Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases.

PubMed

Oh, Soo Jin; Choi, Young Ki; Shin, Ok Sarah

2018-03-01

Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs. © Copyright: Yonsei University College of Medicine 2018.

Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases

PubMed Central

2018-01-01

Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs. PMID:29436184

Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

MCT-based SWIR hyperspectral imaging system for evaluation of biological samples

USDA-ARS?s Scientific Manuscript database

Hyperspectral imaging has been shown to be a powerful tool for nondestructive evaluation of biological samples. We recently developed a new line-scan-based shortwave infrared (SWIR) hyperspectral imaging system. Critical sensing components of the system include a SWIR spectrograph, an MCT (HgCdTe) a...

Learning Systems Biology: Conceptual Considerations toward a Web-Based Learning Platform

ERIC Educational Resources Information Center

Emmert-Streib, Frank; Dehmer, Matthias; Lyardet, Fernando

2013-01-01

Within recent years, there is an increasing need to train students, from biology and beyond, in quantitative methods that are relevant to cope with data-driven biology. Systems Biology is such a field that places a particular focus on the functional aspect of biology and molecular interacting processes. This paper deals with the conceptual design…

Supplementing Introductory Biology with On-Line Curriculum

ERIC Educational Resources Information Center

McGroarty, Estelle; Parker, Joyce; Heidemann, Merle; Lim, Heejun; Olson, Mark; Long, Tammy; Merrill, John; Riffell, Samuel; Smith, James; Batzli, Janet; Kirschtel, David

2004-01-01

We developed web-based modules addressing fundamental concepts of introductory biology delivered through the LON-CAPA course management system. These modules were designed and used to supplement large, lecture-based introductory biology classes. Incorporating educational principles and the strength of web-based instructional technology, choices…

Synthetic biology through biomolecular design and engineering.

PubMed

Channon, Kevin; Bromley, Elizabeth H C; Woolfson, Derek N

2008-08-01

Synthetic biology is a rapidly growing field that has emerged in a global, multidisciplinary effort among biologists, chemists, engineers, physicists, and mathematicians. Broadly, the field has two complementary goals: To improve understanding of biological systems through mimicry and to produce bio-orthogonal systems with new functions. Here we review the area specifically with reference to the concept of synthetic biology space, that is, a hierarchy of components for, and approaches to generating new synthetic and functional systems to test, advance, and apply our understanding of biological systems. In keeping with this issue of Current Opinion in Structural Biology, we focus largely on the design and engineering of biomolecule-based components and systems.

Graphic Representation of Carbon Dioxide Equilibria in Biological Systems.

ERIC Educational Resources Information Center

Kindig, Neal B.; Filley, Giles F.

1983-01-01

The log C-pH diagram is a useful means of displaying quantitatively the many variables (including temperature) that determine acid-base equilibria in biological systems. Presents the diagram as extended to open/closed biological systems and derives a new water-ion balance method for determining equilibrium pH. (JN)

Evaluation and modeling of HIV based on communication theory in biological systems.

PubMed

Dong, Miaowu; Li, Wenrong; Xu, Xi

2016-12-01

Some forms of communication are used in biological systems such as HIV transmission in human beings. In this paper, we plan to get a unique insight into biological communication systems generally through the analogy between HIV infection and electrical communication system. The model established in this paper can be used to test and simulate various communication systems since it provides researchers with an opportunity. We interpret biological communication systems by using telecommunications exemplification from a layered communication protocol developed before and use the model to indicate HIV spreading. We also implement a simulation of HIV infection based on the layered communication protocol to predict the development of this disease and the results prove the validity of the model. Copyright © 2016 Elsevier B.V. All rights reserved.

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

Using the Unified Modelling Language (UML) to guide the systemic description of biological processes and systems.

PubMed

Roux-Rouquié, Magali; Caritey, Nicolas; Gaubert, Laurent; Rosenthal-Sabroux, Camille

2004-07-01

One of the main issues in Systems Biology is to deal with semantic data integration. Previously, we examined the requirements for a reference conceptual model to guide semantic integration based on the systemic principles. In the present paper, we examine the usefulness of the Unified Modelling Language (UML) to describe and specify biological systems and processes. This makes unambiguous representations of biological systems, which would be suitable for translation into mathematical and computational formalisms, enabling analysis, simulation and prediction of these systems behaviours.

