of independent, as well as partnered, biomarker projects with the intention to create diagnostic tests that predict response to therapy.

PINT, A Modern Software Package for Pulsar Timing

NASA Astrophysics Data System (ADS)

Luo, Jing; Ransom, Scott M.; Demorest, Paul; Ray, Paul S.; Stovall, Kevin; Jenet, Fredrick; Ellis, Justin; van Haasteren, Rutger; Bachetti, Matteo; NANOGrav PINT developer team

2018-01-01

Pulsar timing, first developed decades ago, has provided an extremely wide range of knowledge about our universe. It has been responsible for many important discoveries, such as the discovery of the first exoplanet and the orbital period decay of double neutron star systems. Currently pulsar timing is the leading technique for detecting low frequency (about 10^-9 Hertz) gravitational waves (GW) using an array of pulsars as the detectors. To achieve this goal, high precision pulsar timing data, at about nanoseconds level, is required. Most high precision pulsar timing data are analyzed using the widely adopted software TEMPO/TEMPO2. But for a robust and believable GW detection, it is important to have independent software that can cross-check the result. In this poster we present the new generation pulsar timing software PINT. This package will provide a robust system to cross check high-precision timing results, completely independent of TEMPO and TEMPO2. In addition, PINT is designed to be a package that is easy to extend and modify, through use of flexible code architecture and a modern programming language, Python, with modern technology and libraries.

“Drivers” of Translational Cancer Epidemiology in the 21st Century: Needs and Opportunities

PubMed Central

Lam, Tram Kim; Spitz, Margaret; Schully, Sheri D.; Khoury, Muin J.

2012-01-01

Cancer epidemiology is at the cusp of a paradigm shift--propelled by an urgent need to accelerate the pace of translating scientific discoveries into healthcare and population health benefits. As part of a strategic planning process for cancer epidemiologic research, the Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is leading a “longitudinal” meeting with members of the research community to engage in an on-going dialogue to help shape and invigorate the field. Here, we review a translational framework influenced by “drivers” that we believe have begun guiding cancer epidemiology towards translation in the past few years and are most likely to drive the field further in the next decade. The drivers include: (1) collaboration and team science; (2) technology; (3) multi-level analyses and interventions; and (4) knowledge integration from basic, clinical and population sciences. Using the global prevention of cervical cancer as an example of a public health endeavor to anchor the conversation, we discuss how these drivers can guide epidemiology from discovery to population health impact, along the translational research continuum. PMID:23322363

Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

PubMed Central

Tahara, Hideaki; Sato, Marimo; Thurin, Magdalena; Wang, Ena; Butterfield, Lisa H; Disis, Mary L; Fox, Bernard A; Lee, Peter P; Khleif, Samir N; Wigginton, Jon M; Ambs, Stefan; Akutsu, Yasunori; Chaussabel, Damien; Doki, Yuichiro; Eremin, Oleg; Fridman, Wolf Hervé; Hirohashi, Yoshihiko; Imai, Kohzoh; Jacobson, James; Jinushi, Masahisa; Kanamoto, Akira; Kashani-Sabet, Mohammed; Kato, Kazunori; Kawakami, Yutaka; Kirkwood, John M; Kleen, Thomas O; Lehmann, Paul V; Liotta, Lance; Lotze, Michael T; Maio, Michele; Malyguine, Anatoli; Masucci, Giuseppe; Matsubara, Hisahiro; Mayrand-Chung, Shawmarie; Nakamura, Kiminori; Nishikawa, Hiroyoshi; Palucka, A Karolina; Petricoin, Emanuel F; Pos, Zoltan; Ribas, Antoni; Rivoltini, Licia; Sato, Noriyuki; Shiku, Hiroshi; Slingluff, Craig L; Streicher, Howard; Stroncek, David F; Takeuchi, Hiroya; Toyota, Minoru; Wada, Hisashi; Wu, Xifeng; Wulfkuhle, Julia; Yaguchi, Tomonori; Zeskind, Benjamin; Zhao, Yingdong; Zocca, Mai-Britt; Marincola, Francesco M

2009-01-01

Supported by the Office of International Affairs, National Cancer Institute (NCI), the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc) and the United States Food and Drug Administration (FDA) to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a) to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b) to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD) of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs) likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers were recognized that might be added to the list of known entities applicable in immunotherapy trials. The need for a systematic approach to biomarker discovery that takes advantage of powerful high-throughput technologies was recognized; it was clear from the current state of the science that immunotherapy is still in a discovery phase and only a few of the current biomarkers warrant extensive validation. It was, finally, clear that, while current technologies have almost limitless potential, inadequate study design, limited standardization and cross-validation among laboratories and suboptimal comparability of data remain major road blocks. The institution of an interactive consortium for high throughput molecular monitoring of clinical trials with voluntary participation might provide cost-effective solutions. PMID:19534815

Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

PubMed

Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

2015-01-01

Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.

Great Originals of Modern Physics

ERIC Educational Resources Information Center

Decker, Fred W.

1972-01-01

European travel can provide an intimate view of the implements and locales of great discoveries in physics for the knowledgeable traveler. The four museums at Cambridge, London, Remscheid-Lennep, and Munich display a full range of discovery apparatus in modern physics as outlined here. (Author/TS)

Dulse on the Distaff Side.

ERIC Educational Resources Information Center

MacKenzie, Marion

1983-01-01

Scientific research leading to the discovery of female plants of the red alga Palmaria plamata (dulse) is described. This discovery has not only advanced knowledge of marine organisms and taxonomic relationships but also has practical implications. The complete life cycle of this organism is included. (JN)

43 CFR 4.1132 - Scope of discovery.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature, custody... persons having knowledge of any discoverable matter. (b) It is not ground for objection that information...

43 CFR 4.1132 - Scope of discovery.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature, custody... persons having knowledge of any discoverable matter. (b) It is not ground for objection that information...

43 CFR 4.1132 - Scope of discovery.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature, custody... persons having knowledge of any discoverable matter. (b) It is not ground for objection that information...

43 CFR 4.1132 - Scope of discovery.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature, custody... persons having knowledge of any discoverable matter. (b) It is not ground for objection that information...

Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

NASA Astrophysics Data System (ADS)

Fox, P.

2012-04-01

The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

The Medawar Lecture 1998 Is science dangerous?

PubMed Central

Wolpert, Lewis

2005-01-01

The idea that science is dangerous is deeply embedded in our culture, particularly in literature, yet science provides the best way of understanding the world. Science is not the same as technology. In contrast to technology, reliable scientific knowledge is value-free and has no moral or ethical value. Scientists are not responsible for the technological applications of science; the very nature of science is that it is not possible to predict what will be discovered or how these discoveries could be applied. The obligation of scientists is to make public both any social implications of their work and its technological applications. A rare case of immoral science was eugenics. The image of Frankenstein has been turned by the media into genetic pornography, but neither cloning nor stem cells or gene therapy raise new ethical issues. There are no areas of research that are so socially sensitive that research into them should be proscribed. We have to rely on the many institutions of a democratic society: parliament, a free and vigorous press, affected groups and the scientists themselves. That is why programmes for the public understanding of science are so important. Alas, we still do not know how best to do this. PMID:16147520

Stem cell technology for drug discovery and development.

PubMed

Hook, Lilian A

2012-04-01

Stem cells have enormous potential to revolutionise the drug discovery process at all stages, from target identification through to toxicology studies. Their ability to generate physiologically relevant cells in limitless supply makes them an attractive alternative to currently used recombinant cell lines or primary cells. However, realisation of the full potential of stem cells is currently hampered by the difficulty in routinely directing stem cell differentiation to reproducibly and cost effectively generate pure populations of specific cell types. In this article we discuss how stem cells have already been used in the drug discovery process and how novel technologies, particularly in relation to stem cell differentiation, can be applied to attain widespread adoption of stem cell technology by the pharmaceutical industry. Copyright © 2011 Elsevier Ltd. All rights reserved.

Scaling Up: Adapting a Phage-Hunting Course to Increase Participation of First-Year Students in Research

PubMed Central

Staub, Nancy L.; Poxleitner, Marianne; Braley, Amanda; Smith-Flores, Helen; Pribbenow, Christine M.; Jaworski, Leslie; Lopatto, David; Anders, Kirk R.

2016-01-01

Authentic research experiences are valuable components of effective undergraduate education. Research experiences during the first years of college are especially critical to increase persistence in science, technology, engineering, and mathematics fields. The Science Education Alliance Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) model provides a high-impact research experience to first-year students but is usually available to a limited number of students, and its implementation is costly in faculty time and laboratory space. To offer a research experience to all students taking introductory biology at Gonzaga University (n = 350/yr), we modified the traditional two-semester SEA-PHAGES course by streamlining the first-semester Phage Discovery lab and integrating the second SEA-PHAGES semester into other courses in the biology curriculum. Because most students in the introductory course are not biology majors, the Phage Discovery semester may be their only encounter with research. To discover whether students benefit from the first semester alone, we assessed the effects of the one-semester Phage Discovery course on students’ understanding of course content. Specifically, students showed improvement in knowledge of bacteriophages, lab math skills, and understanding experimental design and interpretation. They also reported learning gains and benefits comparable with other course-based research experiences. Responses to open-ended questions suggest that students experienced this course as a true undergraduate research experience. PMID:27146160

Collaborative Web-Enabled GeoAnalytics Applied to OECD Regional Data

NASA Astrophysics Data System (ADS)

Jern, Mikael

Recent advances in web-enabled graphics technologies have the potential to make a dramatic impact on developing collaborative geovisual analytics (GeoAnalytics). In this paper, tools are introduced that help establish progress initiatives at international and sub-national levels aimed at measuring and collaborating, through statistical indicators, economic, social and environmental developments and to engage both statisticians and the public in such activities. Given this global dimension of such a task, the “dream” of building a repository of progress indicators, where experts and public users can use GeoAnalytics collaborative tools to compare situations for two or more countries, regions or local communities, could be accomplished. While the benefits of GeoAnalytics tools are many, it remains a challenge to adapt these dynamic visual tools to the Internet. For example, dynamic web-enabled animation that enables statisticians to explore temporal, spatial and multivariate demographics data from multiple perspectives, discover interesting relationships, share their incremental discoveries with colleagues and finally communicate selected relevant knowledge to the public. These discoveries often emerge through the diverse backgrounds and experiences of expert domains and are precious in a creative analytics reasoning process. In this context, we introduce a demonstrator “OECD eXplorer”, a customized tool for interactively analyzing, and collaborating gained insights and discoveries based on a novel story mechanism that capture, re-use and share task-related explorative events.

Using insects for STEM outreach: Development and evaluation of the UA Insect Discovery Program

NASA Astrophysics Data System (ADS)

Beal, Benjamin D.

Science and technology impact most aspects of modern daily life. It is therefore important to create a scientifically literate society. Since the majority of Americans do not take college-level science courses, strong K-12 science education is essential. At the K-5 level, however, many teachers lack the time, resources and background for effective science teaching. Elementary teachers and students may benefit from scientist-led outreach programs created by Cooperative Extension or other institutions. One example is the University of Arizona Insect Discovery Program, which provides short-duration programing that uses insects to support science content learning, teach critical thinking and spark interest in science. We conducted evaluations of the Insect Discovery programming to determine whether the activities offered were accomplishing program goals. Pre-post tests, post program questionnaires for teachers, and novel assessments of children's drawings were used as assessment tools. Assessments were complicated by the short duration of the program interactions with the children as well as their limited literacy. In spite of these difficulties, results of the pre-post tests indicated a significant impact on content knowledge and critical thinking skills. Based on post-program teacher questionnaires, positive impacts on interest in science learning were noted as much as a month after the children participated in the program. New programming and resources developed to widen the potential for impact are also described.

Examining the effects of a DNA fingerprinting workshop on science teachers' professional development and student learning

NASA Astrophysics Data System (ADS)

Sonmez, Duygu

The 21st century has become the age of biology with the completion of the human genome project and other milestone discoveries. Recent progress has redefined what it means to be scientifically literate, which is the ultimate goal in science education. "What students should know?" "What needs to be taught?" These questions lead to reformulation of the science curriculum due to the changing nature of scientific knowledge. Molecular biology is increasingly emphasized in the science curriculum along with applications of the latest developments within our daily lives, such as medicine or legal matters. However, many schools and classrooms exclude the latest advances in molecular genetics from science curriculum and even teach biology as a non-laboratory science. Many science educators wonder what can be done to help every child gain meaningful experiences with molecular genetics. Limited content knowledge among teachers due to the changing nature of scientific knowledge, and the rapid discoveries in technology are known to be a part of the problem for teachers, especially for teachers who have been in the workforce for many years. A major aim of professional development is to help teachers cope with the advances in scientific knowledge and provide paths for teachers to continually improve their knowledge and skills. The expectation is that increased knowledge and skills among teachers will be reflected in student achievement. Professional development is typically offered in a variety of formats, from short-term, one-shot workshop approaches to long term courses. The effectiveness of short-term exposures, though, is in many cases is questionable. One of the issues appears to be the gap between the incidence of teachers' attendance at professional development programs and the incidence of implementation in participants' classrooms. This study focuses on this issue by exploring the relationship between teachers' professional development attendance and their implementation behavior. The goal is to understand what factors affect teachers' decision making to implement the new knowledge and skills in their classrooms. For this purpose, the study focuses on the effects of a DNA fingerprinting workshop, which has been developed and is regularly offered by a large Midwestern university in the United States for secondary science teachers and their students through cooperation between the university and a large Midwestern public school district. The workshop focuses on the biotechnology applications of genetics---specifically, use of DNA fingerprinting technology in different areas of social life---while forensic science is emphasized. Results indicate that the teachers' motivation to attend the DNA Fingerprinting professional development workshop was mainly influenced by two variables: (1) the need to improve content knowledge and skills, and (2) requirements associated with current educational policies. Level of content knowledge was also found to be a factor contributing to teachers' motivation to implement the workshop. Concerns related to student maturity and classroom management were also identified as factors influencing teachers' implementation behavior. Evidence that the DNA Fingerprinting workshop can be successfully implemented by classroom teachers was obtained. The DNA fingerprinting workshop was found to be a successful model for packaging professional development experiences for content intensive areas.

Foreword to "The Secret of Childhood."

ERIC Educational Resources Information Center

Stephenson, Margaret E.

2000-01-01

Discusses the basic discoveries of Montessori's Casa dei Bambini. Considers principles of Montessori's organizing theory: the absorbent mind, the unfolding nature of life, the spiritual embryo, self-construction, acquisition of culture, creativity of life, repetition of exercise, freedom within limits, children's discovery of knowledge, the secret…

The discovery of medicines for rare diseases

PubMed Central

Swinney, David C; Xia, Shuangluo

2015-01-01

There is a pressing need for new medicines (new molecular entities; NMEs) for rare diseases as few of the 6800 rare diseases (according to the NIH) have approved treatments. Drug discovery strategies for the 102 orphan NMEs approved by the US FDA between 1999 and 2012 were analyzed to learn from past success: 46 NMEs were first in class; 51 were followers; and five were imaging agents. First-in-class medicines were discovered with phenotypic assays (15), target-based approaches (12) and biologic strategies (18). Identification of genetic causes in areas with more basic and translational research such as cancer and in-born errors in metabolism contributed to success regardless of discovery strategy. In conclusion, greater knowledge increases the chance of success and empirical solutions can be effective when knowledge is incomplete. PMID:25068983

The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery

PubMed Central

2014-01-01

The Semanticscience Integrated Ontology (SIO) is an ontology to facilitate biomedical knowledge discovery. SIO features a simple upper level comprised of essential types and relations for the rich description of arbitrary (real, hypothesized, virtual, fictional) objects, processes and their attributes. SIO specifies simple design patterns to describe and associate qualities, capabilities, functions, quantities, and informational entities including textual, geometrical, and mathematical entities, and provides specific extensions in the domains of chemistry, biology, biochemistry, and bioinformatics. SIO provides an ontological foundation for the Bio2RDF linked data for the life sciences project and is used for semantic integration and discovery for SADI-based semantic web services. SIO is freely available to all users under a creative commons by attribution license. See website for further information: http://sio.semanticscience.org. PMID:24602174

Bench-to-bedside review: Future novel diagnostics for sepsis - a systems biology approach

PubMed Central

2013-01-01

The early, accurate diagnosis and risk stratification of sepsis remains an important challenge in the critically ill. Since traditional biomarker strategies have not yielded a gold standard marker for sepsis, focus is shifting towards novel strategies that improve assessment capabilities. The combination of technological advancements and information generated through the human genome project positions systems biology at the forefront of biomarker discovery. While previously available, developments in the technologies focusing on DNA, gene expression, gene regulatory mechanisms, protein and metabolite discovery have made these tools more feasible to implement and less costly, and they have taken on an enhanced capacity such that they are ripe for utilization as tools to advance our knowledge and clinical research. Medicine is in a genome-level era that can leverage the assessment of thousands of molecular signals beyond simply measuring selected circulating proteins. Genomics is the study of the entire complement of genetic material of an individual. Epigenetics is the regulation of gene activity by reversible modifications of the DNA. Transcriptomics is the quantification of the relative levels of messenger RNA for a large number of genes in specific cells or tissues to measure differences in the expression levels of different genes, and the utilization of patterns of differential gene expression to characterize different biological states of a tissue. Proteomics is the large-scale study of proteins. Metabolomics is the study of the small molecule profiles that are the terminal downstream products of the genome and consists of the total complement of all low-molecular-weight molecules that cellular processes leave behind. Taken together, these individual fields of study may be linked during a systems biology approach. There remains a valuable opportunity to deploy these technologies further in human research. The techniques described in this paper not only have the potential to increase the spectrum of diagnostic and prognostic biomarkers in sepsis, but they may also enable the discovery of new disease pathways. This may in turn lead us to improved therapeutic targets. The objective of this paper is to provide an overview and basic framework for clinicians and clinical researchers to better understand the 'omics technologies' to enhance further use of these valuable tools. PMID:24093155

Knowledge discovery from structured mammography reports using inductive logic programming.

PubMed

Burnside, Elizabeth S; Davis, Jesse; Costa, Victor Santos; Dutra, Inês de Castro; Kahn, Charles E; Fine, Jason; Page, David

2005-01-01

The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.

A Metadata based Knowledge Discovery Methodology for Seeding Translational Research.

PubMed

Kothari, Cartik R; Payne, Philip R O

2015-01-01

In this paper, we present a semantic, metadata based knowledge discovery methodology for identifying teams of researchers from diverse backgrounds who can collaborate on interdisciplinary research projects: projects in areas that have been identified as high-impact areas at The Ohio State University. This methodology involves the semantic annotation of keywords and the postulation of semantic metrics to improve the efficiency of the path exploration algorithm as well as to rank the results. Results indicate that our methodology can discover groups of experts from diverse areas who can collaborate on translational research projects.

Genetics of Dyslipidemia and Ischemic Heart Disease.

PubMed

Sharma, Kavita; Baliga, Ragavendra R

2017-05-01

Genetic dyslipidemias contribute to the prevalence of ischemic heart disease. The field of genetic dyslipidemias and their influence on atherosclerotic heart disease is rapidly developing and accumulating increasing evidence. The purpose of this review is to describe the current state of knowledge in regard to inherited atherogenic dyslipidemias. The disorders of familial hypercholesterolemia (FH) and elevated lipoprotein(a) will be detailed. Genetic technology has made rapid advancements, leading to new discoveries in inherited atherogenic dyslipidemias, which will be explored in this review, as well as a description of possible future developments. Increasing attention has come upon the genetic disorders of familial hypercholesterolemia and elevated lipoprotein(a). This review includes new knowledge of these disorders including description of these disorders, their method of diagnosis, their prevalence, their genetic underpinnings, and their effect on the development of cardiovascular disease. In addition, it discusses major advances in genetic technology, including the completion of the human genome sequence, next-generation sequencing, and genome-wide association studies. Also discussed are rare variant studies with specific genetic mechanisms involved in inherited dyslipidemias, such as in the proprotein convertase subtilisin/kexin type 9 (PCSK9) enzyme. The field of genetics of dyslipidemia and cardiovascular disease is rapidly growing, which will result in a bright future of novel mechanisms of action and new therapeutics.

Application of logistic analysis to the history of physics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

LePoire, D. J.; Environmental Assessment

2005-05-01

Recently, two analyses have tried to put technological progress in a larger context. One interpretation hypothesizes that technological progress is likely to continue at increasingly higher rates of change. Another interpretation, which includes data from the beginning of the universe to the present, suggests that the universe is approaching a transition point in a logistic development of complexity. This logistic development is similar to the way ideas or products diffuse in a population, i.e., the rate of discovery in a field of knowledge is proportional to the amount discovered and the amount to be discovered. To test a part ofmore » this hypothesis, a leading indicator field (fundamental physics) was identified and the events in the history of this field were analyzed. Twelve subfields were identified and grouped into six stages. Each stage seemed to demonstrate a logistic-like development. By analyzing both the median time of development and the characteristic time of development of these stages, the overall development of this one field was found to suggest logistic development. These data seem to indicate that development in fundamental physics is slowing down, with at least one subfield beyond string physics yet to be developed. The data tend to support the hypothesis that a knowledge field can develop logistically.« less

Who owns what? Private ownership and the public interest in recombinant DNA technology in the 1970s.

PubMed

Yi, Doogab

2011-09-01

This essay analyzes how academic institutions, government agencies, and the nascent biotech industry contested the legal ownership of recombinant DNA technology in the name of the public interest. It reconstructs the way a small but influential group of government officials and university research administrators introduced a new framework for the commercialization of academic research in the context of a national debate over scientific research's contributions to American economic prosperity and public health. They claimed that private ownership of inventions arising from public support would provide a powerful means to liberate biomedical discoveries for public benefit. This articulation of the causal link between private ownership and the public interest, it is argued, justified a new set of expectations about the use of research results arising from government or public support, in which commercialization became a new public obligation for academic researchers. By highlighting the broader economic and legal shifts that prompted the reconfiguration of the ownership of public knowledge in late twentieth-century American capitalism, the essay examines the threads of policy-informed legal ideas that came together to affirm private ownership of biomedical knowledge as germane to the public interest in the coming of age of biotechnology and genetic medicine.