A Case Study of Web-Based Instruction (WBI): The Effectiveness of Using Frontpage Feedback System (FFS) as Metacognition Strategy for Freshmen Biology Teaching

ERIC Educational Resources Information Center

Wang, Tzu-Hua; Wang, Wei-Lung; Wang, Kuo-Hua; Huang, Hsih-Chieh

2004-01-01

This research aims to develop a Metacognition strategy for Web-Based Instruction (WBI) to stimulate reflective questions in biology learning to run Frontpage Feedback System (FFS) embedded in web pages, and thus to evaluate the influence of this internet-teaching style on biology learning among freshmen. According to the questionnaire survey, we…

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

Virtual Tissues and Developmental Systems Biology (book chapter)

EPA Science Inventory

Virtual tissue (VT) models provide an in silico environment to simulate cross-scale properties in specific tissues or organs based on knowledge of the underlying biological networks. These integrative models capture the fundamental interactions in a biological system and enable ...

A Neural Systems-Based Neurobiology and Neuropsychiatry Course: Integrating Biology, Psychodynamics, and Psychology in the Psychiatric Curriculum

ERIC Educational Resources Information Center

Lacy, Timothy; Hughes, John D.

2006-01-01

Objective: Psychotherapy and biological psychiatry remain divided in psychiatry residency curricula. Behavioral neurobiology and neuropsychiatry provide a systems-level framework that allows teachers to integrate biology, psychodynamics, and psychology. Method: The authors detail the underlying assumptions and outline of a neural systems-based…

Using argument notation to engineer biological simulations with increased confidence

PubMed Central

Alden, Kieran; Andrews, Paul S.; Polack, Fiona A. C.; Veiga-Fernandes, Henrique; Coles, Mark C.; Timmis, Jon

2015-01-01

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions. PMID:25589574

Using argument notation to engineer biological simulations with increased confidence.

PubMed

Alden, Kieran; Andrews, Paul S; Polack, Fiona A C; Veiga-Fernandes, Henrique; Coles, Mark C; Timmis, Jon

2015-03-06

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions.

CONCEPTUAL FRAMEWORK FOR THE CHEMICAL EFFECTS IN BIOLOGICAL SYSTEMS (CEBS) TOXICOGENOMICS KNOWLEDGE BASE

EPA Science Inventory

Conceptual Framework for the Chemical Effects in Biological Systems (CEBS) T oxicogenomics Knowledge Base

Abstract
Toxicogenomics studies how the genome is involved in responses to environmental stressors or toxicants. It combines genetics, genome-scale mRNA expressio...

Construction of a Linux based chemical and biological information system.

PubMed

Molnár, László; Vágó, István; Fehér, András

2003-01-01

A chemical and biological information system with a Web-based easy-to-use interface and corresponding databases has been developed. The constructed system incorporates all chemical, numerical and textual data related to the chemical compounds, including numerical biological screen results. Users can search the database by traditional textual/numerical and/or substructure or similarity queries through the web interface. To build our chemical database management system, we utilized existing IT components such as ORACLE or Tripos SYBYL for database management and Zope application server for the web interface. We chose Linux as the main platform, however, almost every component can be used under various operating systems.

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

PubMed

Rao, Rohit T; Scherholz, Megerle L; Hartmanshenn, Clara; Bae, Seul-A; Androulakis, Ioannis P

2017-12-05

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Programmable Hydrogel Ionic Circuits for Biologically Matched Electronic Interfaces.

PubMed

Zhao, Siwei; Tseng, Peter; Grasman, Jonathan; Wang, Yu; Li, Wenyi; Napier, Bradley; Yavuz, Burcin; Chen, Ying; Howell, Laurel; Rincon, Javier; Omenetto, Fiorenzo G; Kaplan, David L

2018-06-01

The increased need for wearable and implantable medical devices has driven the demand for electronics that interface with living systems. Current bioelectronic systems have not fully resolved mismatches between engineered circuits and biological systems, including the resulting pain and damage to biological tissues. Here, salt/poly(ethylene glycol) (PEG) aqueous two-phase systems are utilized to generate programmable hydrogel ionic circuits. High-conductivity salt-solution patterns are stably encapsulated within PEG hydrogel matrices using salt/PEG phase separation, which route ionic current with high resolution and enable localized delivery of electrical stimulation. This strategy allows designer electronics that match biological systems, including transparency, stretchability, complete aqueous-based connective interface, distribution of ionic electrical signals between engineered and biological systems, and avoidance of tissue damage from electrical stimulation. The potential of such systems is demonstrated by generating light-emitting diode (LED)-based displays, skin-mounted electronics, and stimulators that deliver localized current to in vitro neuron cultures and muscles in vivo with reduced adverse effects. Such electronic platforms may form the basis of future biointegrated electronic systems. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The emerging genomics and systems biology research lead to systems genomics studies.