Potential of Cognitive Computing and Cognitive Systems

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2015-01-01

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The cognitive assistants engage, individually or collectively, with humans through a combination of adaptive multimodal interfaces, and advanced visualization and navigation techniques. The realization of future cognitive environments requires the development of a cognitive innovation ecosystem for the engineering workforce. The continuously expanding major components of the ecosystem include integrated knowledge discovery and exploitation facilities (incorporating predictive and prescriptive big data analytics); novel cognitive modeling and visual simulation facilities; cognitive multimodal interfaces; and cognitive mobile and wearable devices. The ecosystem will provide timely, engaging, personalized / collaborative, learning and effective decision making. It will stimulate creativity and innovation, and prepare the participants to work in future cognitive enterprises and develop new cognitive products of increasing complexity. http://www.aee.odu.edu/cognitivecomp

Harnessing Big Data for Systems Pharmacology

PubMed Central

Xie, Lei; Draizen, Eli J.; Bourne, Philip E.

2017-01-01

Systems pharmacology aims to holistically understand mechanisms of drug actions to support drug discovery and clinical practice. Systems pharmacology modeling (SPM) is data driven. It integrates an exponentially growing amount of data at multiple scales (genetic, molecular, cellular, organismal, and environmental). The goal of SPM is to develop mechanistic or predictive multiscale models that are interpretable and actionable. The current explosions in genomics and other omics data, as well as the tremendous advances in big data technologies, have already enabled biologists to generate novel hypotheses and gain new knowledge through computational models of genome-wide, heterogeneous, and dynamic data sets. More work is needed to interpret and predict a drug response phenotype, which is dependent on many known and unknown factors. To gain a comprehensive understanding of drug actions, SPM requires close collaborations between domain experts from diverse fields and integration of heterogeneous models from biophysics, mathematics, statistics, machine learning, and semantic webs. This creates challenges in model management, model integration, model translation, and knowledge integration. In this review, we discuss several emergent issues in SPM and potential solutions using big data technology and analytics. The concurrent development of high-throughput techniques, cloud computing, data science, and the semantic web will likely allow SPM to be findable, accessible, interoperable, reusable, reliable, interpretable, and actionable. PMID:27814027

Harnessing Big Data for Systems Pharmacology.

PubMed

Xie, Lei; Draizen, Eli J; Bourne, Philip E

2017-01-06

Systems pharmacology aims to holistically understand mechanisms of drug actions to support drug discovery and clinical practice. Systems pharmacology modeling (SPM) is data driven. It integrates an exponentially growing amount of data at multiple scales (genetic, molecular, cellular, organismal, and environmental). The goal of SPM is to develop mechanistic or predictive multiscale models that are interpretable and actionable. The current explosions in genomics and other omics data, as well as the tremendous advances in big data technologies, have already enabled biologists to generate novel hypotheses and gain new knowledge through computational models of genome-wide, heterogeneous, and dynamic data sets. More work is needed to interpret and predict a drug response phenotype, which is dependent on many known and unknown factors. To gain a comprehensive understanding of drug actions, SPM requires close collaborations between domain experts from diverse fields and integration of heterogeneous models from biophysics, mathematics, statistics, machine learning, and semantic webs. This creates challenges in model management, model integration, model translation, and knowledge integration. In this review, we discuss several emergent issues in SPM and potential solutions using big data technology and analytics. The concurrent development of high-throughput techniques, cloud computing, data science, and the semantic web will likely allow SPM to be findable, accessible, interoperable, reusable, reliable, interpretable, and actionable.

The virtue of innovation: innovation through the lenses of biological evolution.

PubMed

Kell, Douglas B; Lurie-Luke, Elena

2015-02-06

We rehearse the processes of innovation and discovery in general terms, using as our main metaphor the biological concept of an evolutionary fitness landscape. Incremental and disruptive innovations are seen, respectively, as successful searches carried out locally or more widely. They may also be understood as reflecting evolution by mutation (incremental) versus recombination (disruptive). We also bring a platonic view, focusing on virtue and memory. We use 'virtue' as a measure of efforts, including the knowledge required to come up with disruptive and incremental innovations, and 'memory' as a measure of their lifespan, i.e. how long they are remembered. Fostering innovation, in the evolutionary metaphor, means providing the wherewithal to promote novelty, good objective functions that one is trying to optimize, and means to improve one's knowledge of, and ability to navigate, the landscape one is searching. Recombination necessarily implies multi- or inter-disciplinarity. These principles are generic to all kinds of creativity, novel ideas formation and the development of new products and technologies.

Intelligent Systems: Terrestrial Observation and Prediction Using Remote Sensing Data

NASA Technical Reports Server (NTRS)

Coughlan, Joseph C.

2005-01-01

NASA has made science and technology investments to better utilize its large space-borne remote sensing data holdings of the Earth. With the launch of Terra, NASA created a data-rich environment where the challenge is to fully utilize the data collected from EOS however, despite unprecedented amounts of observed data, there is a need for increasing the frequency, resolution, and diversity of observations. Current terrestrial models that use remote sensing data were constructed in a relatively data and compute limited era and do not take full advantage of on-line learning methods and assimilation techniques that can exploit these data. NASA has invested in visualization, data mining and knowledge discovery methods which have facilitated data exploitation, but these methods are insufficient for improving Earth science models that have extensive background knowledge nor do these methods refine understanding of complex processes. Investing in interdisciplinary teams that include computational scientists can lead to new models and systems for online operation and analysis of data that can autonomously improve in prediction skill over time.

The virtue of innovation: innovation through the lenses of biological evolution

PubMed Central

Kell, Douglas B.; Lurie-Luke, Elena

2015-01-01

We rehearse the processes of innovation and discovery in general terms, using as our main metaphor the biological concept of an evolutionary fitness landscape. Incremental and disruptive innovations are seen, respectively, as successful searches carried out locally or more widely. They may also be understood as reflecting evolution by mutation (incremental) versus recombination (disruptive). We also bring a platonic view, focusing on virtue and memory. We use ‘virtue’ as a measure of efforts, including the knowledge required to come up with disruptive and incremental innovations, and ‘memory’ as a measure of their lifespan, i.e. how long they are remembered. Fostering innovation, in the evolutionary metaphor, means providing the wherewithal to promote novelty, good objective functions that one is trying to optimize, and means to improve one's knowledge of, and ability to navigate, the landscape one is searching. Recombination necessarily implies multi- or inter-disciplinarity. These principles are generic to all kinds of creativity, novel ideas formation and the development of new products and technologies. PMID:25505138

Is the training of biomedical scientists at a crossroads?

PubMed

Halushka, Perry V; Krug, Edward L

2009-04-01

In this commentary, the authors respond to the allegation that the title "scientist" has lost much of its classical meaning because of the highly specialized nature of biomedical graduate training programs that produce "researchers" and "supertechnologists." Scientists, by this definition, have a firm grasp of the historical, philosophical, and biological contexts in which their work exists, whereas their researcher and supertechnologist counterparts are limited by narrowly focused, technologically driven experimentation and data collection with little knowledge or appreciation of the integrated nature of biological systems and the historical basis of discovery. With these definitions in mind, the authors discuss how to ensure that innovative thinking and the ability to integrate molecular knowledge into a higher-order context remain alive and well, complementing today's highly technological environment. In this regard, examples of new emphasis from both scientific societies and funding agencies are provided. However, effective mentoring strategies, practiced on a daily basis, remain the best means for assuring that narrowly focused researchers and supertechnologists do not become the norm of the future. Technological innovation is critical for acquiring new insight into fundamental questions, but using that information for a greater understanding will always favor the prepared intellect. Multidisciplinary teams are emerging as the future of biomedical research. The authors propose a course of action to ensure that trainees are given the necessary opportunities and guidance to help them function effectively in a contemporary teamwork environment with scientific reasoning and logic at its core.

Business Intelligence in Process Control

NASA Astrophysics Data System (ADS)

Kopčeková, Alena; Kopček, Michal; Tanuška, Pavol

2013-12-01

The Business Intelligence technology, which represents a strong tool not only for decision making support, but also has a big potential in other fields of application, is discussed in this paper. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for company management. Article is logically divided into five main parts. In the first part, there is the definition of the technology and the list of main advantages. In the second part, an overview of the system architecture with the brief description of separate building blocks is presented. Also, the hierarchical nature of the system architecture is shown. The technology life cycle consisting of four steps, which are mutually interconnected into a ring, is described in the third part. In the fourth part, analytical methods incorporated in the online analytical processing and data mining used within the business intelligence as well as the related data mining methodologies are summarised. Also, some typical applications of the above-mentioned particular methods are introduced. In the final part, a proposal of the knowledge discovery system for hierarchical process control is outlined. The focus of this paper is to provide a comprehensive view and to familiarize the reader with the Business Intelligence technology and its utilisation.

ASIS 2000: Knowledge Innovations: Celebrating Our Heritage, Designing Our Future. Proceedings of the ASIS Annual Meeting (63rd, Chicago, Illinois, November 12-16, 2000). Volume 37.

ERIC Educational Resources Information Center

Kraft, Donald H., Ed.

The 2000 ASIS (American Society for Information Science) conference explored knowledge innovation. The tracks in the conference program included knowledge discovery, capture, and creation; classification and representation; information retrieval; knowledge dissemination; and social, behavioral, ethical, and legal aspects. This proceedings is…

Evaluating the Science of Discovery in Complex Health Systems

ERIC Educational Resources Information Center

Norman, Cameron D.; Best, Allan; Mortimer, Sharon; Huerta, Timothy; Buchan, Alison

2011-01-01

Complex health problems such as chronic disease or pandemics require knowledge that transcends disciplinary boundaries to generate solutions. Such transdisciplinary discovery requires researchers to work and collaborate across boundaries, combining elements of basic and applied science. At the same time, calls for more interdisciplinary health…

29 CFR 18.14 - Scope of discovery.

Code of Federal Regulations, 2014 CFR

2014-07-01

... administrative law judge in accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the... things and the identity and location of persons having knowledge of any discoverable matter. (b) It is...

49 CFR 386.38 - Scope of discovery.

Code of Federal Regulations, 2011 CFR

2011-10-01

... accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature... location of persons having knowledge of any discoverable matter. (b) It is not ground for objection that...

49 CFR 386.38 - Scope of discovery.

Code of Federal Regulations, 2012 CFR

2012-10-01

... accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature... location of persons having knowledge of any discoverable matter. (b) It is not ground for objection that...

29 CFR 18.14 - Scope of discovery.

Code of Federal Regulations, 2012 CFR

2012-07-01

... administrative law judge in accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the... things and the identity and location of persons having knowledge of any discoverable matter. (b) It is...

49 CFR 386.38 - Scope of discovery.

Code of Federal Regulations, 2013 CFR

2013-10-01

... accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature... location of persons having knowledge of any discoverable matter. (b) It is not ground for objection that...

29 CFR 18.14 - Scope of discovery.

Code of Federal Regulations, 2011 CFR

2011-07-01

... administrative law judge in accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the... things and the identity and location of persons having knowledge of any discoverable matter. (b) It is...

29 CFR 18.14 - Scope of discovery.

Code of Federal Regulations, 2013 CFR

2013-07-01

... administrative law judge in accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the... things and the identity and location of persons having knowledge of any discoverable matter. (b) It is...