PubMed

Yang, Mary Qu; Yoshigoe, Kenji; Yang, William; Tong, Weida; Qin, Xiang; Dunker, A; Chen, Zhongxue; Arbania, Hamid R; Liu, Jun S; Niemierko, Andrzej; Yang, Jack Y

2014-01-01

Synergistically integrating multi-layer genomic data at systems level not only can lead to deeper insights into the molecular mechanisms related to disease initiation and progression, but also can guide pathway-based biomarker and drug target identification. With the advent of high-throughput next-generation sequencing technologies, sequencing both DNA and RNA has generated multi-layer genomic data that can provide DNA polymorphism, non-coding RNA, messenger RNA, gene expression, isoform and alternative splicing information. Systems biology on the other hand studies complex biological systems, particularly systematic study of complex molecular interactions within specific cells or organisms. Genomics and molecular systems biology can be merged into the study of genomic profiles and implicated biological functions at cellular or organism level. The prospectively emerging field can be referred to as systems genomics or genomic systems biology. The Mid-South Bioinformatics Centre (MBC) and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and University of Arkansas for Medical Sciences are particularly interested in promoting education and research advancement in this prospectively emerging field. Based on past investigations and research outcomes, MBC is further utilizing differential gene and isoform/exon expression from RNA-seq and co-regulation from the ChiP-seq specific for different phenotypes in combination with protein-protein interactions, and protein-DNA interactions to construct high-level gene networks for an integrative genome-phoneme investigation at systems biology level.

From Here to Autonomicity: Self-Managing Agents and the Biological Metaphors that Inspire Them

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

We seek inspiration for self-managing systems from (obviously, pre-existing) biological mechanisms. Autonomic Computing (AC), a self-managing systems initiative based on the biological metaphor of the autonomic nervous system, is increasingly gaining momentum as the way forward for integrating and designing reliable systems, while agent technologies have been identified as a key enabler for engineering autonomicity in systems. This paper looks at other biological metaphors such as reflex and healing, heart- beat monitors, pulse monitors and apoptosis for assisting in the realization of autonomicity.

Reverse engineering systems models of regulation: discovery, prediction and mechanisms.

PubMed

Ashworth, Justin; Wurtmann, Elisabeth J; Baliga, Nitin S

2012-08-01

Biological systems can now be understood in comprehensive and quantitative detail using systems biology approaches. Putative genome-scale models can be built rapidly based upon biological inventories and strategic system-wide molecular measurements. Current models combine statistical associations, causative abstractions, and known molecular mechanisms to explain and predict quantitative and complex phenotypes. This top-down 'reverse engineering' approach generates useful organism-scale models despite noise and incompleteness in data and knowledge. Here we review and discuss the reverse engineering of biological systems using top-down data-driven approaches, in order to improve discovery, hypothesis generation, and the inference of biological properties. Copyright © 2011 Elsevier Ltd. All rights reserved.

Formal reasoning about systems biology using theorem proving

PubMed Central

Hasan, Osman; Siddique, Umair; Tahar, Sofiène

2017-01-01

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients. PMID:28671950

Applying systems biology methods to the study of human physiology in extreme environments

PubMed Central

2013-01-01

Systems biology is defined in this review as ‘an iterative process of computational model building and experimental model revision with the aim of understanding or simulating complex biological systems’. We propose that, in practice, systems biology rests on three pillars: computation, the omics disciplines and repeated experimental perturbation of the system of interest. The number of ethical and physiologically relevant perturbations that can be used in experiments on healthy humans is extremely limited and principally comprises exercise, nutrition, infusions (e.g. Intralipid), some drugs and altered environment. Thus, we argue that systems biology and environmental physiology are natural symbionts for those interested in a system-level understanding of human biology. However, despite excellent progress in high-altitude genetics and several proteomics studies, systems biology research into human adaptation to extreme environments is in its infancy. A brief description and overview of systems biology in its current guise is given, followed by a mini review of computational methods used for modelling biological systems. Special attention is given to high-altitude research, metabolic network reconstruction and constraint-based modelling. PMID:23849719

Systems Biology Approach in Hypertension Research.

PubMed

Delles, Christian; Husi, Holger

2017-01-01

Systems biology is an approach to study all genes, gene transcripts, proteins, metabolites, and their interactions in specific cells, tissues, organs, or the whole organism. It is based on data derived from high-throughput analytical technologies and bioinformatics tools to analyze these data, and aims to understand the whole system rather than individual aspects of it. Systems biology can be applied to virtually all conditions and diseases and therefore also to hypertension and its underlying vascular disorders. Unlike other methods in this book there is no clear-cut protocol to explain a systems biology approach. We will instead outline some of the most important and common steps in the generation and analysis of systems biology data.

The role of mechanics in biological and bio-inspired systems.