49 CFR 386.38 - Scope of discovery.

Code of Federal Regulations, 2014 CFR

2014-10-01

... accordance with these rules, the parties may obtain discovery regarding any matter, not privileged, which is relevant to the subject matter involved in the proceeding, including the existence, description, nature... location of persons having knowledge of any discoverable matter. (b) It is not ground for objection that...

The future of drug discovery: enabling technologies for enhancing lead characterization and profiling therapeutic potential.

PubMed

Janero, David R

2014-08-01

Technology often serves as a handmaiden and catalyst of invention. The discovery of safe, effective medications depends critically upon experimental approaches capable of providing high-impact information on the biological effects of drug candidates early in the discovery pipeline. This information can enable reliable lead identification, pharmacological compound differentiation and successful translation of research output into clinically useful therapeutics. The shallow preclinical profiling of candidate compounds promulgates a minimalistic understanding of their biological effects and undermines the level of value creation necessary for finding quality leads worth moving forward within the development pipeline with efficiency and prognostic reliability sufficient to help remediate the current pharma-industry productivity drought. Three specific technologies discussed herein, in addition to experimental areas intimately associated with contemporary drug discovery, appear to hold particular promise for strengthening the preclinical valuation of drug candidates by deepening lead characterization. These are: i) hydrogen-deuterium exchange mass spectrometry for characterizing structural and ligand-interaction dynamics of disease-relevant proteins; ii) activity-based chemoproteomics for profiling the functional diversity of mammalian proteomes; and iii) nuclease-mediated precision gene editing for developing more translatable cellular and in vivo models of human diseases. When applied in an informed manner congruent with the clinical understanding of disease processes, technologies such as these that span levels of biological organization can serve as valuable enablers of drug discovery and potentially contribute to reducing the current, unacceptably high rates of compound clinical failure.

Reuniting Virtue and Knowledge

ERIC Educational Resources Information Center

Culham, Tom

2015-01-01

Einstein held that intuition is more important than rational inquiry as a source of discovery. Further, he explicitly and implicitly linked the heart, the sacred, devotion and intuitive knowledge. The raison d'être of universities is the advance of knowledge; however, they have primarily focused on developing student's skills in working with…

Three-Dimensional Cell Cultures in Drug Discovery and Development

PubMed Central

Fang, Ye; Eglen, Richard M.

2017-01-01

The past decades have witnessed significant efforts toward the development of three-dimensional (3D) cell cultures as systems that better mimic in vivo physiology. Today, 3D cell cultures are emerging, not only as a new tool in early drug discovery but also as potential therapeutics to treat disease. In this review, we assess leading 3D cell culture technologies and their impact on drug discovery, including spheroids, organoids, scaffolds, hydrogels, organs-on-chips, and 3D bioprinting. We also discuss the implementation of these technologies in compound identification, screening, and development, ranging from disease modeling to assessment of efficacy and safety profiles. PMID:28520521

Fifty years of herbicide research: comparing the discovery of trifluralin and halauxifen-methyl.

PubMed

Epp, Jeffrey B; Schmitzer, Paul R; Crouse, Gary D

2018-01-01

Fifty years separate the commercialization of the herbicides trifluralin and halauxifen-methyl. Despite the vast degree of technological change that occurred over that time frame, some aspects of their discovery stories are remarkably similar. For example, both herbicides were prepared very early in the iterative discovery process and both were developed from known lead compound structures by hypothesis-driven research efforts without the use of in vitro assays or computer-aided molecular design. However, there are aspects of the halauxifen-methyl and trifluralin discovery stories that are substantially different. For example, the chemical technology required for the cost-effective production of halauxifen-methyl simply did not exist just two decades prior to its commercial launch. By contrast, the chemical technology required for the cost-effective production of trifluralin was reported in the chemical literature more than two decades prior to its commercial launch. In addition, changes in regulatory environment since the early 1960s ensured that their respective discovery to commercial launch stories would also differ in substantial ways. Ultimately, the time and cost required to develop and register halauxifen-methyl demanded a global initial business case while the lower registration hurdles that trifluralin cleared enabled a narrow initial business case mainly focused on the USA. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Integrative Systems Biology for Data Driven Knowledge Discovery

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2015-01-01

Integrative systems biology is an approach that brings together diverse high throughput experiments and databases to gain new insights into biological processes or systems at molecular through physiological levels. These approaches rely on diverse high-throughput experimental techniques that generate heterogeneous data by assaying varying aspects of complex biological processes. Computational approaches are necessary to provide an integrative view of these experimental results and enable data-driven knowledge discovery. Hypotheses generated from these approaches can direct definitive molecular experiments in a cost effective manner. Using integrative systems biology approaches, we can leverage existing biological knowledge and large-scale data to improve our understanding of yet unknown components of a system of interest and how its malfunction leads to disease. PMID:21044756

Automated Knowledge Discovery from Simulators

NASA Technical Reports Server (NTRS)

Burl, Michael C.; DeCoste, D.; Enke, B. L.; Mazzoni, D.; Merline, W. J.; Scharenbroich, L.

2006-01-01

In this paper, we explore one aspect of knowledge discovery from simulators, the landscape characterization problem, where the aim is to identify regions in the input/ parameter/model space that lead to a particular output behavior. Large-scale numerical simulators are in widespread use by scientists and engineers across a range of government agencies, academia, and industry; in many cases, simulators provide the only means to examine processes that are infeasible or impossible to study otherwise. However, the cost of simulation studies can be quite high, both in terms of the time and computational resources required to conduct the trials and the manpower needed to sift through the resulting output. Thus, there is strong motivation to develop automated methods that enable more efficient knowledge extraction.

18 CFR 385.402 - Scope of discovery (Rule 402).

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Scope of discovery (Rule 402). 385.402 Section 385.402 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... persons having any knowledge of any discoverable matter. It is not ground for objection that the...

Doors to Discovery[TM]. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2013

2013-01-01

"Doors to Discovery"]TM] is a preschool literacy curriculum that uses eight thematic units of activities to help children build fundamental early literacy skills in oral language, phonological awareness, concepts of print, alphabet knowledge, writing, and comprehension. The eight thematic units cover topics such as nature, friendship,…

78 FR 12933 - Proceedings Before the Commodity Futures Trading Commission

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-26

... proceedings. These new amendments also provide that Judgment Officers may conduct sua sponte discovery in... discovery; (4) sound risk management practices; and (5) other public interest considerations. The amendments... representative capacity, it was done with full power and authority to do so; (C) To the best of his knowledge...

76 FR 64803 - Rules of Adjudication and Enforcement

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-19

...) is also amended to clarify the limits on discovery when the Commission orders the ALJ to consider the... that the complainant identify, to the best of its knowledge, the ``like or directly competitive... the taking of discovery by the parties shall be at the discretion of the presiding ALJ. The ITCTLA...

78 FR 63253 - Davidson Kempner Capital Management LLC; Notice of Application

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-23

... employees of the Adviser other than the Contributor have any knowledge of the Contribution prior to its discovery by the Adviser on November 2, 2011. The Contribution was discovered by the Adviser's compliance... names of employees. After discovery of the Contribution, the Adviser and Contributor obtained the...

G-protein-coupled receptors: new approaches to maximise the impact of GPCRS in drug discovery.

PubMed

Davey, John

2004-04-01

IBC's Drug Discovery Technology Series is a group of conferences highlighting technological advances and applications in niche areas of the drug discovery pipeline. This 2-day meeting focused on G-protein-coupled receptors (GPCRs), probably the most important and certainly the most valuable class of targets for drug discovery. The meeting was chaired by J Beesley (Vice President, European Business Development for LifeSpan Biosciences, Seattle, USA) and included 17 presentations on various aspects of GPCR activity, drug screens and therapeutic analyses. Keynote Addresses covered two of the emerging areas in GPCR regulation; receptor dimerisation (G Milligan, Professor of Molecular Pharmacology and Biochemistry, University of Glasgow, UK) and proteins that interact with GPCRs (J Bockaert, Laboratory of Functional Genomics, CNRS Montpellier, France). A third Keynote Address from W Thomsen (Director of GPCR Drug Screening, Arena Pharmaceuticals, USA) discussed Arena's general approach to drug discovery and illustrated this with reference to the development of an agonist with potential efficacy in Type II diabetes.

Enamel paint techniques in archaeology and their identification using XRF and micro-XRF

NASA Astrophysics Data System (ADS)

Hložek, M.; Trojek, T.; Komoróczy, B.; Prokeš, R.

2017-08-01

This investigation focuses in detail on the analysis of discoveries in South Moravia - important sites from the Roman period in Pasohlávky and Mušov. Using X-ray fluorescence analysis and micro-analysis we help identify the techniques of enamel paint and give a thorough chemical analysis in details which would not be possible to determine by means of macroscopic examination. We thus address the influence of elemental composition on the final colour of the enamel paint and describe the less known technique of combining enamel with millefiori. The material analyses of the metal artefacts decorated with enamel paint significantly contribute to our knowledge of the technology being used during the Roman period.

Helping science to succeed: improving processes in R&D.

PubMed

Sewing, Andreas; Winchester, Toby; Carnell, Pauline; Hampton, David; Keighley, Wilma

2008-03-01

Bringing drugs to the market remains a costly and, until now, often unpredictable challenge. Although understanding the underlying science is key to further progress, our imperfect knowledge of disease and complex biological systems leaves excellence in execution as the most tangible lever to sustain our serendipitous approach to drug discovery. The problems encountered in pharmaceutical R&D are not unique, but to learn from other industries it is important to recognise similarity, rather than differences, and to advance industrialisation of R&D beyond technology and automation. Tools like Lean and Six Sigma, already applied to increase business excellence across diverse organisations, can equally be introduced to pharmaceutical R&D and offer the potential to transform operations without large-scale investment.

Teaching Technology Applied in the Main Stream: The Supermarket Discovery Center

ERIC Educational Resources Information Center

Filep, Robert T.; Gillette, Pearl

1969-01-01

Describes the approach and results of the Supermarket Discovery Center Demonstration Project, a program attempting to provide pre-school children with meaningful learning experiences while their parents are shopping. (LS)

48 CFR 970.5227-11 - Patent rights-management and operating contracts, for-profit contractor, non-technology transfer.

Code of Federal Regulations, 2011 CFR

2011-10-01

... patent waiver regulations at 10 CFR part 784. (3) Invention means any invention or discovery which is or... Contracting Officer or authorized representative deems reasonably pertinent to the discovery or identification... Energy Act of 1954, as amended, may be asserted with respect to any invention or discovery made or...

48 CFR 970.5227-11 - Patent rights-management and operating contracts, for-profit contractor, non-technology transfer.

Code of Federal Regulations, 2012 CFR

2012-10-01

... patent waiver regulations at 10 CFR part 784. (3) Invention means any invention or discovery which is or... Contracting Officer or authorized representative deems reasonably pertinent to the discovery or identification... Energy Act of 1954, as amended, may be asserted with respect to any invention or discovery made or...

48 CFR 970.5227-11 - Patent rights-management and operating contracts, for-profit contractor, non-technology transfer.

Code of Federal Regulations, 2014 CFR

2014-10-01

... patent waiver regulations at 10 CFR part 784. (3) Invention means any invention or discovery which is or... Contracting Officer or authorized representative deems reasonably pertinent to the discovery or identification... Energy Act of 1954, as amended, may be asserted with respect to any invention or discovery made or...

48 CFR 970.5227-11 - Patent rights-management and operating contracts, for-profit contractor, non-technology transfer.

Code of Federal Regulations, 2013 CFR

2013-10-01

... patent waiver regulations at 10 CFR part 784. (3) Invention means any invention or discovery which is or... Contracting Officer or authorized representative deems reasonably pertinent to the discovery or identification... Energy Act of 1954, as amended, may be asserted with respect to any invention or discovery made or...

Teaching Slope of a Line Using the Graphing Calculator as a Tool for Discovery Learning

ERIC Educational Resources Information Center

Nichols, Fiona Costello

2012-01-01

Discovery learning is one of the instructional strategies sometimes used to teach Algebra I. However, little research is available that includes investigation of the effects of incorporating the graphing calculator technology with discovery learning. This study was initiated to investigate two instructional approaches for teaching slope of a line…

Transforming Epidemiology for 21st Century Medicine and Public Health

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khoury, Muin J; Lam, Tram Kim; Ioannidis, John

2013-01-01

n 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving toward more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and acceleratemore » translation; (iii) expanding cohort studies to collect exposure, clinical, and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating big data science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy, and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology, in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits.« less

Transforming Epidemiology for 21st Century Medicine and Public Health

PubMed Central

Khoury, Muin J.; Lam, Tram Kim; Ioannidis, John P.A.; Hartge, Patricia; Spitz, Margaret R.; Buring, Julie E.; Chanock, Stephen J.; Croyle, Robert T.; Goddard, Katrina A.; Ginsburg, Geoffrey S.; Herceg, Zdenko; Hiatt, Robert A.; Hoover, Robert N.; Hunter, David J.; Kramer, Barnet S.; Lauer, Michael S.; Meyerhardt, Jeffrey A.; Olopade, Olufunmilayo I.; Palmer, Julie R.; Sellers, Thomas A.; Seminara, Daniela; Ransohoff, David F.; Rebbeck, Timothy R.; Tourassi, Georgia; Winn, Deborah M.; Zauber, Ann; Schully, Sheri D.

2013-01-01

In 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving towards more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and accelerate translation; (iii) expanding cohort studies to collect exposure, clinical and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating “big data” science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits. PMID:23462917

Cosmology Without Finality

NASA Astrophysics Data System (ADS)

Mahootian, F.

2009-12-01

The rapid convergence of advancing sensor technology, computational power, and knowledge discovery techniques over the past decade has brought unprecedented volumes of astronomical data together with unprecedented capabilities of data assimilation and analysis. A key result is that a new, data-driven "observational-inductive'' framework for scientific inquiry is taking shape and proving viable. The anticipated rise in data flow and processing power will have profound effects, e.g., confirmations and disconfirmations of existing theoretical claims both for and against the big bang model. But beyond enabling new discoveries can new data-driven frameworks of scientific inquiry reshape the epistemic ideals of science? The history of physics offers a comparison. The Bohr-Einstein debate over the "completeness'' of quantum mechanics centered on a question of ideals: what counts as science? We briefly examine lessons from that episode and pose questions about their applicability to cosmology. If the history of 20th century physics is any indication, the abandonment of absolutes (e.g., space, time, simultaneity, continuity, determinacy) can produce fundamental changes in understanding. The classical ideal of science, operative in both physics and cosmology, descends from the European Enlightenment. This ideal has for over 200 years guided science to seek the ultimate order of nature, to pursue the absolute theory, the "theory of everything.'' But now that we have new models of scientific inquiry powered by new technologies and driven more by data than by theory, it is time, finally, to relinquish dreams of a "final'' theory.

Bridging the Gap in Neurotherapeutic Discovery and Development: The Role of the National Institute of Neurological Disorders and Stroke in Translational Neuroscience.

PubMed

Mott, Meghan; Koroshetz, Walter

2015-07-01

The mission of the National Institute of Neurological Disorders and Stroke (NINDS) is to seek fundamental knowledge about the brain and nervous system and to use that knowledge to reduce the burden of neurological disease. NINDS supports early- and late-stage therapy development funding programs to accelerate preclinical discovery and the development of new therapeutic interventions for neurological disorders. The NINDS Office of Translational Research facilitates and funds the movement of discoveries from the laboratory to patients. Its grantees include academics, often with partnerships with the private sector, as well as small businesses, which, by Congressional mandate, receive > 3% of the NINDS budget for small business innovation research. This article provides an overview of NINDS-funded therapy development programs offered by the NINDS Office of Translational Research.

Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases

PubMed Central

Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand

2010-01-01

The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs. PMID:20885778

Interdisciplinary Laboratory Course Facilitating Knowledge Integration, Mutualistic Teaming, and Original Discovery.

PubMed

Full, Robert J; Dudley, Robert; Koehl, M A R; Libby, Thomas; Schwab, Cheryl

2015-11-01

Experiencing the thrill of an original scientific discovery can be transformative to students unsure about becoming a scientist, yet few courses offer authentic research experiences. Increasingly, cutting-edge discoveries require an interdisciplinary approach not offered in current departmental-based courses. Here, we describe a one-semester, learning laboratory course on organismal biomechanics offered at our large research university that enables interdisciplinary teams of students from biology and engineering to grow intellectually, collaborate effectively, and make original discoveries. To attain this goal, we avoid traditional "cookbook" laboratories by training 20 students to use a dozen research stations. Teams of five students rotate to a new station each week where a professor, graduate student, and/or team member assists in the use of equipment, guides students through stages of critical thinking, encourages interdisciplinary collaboration, and moves them toward authentic discovery. Weekly discussion sections that involve the entire class offer exchange of discipline-specific knowledge, advice on experimental design, methods of collecting and analyzing data, a statistics primer, and best practices for writing and presenting scientific papers. The building of skills in concert with weekly guided inquiry facilitates original discovery via a final research project that can be presented at a national meeting or published in a scientific journal. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Maya medicine in the biological gaze: bioprospecting research as herbal fetishism.

PubMed

Nigh, Ronald

2002-06-01

The relationship of human societies to territory and natural resources is being drastically altered by a series of global agreements concerning trade, intellectual property, and the conservation and use of genetic resources. Through a characteristic style of collective appropriation of their tropical ecosystems, Maya societies have created local institutions for governing access to their common resources. However, new mechanisms of global governance require access to Maya biodiversity for world commercial interests. The Chiapas Highland Maya already face this prospect in the International Cooperative Biodiversity Group drug discovery project, which proposes to use Maya medical knowledge to screen plants for potential pharmaceuticals. The ethnobiological focus of the project emphasizes the naturalistic aspects of Maya medicine, primarily the use of herbal remedies. This biological gaze decontextualizes the situated knowledge of Maya healers, ignoring the cultural context in which they create and apply that knowledge. The search for raw materials for the production of universal medical technology results in symbolic violence to the cultural logic of Maya peoples. Only the full recognition of Maya peoples' collective rights to territory and respect for their local common-resource institutions will provide ultimate protection for their cultural and natural patrimony.

Nephrology, a newly rich speciality, is looking for an illustrious ancestry: what about a famous grandfather?

PubMed

Diamandopoulos, A A; Goudas, P C

2000-01-01

Nephrology is a newborn speciality compared to the other medical specialities. However, the study of the urinary tract's physiology and pathology had begun simultaneously with the birth of medicine. The scientific revolution of the renaissance and enlightenment eras caused an intense contestation of earlier theories and methods as if all knowledge had evolved suddenly from parthenogenesis after the dark (?) medieval years and human intellect suddenly exploded to huge intelligence quotients after the 15th century while before that humans were mentally deprived. Indeed most of the scientific knowledge did evolve impressively during renaissance and enlightenment years but not through parthenogenesis. Some observations, discoveries and inventions of this era were actually reobservations, rediscoveries and reinventions. Such an example is that of the experiments of Sanctorius Santorii of the 16th century AD and of Erasistratus of the 3rd century BC. Sanctorius and Erasistratus carried out an experiment with the same basic principles, similar methodology and proportional results with an almost 2000 years lag phase. With our paper we wish to give credit to earlier researchers of physiological and medical knowledge who, despite the lack of technological support, often concluded in extremely accurate observations. Copyright 2000 S. Karger AG, Basel

Asymmetric threat data mining and knowledge discovery

NASA Astrophysics Data System (ADS)

Gilmore, John F.; Pagels, Michael A.; Palk, Justin

2001-03-01

Asymmetric threats differ from the conventional force-on- force military encounters that the Defense Department has historically been trained to engage. Terrorism by its nature is now an operational activity that is neither easily detected or countered as its very existence depends on small covert attacks exploiting the element of surprise. But terrorism does have defined forms, motivations, tactics and organizational structure. Exploiting a terrorism taxonomy provides the opportunity to discover and assess knowledge of terrorist operations. This paper describes the Asymmetric Threat Terrorist Assessment, Countering, and Knowledge (ATTACK) system. ATTACK has been developed to (a) data mine open source intelligence (OSINT) information from web-based newspaper sources, video news web casts, and actual terrorist web sites, (b) evaluate this information against a terrorism taxonomy, (c) exploit country/region specific social, economic, political, and religious knowledge, and (d) discover and predict potential terrorist activities and association links. Details of the asymmetric threat structure and the ATTACK system architecture are presented with results of an actual terrorist data mining and knowledge discovery test case shown.

Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning.

PubMed

Hoehndorf, Robert; Dumontier, Michel; Oellrich, Anika; Rebholz-Schuhmann, Dietrich; Schofield, Paul N; Gkoutos, Georgios V

2011-01-01

Researchers design ontologies as a means to accurately annotate and integrate experimental data across heterogeneous and disparate data- and knowledge bases. Formal ontologies make the semantics of terms and relations explicit such that automated reasoning can be used to verify the consistency of knowledge. However, many biomedical ontologies do not sufficiently formalize the semantics of their relations and are therefore limited with respect to automated reasoning for large scale data integration and knowledge discovery. We describe a method to improve automated reasoning over biomedical ontologies and identify several thousand contradictory class definitions. Our approach aligns terms in biomedical ontologies with foundational classes in a top-level ontology and formalizes composite relations as class expressions. We describe the semi-automated repair of contradictions and demonstrate expressive queries over interoperable ontologies. Our work forms an important cornerstone for data integration, automatic inference and knowledge discovery based on formal representations of knowledge. Our results and analysis software are available at http://bioonto.de/pmwiki.php/Main/ReasonableOntologies.

Is there a best strategy for drug discovery?--SMR Meeting. 13 March 2003, London, UK.

PubMed

Lunec, Anna

2003-05-01

This gathering of members from academia and industry allowed the sharing of ideas and techniques or the acceleration of drug discovery, and it was clear that there is a need for a more streamlined approach to discovery and development. Clearly, new technologies will aid in the discovery process, but the abilities of the human brain to analyze and interpret data should not be overlooked, as many discoveries have been made by chance or as the result of a hunch, and it would be a shame if the advent of artificial intelligence quashed that inquisitive aspect of drug discovery.

Conceptual dissonance: evaluating the efficacy of natural language processing techniques for validating translational knowledge constructs.

PubMed

Payne, Philip R O; Kwok, Alan; Dhaval, Rakesh; Borlawsky, Tara B

2009-03-01

The conduct of large-scale translational studies presents significant challenges related to the storage, management and analysis of integrative data sets. Ideally, the application of methodologies such as conceptual knowledge discovery in databases (CKDD) provides a means for moving beyond intuitive hypothesis discovery and testing in such data sets, and towards the high-throughput generation and evaluation of knowledge-anchored relationships between complex bio-molecular and phenotypic variables. However, the induction of such high-throughput hypotheses is non-trivial, and requires correspondingly high-throughput validation methodologies. In this manuscript, we describe an evaluation of the efficacy of a natural language processing-based approach to validating such hypotheses. As part of this evaluation, we will examine a phenomenon that we have labeled as "Conceptual Dissonance" in which conceptual knowledge derived from two or more sources of comparable scope and granularity cannot be readily integrated or compared using conventional methods and automated tools.

Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, Larry W.; Lee, Sangkeun

2016-01-01

In this era of data-driven decisions and discovery where Big Data is producing Bigger Data, data scientists at the Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g., Urika XA and Urika GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with Big Data (i.e., data stored in databases as well as unstructured data in documents). ORiGAMI is a next-generation knowledge-discovery framework that is: (a) knowledge nurturing (i.e., evolves seamlessly with newer knowledge and data), (b) smart and curious (i.e. using information-foraging and reasoning algorithms to digest content) and (c) synergistic (i.e., interfaces computers with whatmore » they do best to help subject-matter-experts do their best. ORiGAMI has been demonstrated using the National Library of Medicine's SEMANTIC MEDLINE (archive of medical knowledge since 1994).« less

gDNA enrichment by a transposase-based technology for NGS analysis of the whole sequence of BRCA1, BRCA2, and 9 genes involved in DNA damage repair.

PubMed

Chevrier, Sandy; Boidot, Romain

2014-10-06

The widespread use of Next Generation Sequencing has opened up new avenues for cancer research and diagnosis. NGS will bring huge amounts of new data on cancer, and especially cancer genetics. Current knowledge and future discoveries will make it necessary to study a huge number of genes that could be involved in a genetic predisposition to cancer. In this regard, we developed a Nextera design to study 11 complete genes involved in DNA damage repair. This protocol was developed to safely study 11 genes (ATM, BARD1, BRCA1, BRCA2, BRIP1, CHEK2, PALB2, RAD50, RAD51C, RAD80, and TP53) from promoter to 3'-UTR in 24 patients simultaneously. This protocol, based on transposase technology and gDNA enrichment, gives a great advantage in terms of time for the genetic diagnosis thanks to sample multiplexing. This protocol can be safely used with blood gDNA.

Projections for insulin treatment for diabetics.

PubMed

Cao, Ying; Lam, Laura

2002-06-01

The evolution of insulin treatment of diabetes has dramatically changed the natural course of this disease. Modern recombinant DNA technology has brought about many new insulin analogues with improved pharmacokinetics, resulting in better glycemic control. In addition, improved insulin delivery systems, such as insulin pumps and pens, have been introduced to provide convenience and to enhance patient compliance. Efforts are currently being devoted to developing noninvasive insulin formulations, such as oral and pulmonary insulin. A number of products are at different stages of clinical trials. Meanwhile, the quest for a permanent cure for diabetes continues. The frontier of diabetes research has gone through a period of substantial expansion, with the emergence of new areas that include gene therapy, islet cell transplantation and diabetic vaccine. Technological breakthroughs, such as recombinant DNA, nanotechnology, microarray-aided genomics and proteomics, will provide more profound insights into the pathogenesis, and the immunological and biological basis of diabetes. Our growing knowledge in these areas will ultimately contribute to the discovery of preventive methods against or a cure for this disease.

Interactive Visualization of Large-Scale Hydrological Data using Emerging Technologies in Web Systems and Parallel Programming

NASA Astrophysics Data System (ADS)

Demir, I.; Krajewski, W. F.

2013-12-01

As geoscientists are confronted with increasingly massive datasets from environmental observations to simulations, one of the biggest challenges is having the right tools to gain scientific insight from the data and communicate the understanding to stakeholders. Recent developments in web technologies make it easy to manage, visualize and share large data sets with general public. Novel visualization techniques and dynamic user interfaces allow users to interact with data, and modify the parameters to create custom views of the data to gain insight from simulations and environmental observations. This requires developing new data models and intelligent knowledge discovery techniques to explore and extract information from complex computational simulations or large data repositories. Scientific visualization will be an increasingly important component to build comprehensive environmental information platforms. This presentation provides an overview of the trends and challenges in the field of scientific visualization, and demonstrates information visualization and communication tools developed within the light of these challenges.

Microscopic origins of the large piezoelectricity of leadfree (Ba,Ca)(Zr,Ti)O3

NASA Astrophysics Data System (ADS)

Nahas, Yousra; Akbarzadeh, Alireza; Prokhorenko, Sergei; Prosandeev, Sergey; Walter, Raymond; Kornev, Igor; Íñiguez, Jorge; Bellaiche, L.

2017-06-01

In light of directives around the world to eliminate toxic materials in various technologies, finding lead-free materials with high piezoelectric responses constitutes an important current scientific goal. As such, the recent discovery of a large electromechanical conversion near room temperature in (1-x)Ba(Zr0.2Ti0.8)O3-x(Ba0.7Ca0.3)TiO3 compounds has directed attention to understanding its origin. Here, we report the development of a large-scale atomistic scheme providing a microscopic insight into this technologically promising material. We find that its high piezoelectricity originates from the existence of large fluctuations of polarization in the orthorhombic state arising from the combination of a flat free-energy landscape, a fragmented local structure, and the narrow temperature window around room temperature at which this orthorhombic phase is the equilibrium state. In addition to deepening the current knowledge on piezoelectricity, these findings have the potential to guide the design of other lead-free materials with large electromechanical responses.

Geoinformatics 2008 - Data to Knowledge

USGS Publications Warehouse

Brady, Shailaja R.; Sinha, A. Krishna; Gundersen, Linda C.

2008-01-01

Geoinformatics is the term used to describe a variety of efforts to promote collaboration between the computer sciences and the geosciences to solve complex scientific questions. It refers to the distributed, integrated digital information system and working environment that provides innovative means for the study of the Earth systems, as well as other planets, through use of advanced information technologies. Geoinformatics activities range from major research and development efforts creating new technologies to provide high-quality, sustained production-level services for data discovery, integration and analysis, to small, discipline-specific efforts that develop earth science data collections and data analysis tools serving the needs of individual communities. The ultimate vision of Geoinformatics is a highly interconnected data system populated with high quality, freely available data, as well as, a robust set of software for analysis, visualization, and modeling. This volume is a collection of extended abstracts for oral papers presented at the Geoinformatics 2008 conference, June 11 and 13, 2008, in Potsdam, Germany.

From embryonic stem cells to functioning germ cells: science, clinical and ethical perspectives.

PubMed

Kiatpongsan, Sorapop

2007-10-01

Embryonic stem cells have been well recognized as cells having a versatile potential to differentiate into all types of cells in the body including germ cells. There are many research studies focusing on the differentiation processes and protocols to derive various types of somatic cells from embryonic stem cells. However, germ cells have unique differentiation process and developmental pathway compared with somatic cells. Consequently, they will require different differentiation protocols and special culture techniques. More understanding and established in vitro systems for gametogenesis will greatly contribute to further progression of knowledge and technology in germ cell biology, reproductive biology and reproductive medicine. Moreover if oocytes can be efficiently produced in vitro, this will play an important role on progression in nuclear transfer and nuclear reprogramming technology. The present article will provide concise review on past important discoveries, current ongoing studies and future views of this challenging research area. An ethical perspective has also been proposed to give comprehensive summary and viewpoint for future clinical application.

License Agreements | NCI Technology Transfer Center | TTC

Cancer.gov

NCI Technology Transfer Center (TTC) licenses the discoveries of NCI and nine other NIH Institutes so new technologies can be developed and commercialized, to convert them into public health benefits.

University of Washington's eScience Institute Promotes New Training and Career Pathways in Data Science

NASA Astrophysics Data System (ADS)

Stone, S.; Parker, M. S.; Howe, B.; Lazowska, E.

2015-12-01

Rapid advances in technology are transforming nearly every field from "data-poor" to "data-rich." The ability to extract knowledge from this abundance of data is the cornerstone of 21st century discovery. At the University of Washington eScience Institute, our mission is to engage researchers across disciplines in developing and applying advanced computational methods and tools to real world problems in data-intensive discovery. Our research team consists of individuals with diverse backgrounds in domain sciences such as astronomy, oceanography and geology, with complementary expertise in advanced statistical and computational techniques such as data management, visualization, and machine learning. Two key elements are necessary to foster careers in data science: individuals with cross-disciplinary training in both method and domain sciences, and career paths emphasizing alternative metrics for advancement. We see persistent and deep-rooted challenges for the career paths of people whose skills, activities and work patterns don't fit neatly into the traditional roles and success metrics of academia. To address these challenges the eScience Institute has developed training programs and established new career opportunities for data-intensive research in academia. Our graduate students and post-docs have mentors in both a methodology and an application field. They also participate in coursework and tutorials to advance technical skill and foster community. Professional Data Scientist positions were created to support research independence while encouraging the development and adoption of domain-specific tools and techniques. The eScience Institute also supports the appointment of faculty who are innovators in developing and applying data science methodologies to advance their field of discovery. Our ultimate goal is to create a supportive environment for data science in academia and to establish global recognition for data-intensive discovery across all fields.

Knowledge discovery from data and Monte-Carlo DEA to evaluate technical efficiency of mental health care in small health areas

PubMed Central

García-Alonso, Carlos; Pérez-Naranjo, Leonor

2009-01-01

Introduction Knowledge management, based on information transfer between experts and analysts, is crucial for the validity and usability of data envelopment analysis (DEA). Aim To design and develop a methodology: i) to assess technical efficiency of small health areas (SHA) in an uncertainty environment, and ii) to transfer information between experts and operational models, in both directions, for improving expert’s knowledge. Method A procedure derived from knowledge discovery from data (KDD) is used to select, interpret and weigh DEA inputs and outputs. Based on KDD results, an expert-driven Monte-Carlo DEA model has been designed to assess the technical efficiency of SHA in Andalusia. Results In terms of probability, SHA 29 is the most efficient being, on the contrary, SHA 22 very inefficient. 73% of analysed SHA have a probability of being efficient (Pe) >0.9 and 18% <0.5. Conclusions Expert knowledge is necessary to design and validate any operational model. KDD techniques make the transfer of information from experts to any operational model easy and results obtained from the latter improve expert’s knowledge.

Search Pathways: Modeling GeoData Search Behavior to Support Usable Application Development

NASA Astrophysics Data System (ADS)

Yarmey, L.; Rosati, A.; Tressel, S.

2014-12-01

Recent technical advances have enabled development of new scientific data discovery systems. Metadata brokering, linked data, and other mechanisms allow users to discover scientific data of interes across growing volumes of heterogeneous content. Matching this complex content with existing discovery technologies, people looking for scientific data are presented with an ever-growing array of features to sort, filter, subset, and scan through search returns to help them find what they are looking for. This paper examines the applicability of available technologies in connecting searchers with the data of interest. What metrics can be used to track success given shifting baselines of content and technology? How well do existing technologies map to steps in user search patterns? Taking a user-driven development approach, the team behind the Arctic Data Explorer interdisciplinary data discovery application invested heavily in usability testing and user search behavior analysis. Building on earlier library community search behavior work, models were developed to better define the diverse set of thought processes and steps users took to find data of interest, here called 'search pathways'. This research builds a deeper understanding of the user community that seeks to reuse scientific data. This approach ensures that development decisions are driven by clearly articulated user needs instead of ad hoc technology trends. Initial results from this research will be presented along with lessons learned for other discovery platform development and future directions for informatics research into search pathways.

Seafloor Science and Remotely Operated Vehicle (SSROV) Day Camp: A Week-Long, Hands-On STEM Summer Camp

NASA Astrophysics Data System (ADS)

Wheat, C. G.; Fournier, T.; Monahan, K.; Paul, C.

2015-12-01

RETINA (Robotic Exploration Technologies IN Astrobiology) has developed a program geared towards stimulating our youth with innovative and relevant hands-on learning modules under a STEM umbrella. Given the breadth of potential science and engineering topics that excite children, the RETINA Program focuses on interactive participation in the design and development of simple robotic and sensor systems, providing a range of challenges to engage students through project-based learning (PBL). Thus, young students experience scientific discovery through the use and understanding of technology. This groundwork serves as the foundation for SSROV Camp, a week-long, summer day camp for 6th-8th grade students. The camp is centered on the sensors and platforms that guide seafloor exploration and discovery and builds upon the notion that transformative discoveries in the deep sea result from either sampling new environments or making new measurements with sensors adapted to this extreme environment. These technical and scientific needs are folded into the curriculum. Each of the first four days of the camp includes four team-based, hands-on technical challenges, communication among peer groups, and competition. The fifth day includes additional activities, culminating in camper-led presentations to describe a planned mission based on a given geologic setting. Presentations include hypotheses, operational requirements and expected data products. SSROV Camp was initiated last summer for three sessions, two in Monterey, CA and one in Oxford, MS. Campers from both regions grasped key elements of the program, based on written responses to questions before and after the camp. On average, 32% of the pre-test questions were answered correctly compared with 80% of the post-test questions. Additional confirmation of gains in campers' knowledge, skills, and critical thinking on environmental issues and engineering problems were apparent during the "jeopardy" competition, nightly homework, and mission presentations. On the basis of this successful effort, we hope to expand to other towns.

[Artificial Intelligence in Drug Discovery].

PubMed

Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

2018-04-01

According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

The University of Kansas High-Throughput Screening laboratory. Part I: meeting drug-discovery needs in the heartland of America with entrepreneurial flair.

PubMed

McDonald, Peter R; Roy, Anuradha; Chaguturu, Rathnam

2011-05-01

The University of Kansas High-Throughput Screening (KU HTS) core is a state-of-the-art drug-discovery facility with an entrepreneurial open-service policy, which provides centralized resources supporting public- and private-sector research initiatives. The KU HTS core applies pharmaceutical industry project-management principles in an academic setting by bringing together multidisciplinary teams to fill critical scientific and technology gaps, using an experienced team of industry-trained researchers and project managers. The KU HTS proactively engages in supporting grant applications for extramural funding, intellectual-property management and technology transfer. The KU HTS staff further provides educational opportunities for the KU faculty and students to learn cutting-edge technologies in drug-discovery platforms through seminars, workshops, internships and course teaching. This is the first instalment of a two-part contribution from the KU HTS laboratory.

Microwave and continuous flow technologies in drug discovery.

PubMed

Sadler, Sara; Moeller, Alexander R; Jones, Graham B

2012-12-01

Microwave and continuous flow microreactors have become mainstream heating sources in contemporary pharmaceutical company laboratories. Such technologies will continue to benefit from design and engineering improvements, and now play a key role in the drug discovery process. The authors review the applications of flow- and microwave-mediated heating in library, combinatorial, solid-phase, metal-assisted, and protein chemistries. Additionally, the authors provide a description of the combination of microwave and continuous flow platforms, with applications in the preparation of radiopharmaceuticals and in drug candidate development. Literature reviewed is chiefly 2000 - 2012, plus key citations from earlier reports. With the advent of microwave irradiation, reactions that normally took days to complete can now be performed in a matter of minutes. Coupled with the introduction of continuous flow microreactors, pharmaceutical companies have an easy way to improve the greenness and efficiency of many synthetic operations. The combined force of these technologies offers the potential to revolutionize discovery and manufacturing processes.

18 CFR 385.403 - Methods of discovery; general provisions (Rule 403).

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Methods of discovery; general provisions (Rule 403). 385.403 Section 385.403 Conservation of Power and Water Resources FEDERAL... the response is true and accurate to the best of that person's knowledge, information, and belief...

Evaluation Techniques for the Sandy Point Discovery Center, Great Bay National Estuarine Research Reserve.

ERIC Educational Resources Information Center

Heffernan, Bernadette M.

1998-01-01

Describes work done to provide staff of the Sandy Point Discovery Center with methods for evaluating exhibits and interpretive programming. Quantitative and qualitative evaluation measures were designed to assess the program's objective of estuary education. Pretest-posttest questionnaires and interviews are used to measure subjects' knowledge and…

The Prehistory of Discovery: Precursors of Representational Change in Solving Gear System Problems.

ERIC Educational Resources Information Center

Dixon, James A.; Bangert, Ashley S.

2002-01-01

This study investigated whether the process of representational change undergoes developmental change or different processes occupy different niches in the course of knowledge acquisition. Subjects--college, third-, and sixth-grade students--solved gear system problems over two sessions. Findings indicated that for all grades, discovery of the…

40 CFR 300.300 - Phase I-Discovery or notification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 27 2010-07-01 2010-07-01 false Phase I-Discovery or notification. 300.300 Section 300.300 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND... person in charge of a vessel or a facility shall, as soon as he or she has knowledge of any discharge...

Next-generation sequencing in clinical virology: Discovery of new viruses.

PubMed

Datta, Sibnarayan; Budhauliya, Raghvendra; Das, Bidisha; Chatterjee, Soumya; Vanlalhmuaka; Veer, Vijay

2015-08-12

Viruses are a cause of significant health problem worldwide, especially in the developing nations. Due to different anthropological activities, human populations are exposed to different viral pathogens, many of which emerge as outbreaks. In such situations, discovery of novel viruses is utmost important for deciding prevention and treatment strategies. Since last century, a number of different virus discovery methods, based on cell culture inoculation, sequence-independent PCR have been used for identification of a variety of viruses. However, the recent emergence and commercial availability of next-generation sequencers (NGS) has entirely changed the field of virus discovery. These massively parallel sequencing platforms can sequence a mixture of genetic materials from a very heterogeneous mix, with high sensitivity. Moreover, these platforms work in a sequence-independent manner, making them ideal tools for virus discovery. However, for their application in clinics, sample preparation or enrichment is necessary to detect low abundance virus populations. A number of techniques have also been developed for enrichment or viral nucleic acids. In this manuscript, we review the evolution of sequencing; NGS technologies available today as well as widely used virus enrichment technologies. We also discuss the challenges associated with their applications in the clinical virus discovery.

SAFOD Brittle Microstructure and Mechanics Knowledge Base (BM2KB)

NASA Astrophysics Data System (ADS)

Babaie, Hassan A.; Broda Cindi, M.; Hadizadeh, Jafar; Kumar, Anuj

2013-07-01

Scientific drilling near Parkfield, California has established the San Andreas Fault Observatory at Depth (SAFOD), which provides the solid earth community with short range geophysical and fault zone material data. The BM2KB ontology was developed in order to formalize the knowledge about brittle microstructures in the fault rocks sampled from the SAFOD cores. A knowledge base, instantiated from this domain ontology, stores and presents the observed microstructural and analytical data with respect to implications for brittle deformation and mechanics of faulting. These data can be searched on the knowledge base‧s Web interface by selecting a set of terms (classes, properties) from different drop-down lists that are dynamically populated from the ontology. In addition to this general search, a query can also be conducted to view data contributed by a specific investigator. A search by sample is done using the EarthScope SAFOD Core Viewer that allows a user to locate samples on high resolution images of core sections belonging to different runs and holes. The class hierarchy of the BM2KB ontology was initially designed using the Unified Modeling Language (UML), which was used as a visual guide to develop the ontology in OWL applying the Protégé ontology editor. Various Semantic Web technologies such as the RDF, RDFS, and OWL ontology languages, SPARQL query language, and Pellet reasoning engine, were used to develop the ontology. An interactive Web application interface was developed through Jena, a java based framework, with AJAX technology, jsp pages, and java servlets, and deployed via an Apache tomcat server. The interface allows the registered user to submit data related to their research on a sample of the SAFOD core. The submitted data, after initial review by the knowledge base administrator, are added to the extensible knowledge base and become available in subsequent queries to all types of users. The interface facilitates inference capabilities in the ontology, supports SPARQL queries, allows for modifications based on successive discoveries, and provides an accessible knowledge base on the Web.

Drug Discovery Prospect from Untapped Species: Indications from Approved Natural Product Drugs

PubMed Central

Qin, Chu; Tao, Lin; Liu, Xin; Shi, Zhe; Zhang, Cun Long; Tan, Chun Yan; Chen, Yu Zong; Jiang, Yu Yang

2012-01-01

Due to extensive bioprospecting efforts of the past and technology factors, there have been questions about drug discovery prospect from untapped species. We analyzed recent trends of approved drugs derived from previously untapped species, which show no sign of untapped drug-productive species being near extinction and suggest high probability of deriving new drugs from new species in existing drug-productive species families and clusters. Case histories of recently approved drugs reveal useful strategies for deriving new drugs from the scaffolds and pharmacophores of the natural product leads of these untapped species. New technologies such as cryptic gene-cluster exploration may generate novel natural products with highly anticipated potential impact on drug discovery. PMID:22808057

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Designer drugs: the evolving science of drug discovery.

PubMed

Wanke, L A; DuBose, R F

1998-07-01

Drug discovery and design are fundamental to drug development. Until recently, most drugs were discovered through random screening or developed through molecular modification. New technologies are revolutionizing this phase of drug development. Rational drug design, using powerful computers and computational chemistry and employing X-ray crystallography, nuclear magnetic resonance spectroscopy, and three-dimensional quantitative structure activity relationship analysis, is creating highly specific, biologically active molecules by virtual reality modeling. Sophisticated screening technologies are eliminating all but the most active lead compounds. These new technologies promise more efficacious, safe, and cost-effective medications, while minimizing drug development time and maximizing profits.

Alaska's Secondary Science Teachers and Students Receive Earth Systems Science Knowledge, GIS Know How and University Technical Support for Pre- College Research Experiences: The EDGE Project

NASA Astrophysics Data System (ADS)

Connor, C. L.; Prakash, A.

2007-12-01

Alaska's secondary school teachers are increasingly required to provide Earth systems science (ESS) education that integrates student observations of local natural processes related to rapid climate change with geospatial datasets and satellite imagery using Geographic Information Systems (GIS) technology. Such skills are also valued in various employment sectors of the state where job opportunities requiring Earth science and GIS training are increasing. University of Alaska's EDGE (Experiential Discoveries in Geoscience Education) program has provided training and classroom resources for 3 cohorts of inservice Alaska science and math teachers in GIS and Earth Systems Science (2005-2007). Summer workshops include geologic field experiences, GIS instruction, computer equipment and technical support for groups of Alaska high school (HS) and middle school (MS) science teachers each June and their students in August. Since 2005, EDGE has increased Alaska science and math teachers' Earth science content knowledge and developed their GIS and computer skills. In addition, EDGE has guided teachers using a follow-up, fall online course that provided more extensive ESS knowledge linked with classroom standards and provided course content that was directly transferable into their MS and HS science classrooms. EDGE teachers were mentored by University faculty and technical staff as they guided their own students through semester-scale, science fair style projects using geospatial data that was student- collected. EDGE program assessment indicates that all teachers have improved their ESS knowledge, GIS knowledge, and the use of technology in their classrooms. More than 230 middle school students have learned GIS, from EDGE teachers and 50 EDGE secondary students have conducted original research related to landscape change and its impacts on their own communities. Longer-term EDGE goals include improving student performance on the newly implemented (spring 2008) 10th grade, standards-based, High School Qualifying Exam, on recruiting first-generation college students, and on increasing the number of Earth science majors in the University of Alaska system.

Mississippi Curriculum Framework for Computer Discovery (8th Grade). CIP: 00.0252.

ERIC Educational Resources Information Center

Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

This document, which is intended for technology educators in Mississippi, outlines a modular instruction approach that allows eighth graders to experience various workplace technologies within four career cluster areas: agriculture/natural resources technology, business/marketing technology, health/human services technology, and…

Serendipity: Accidental Discoveries in Science

NASA Astrophysics Data System (ADS)

Roberts, Royston M.

1989-06-01

Many of the things discovered by accident are important in our everyday lives: Teflon, Velcro, nylon, x-rays, penicillin, safety glass, sugar substitutes, and polyethylene and other plastics. And we owe a debt to accident for some of our deepest scientific knowledge, including Newton's theory of gravitation, the Big Bang theory of Creation, and the discovery of DNA. Even the Rosetta Stone, the Dead Sea Scrolls, and the ruins of Pompeii came to light through chance. This book tells the fascinating stories of these and other discoveries and reveals how the inquisitive human mind turns accident into discovery. Written for the layman, yet scientifically accurate, this illuminating collection of anecdotes portrays invention and discovery as quintessentially human acts, due in part to curiosity, perserverance, and luck.

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery.

PubMed

Thomford, Nicholas Ekow; Senthebane, Dimakatso Alice; Rowe, Arielle; Munro, Daniella; Seele, Palesa; Maroyi, Alfred; Dzobo, Kevin

2018-05-25

The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of "active compound" has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of 'organ-on chip' and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review discusses plant-based natural product drug discovery and how innovative technologies play a role in next-generation drug discovery.

From the EBM pyramid to the Greek temple: a new conceptual approach to Guidelines as implementation tools in mental health.

PubMed

Salvador-Carulla, L; Lukersmith, S; Sullivan, W

2017-04-01

Guideline methods to develop recommendations dedicate most effort around organising discovery and corroboration knowledge following the evidence-based medicine (EBM) framework. Guidelines typically use a single dimension of information, and generally discard contextual evidence and formal expert knowledge and consumer's experiences in the process. In recognition of the limitations of guidelines in complex cases, complex interventions and systems research, there has been significant effort to develop new tools, guides, resources and structures to use alongside EBM methods of guideline development. In addition to these advances, a new framework based on the philosophy of science is required. Guidelines should be defined as implementation decision support tools for improving the decision-making process in real-world practice and not only as a procedure to optimise the knowledge base of scientific discovery and corroboration. A shift from the model of the EBM pyramid of corroboration of evidence to the use of broader multi-domain perspective graphically depicted as 'Greek temple' could be considered. This model takes into account the different stages of scientific knowledge (discovery, corroboration and implementation), the sources of knowledge relevant to guideline development (experimental, observational, contextual, expert-based and experiential); their underlying inference mechanisms (deduction, induction, abduction, means-end inferences) and a more precise definition of evidence and related terms. The applicability of this broader approach is presented for the development of the Canadian Consensus Guidelines for the Primary Care of People with Developmental Disabilities.

Applying data mining techniques to medical time series: an empirical case study in electroencephalography and stabilometry.

PubMed

Anguera, A; Barreiro, J M; Lara, J A; Lizcano, D

2016-01-01

One of the major challenges in the medical domain today is how to exploit the huge amount of data that this field generates. To do this, approaches are required that are capable of discovering knowledge that is useful for decision making in the medical field. Time series are data types that are common in the medical domain and require specialized analysis techniques and tools, especially if the information of interest to specialists is concentrated within particular time series regions, known as events. This research followed the steps specified by the so-called knowledge discovery in databases (KDD) process to discover knowledge from medical time series derived from stabilometric (396 series) and electroencephalographic (200) patient electronic health records (EHR). The view offered in the paper is based on the experience gathered as part of the VIIP project. Knowledge discovery in medical time series has a number of difficulties and implications that are highlighted by illustrating the application of several techniques that cover the entire KDD process through two case studies. This paper illustrates the application of different knowledge discovery techniques for the purposes of classification within the above domains. The accuracy of this application for the two classes considered in each case is 99.86% and 98.11% for epilepsy diagnosis in the electroencephalography (EEG) domain and 99.4% and 99.1% for early-age sports talent classification in the stabilometry domain. The KDD techniques achieve better results than other traditional neural network-based classification techniques.

[Current applications of high-throughput DNA sequencing technology in antibody drug research].

PubMed

Yu, Xin; Liu, Qi-Gang; Wang, Ming-Rong

2012-03-01

Since the publication of a high-throughput DNA sequencing technology based on PCR reaction was carried out in oil emulsions in 2005, high-throughput DNA sequencing platforms have been evolved to a robust technology in sequencing genomes and diverse DNA libraries. Antibody libraries with vast numbers of members currently serve as a foundation of discovering novel antibody drugs, and high-throughput DNA sequencing technology makes it possible to rapidly identify functional antibody variants with desired properties. Herein we present a review of current applications of high-throughput DNA sequencing technology in the analysis of antibody library diversity, sequencing of CDR3 regions, identification of potent antibodies based on sequence frequency, discovery of functional genes, and combination with various display technologies, so as to provide an alternative approach of discovery and development of antibody drugs.

Equation Discovery for Model Identification in Respiratory Mechanics of the Mechanically Ventilated Human Lung

NASA Astrophysics Data System (ADS)

Ganzert, Steven; Guttmann, Josef; Steinmann, Daniel; Kramer, Stefan

Lung protective ventilation strategies reduce the risk of ventilator associated lung injury. To develop such strategies, knowledge about mechanical properties of the mechanically ventilated human lung is essential. This study was designed to develop an equation discovery system to identify mathematical models of the respiratory system in time-series data obtained from mechanically ventilated patients. Two techniques were combined: (i) the usage of declarative bias to reduce search space complexity and inherently providing the processing of background knowledge. (ii) A newly developed heuristic for traversing the hypothesis space with a greedy, randomized strategy analogical to the GSAT algorithm. In 96.8% of all runs the applied equation discovery system was capable to detect the well-established equation of motion model of the respiratory system in the provided data. We see the potential of this semi-automatic approach to detect more complex mathematical descriptions of the respiratory system from respiratory data.

Of possible cheminformatics futures.

PubMed

Oprea, Tudor I; Taboureau, Olivier; Bologa, Cristian G

2012-01-01

For over a decade, cheminformatics has contributed to a wide array of scientific tasks from analytical chemistry and biochemistry to pharmacology and drug discovery; and although its contributions to decision making are recognized, the challenge is how it would contribute to faster development of novel, better products. Here we address the future of cheminformatics with primary focus on innovation. Cheminformatics developers often need to choose between "mainstream" (i.e., accepted, expected) and novel, leading-edge tools, with an increasing trend for open science. Possible futures for cheminformatics include the worst case scenario (lack of funding, no creative usage), as well as the best case scenario (complete integration, from systems biology to virtual physiology). As "-omics" technologies advance, and computer hardware improves, compounds will no longer be profiled at the molecular level, but also in terms of genetic and clinical effects. Among potentially novel tools, we anticipate machine learning models based on free text processing, an increased performance in environmental cheminformatics, significant decision-making support, as well as the emergence of robot scientists conducting automated drug discovery research. Furthermore, cheminformatics is anticipated to expand the frontiers of knowledge and evolve in an open-ended, extensible manner, allowing us to explore multiple research scenarios in order to avoid epistemological "local information minimum trap".

Quantitative mass spectrometry: an overview

NASA Astrophysics Data System (ADS)

Urban, Pawel L.

2016-10-01

Mass spectrometry (MS) is a mainstream chemical analysis technique in the twenty-first century. It has contributed to numerous discoveries in chemistry, physics and biochemistry. Hundreds of research laboratories scattered all over the world use MS every day to investigate fundamental phenomena on the molecular level. MS is also widely used by industry-especially in drug discovery, quality control and food safety protocols. In some cases, mass spectrometers are indispensable and irreplaceable by any other metrological tools. The uniqueness of MS is due to the fact that it enables direct identification of molecules based on the mass-to-charge ratios as well as fragmentation patterns. Thus, for several decades now, MS has been used in qualitative chemical analysis. To address the pressing need for quantitative molecular measurements, a number of laboratories focused on technological and methodological improvements that could render MS a fully quantitative metrological platform. In this theme issue, the experts working for some of those laboratories share their knowledge and enthusiasm about quantitative MS. I hope this theme issue will benefit readers, and foster fundamental and applied research based on quantitative MS measurements. This article is part of the themed issue 'Quantitative mass spectrometry'.

Framework for development of physician competencies in genomic medicine: report of the Competencies Working Group of the Inter-Society Coordinating Committee for Physician Education in Genomics.

PubMed

Korf, Bruce R; Berry, Anna B; Limson, Melvin; Marian, Ali J; Murray, Michael F; O'Rourke, P Pearl; Passamani, Eugene R; Relling, Mary V; Tooker, John; Tsongalis, Gregory J; Rodriguez, Laura L

2014-11-01

Completion of the Human Genome Project, in conjunction with dramatic reductions in the cost of DNA sequencing and advances in translational research, is gradually ushering genomic discoveries and technologies into the practice of medicine. The rapid pace of these advances is opening up a gap between the knowledge available about the clinical relevance of genomic information and the ability of clinicians to include such information in their medical practices. This educational gap threatens to be rate limiting to the clinical adoption of genomics in medicine. Solutions will require not only a better understanding of the clinical implications of genetic discoveries but also training in genomics at all levels of professional development, including for individuals in formal training and others who long ago completed such training. The National Human Genome Research Institute has convened the Inter-Society Coordinating Committee for Physician Education in Genomics (ISCC) to develop and share best practices in the use of genomics in medicine. The ISCC has developed a framework for development of genomics practice competencies that may serve as a starting point for formulation of competencies for physicians in various medical disciplines.