PubMed

Egan, Paul; Sinko, Robert; LeDuc, Philip R; Keten, Sinan

2015-07-06

Natural systems frequently exploit intricate multiscale and multiphasic structures to achieve functionalities beyond those of man-made systems. Although understanding the chemical make-up of these systems is essential, the passive and active mechanics within biological systems are crucial when considering the many natural systems that achieve advanced properties, such as high strength-to-weight ratios and stimuli-responsive adaptability. Discovering how and why biological systems attain these desirable mechanical functionalities often reveals principles that inform new synthetic designs based on biological systems. Such approaches have traditionally found success in medical applications, and are now informing breakthroughs in diverse frontiers of science and engineering.

Development and implementation of an expert system to improve the control of nitrification and denitrification in the Vic wastewater treatment plant.

PubMed

Ribas, F; Rodríguez-Roda, I; Serrat, J; Clara, P; Comas, J

2008-05-01

Wastewater treatment plants employ various physical, chemical and biological processes to reduce pollutants from raw wastewater. One of the most important is the biological nitrogen removal process through nitrification and denitrification steps taking place in various sections of the biological reactor. One of the most extensively used configurations to achieve the biological nitrogen removal is an activated sludge system using oxidation ditch or extended aeration. To improve nitrogen removal in the wastewater treatment plant (WWTP) of Vic (Catalonia, NE Spain), the automatic aeration control system was complemented with an Expert System to always provide the most appropriate aeration or anoxia sequence based on the values of ammonium and nitrates given by an automatic analyzer. This article illustrates the development and implementation of this knowledge-based system within the framework of a Decision Support System, which performs SCADA functions. The paper also shows that the application of the decision support system in the Vic WWTP resulted in significant improvements to the biological nitrogen removal.

Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Plice, Laura; Pisanich, Greg

2003-01-01

The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

PubMed

Yang, Laurence; Tan, Justin; O'Brien, Edward J; Monk, Jonathan M; Kim, Donghyuk; Li, Howard J; Charusanti, Pep; Ebrahim, Ali; Lloyd, Colton J; Yurkovich, James T; Du, Bin; Dräger, Andreas; Thomas, Alex; Sun, Yuekai; Saunders, Michael A; Palsson, Bernhard O

2015-08-25

Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

Biological-based and physical-based optimization for biological evaluation of prostate patient's plans

NASA Astrophysics Data System (ADS)

Sukhikh, E.; Sheino, I.; Vertinsky, A.

2017-09-01

Modern modalities of radiation treatment therapy allow irradiation of the tumor to high dose values and irradiation of organs at risk (OARs) to low dose values at the same time. In this paper we study optimal radiation treatment plans made in Monaco system. The first aim of this study was to evaluate dosimetric features of Monaco treatment planning system using biological versus dose-based cost functions for the OARs and irradiation targets (namely tumors) when the full potential of built-in biological cost functions is utilized. The second aim was to develop criteria for the evaluation of radiation dosimetry plans for patients based on the macroscopic radiobiological criteria - TCP/NTCP. In the framework of the study four dosimetric plans were created utilizing the full extent of biological and physical cost functions using dose calculation-based treatment planning for IMRT Step-and-Shoot delivery of stereotactic body radiation therapy (SBRT) in prostate case (5 fractions per 7 Gy).

Systems metabolic engineering strategies for the production of amino acids.

PubMed

Ma, Qian; Zhang, Quanwei; Xu, Qingyang; Zhang, Chenglin; Li, Yanjun; Fan, Xiaoguang; Xie, Xixian; Chen, Ning

2017-06-01

Systems metabolic engineering is a multidisciplinary area that integrates systems biology, synthetic biology and evolutionary engineering. It is an efficient approach for strain improvement and process optimization, and has been successfully applied in the microbial production of various chemicals including amino acids. In this review, systems metabolic engineering strategies including pathway-focused approaches, systems biology-based approaches, evolutionary approaches and their applications in two major amino acid producing microorganisms: Corynebacterium glutamicum and Escherichia coli, are summarized.

Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

PubMed Central

Liu, Fei; Heiner, Monika; Yang, Ming

2016-01-01

Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information. PMID:26910830

Developments in the Tools and Methodologies of Synthetic Biology

PubMed Central

Kelwick, Richard; MacDonald, James T.; Webb, Alexander J.; Freemont, Paul

2014-01-01

Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community. PMID:25505788

Promoting new concepts of skincare via skinomics and systems biology-From traditional skincare and efficacy-based skincare to precision skincare.

PubMed

Jiang, Biao; Jia, Yan; He, Congfen

2018-05-11

Traditional skincare involves the subjective classification of skin into 4 categories (oily, dry, mixed, and neutral) prior to skin treatment. Following the development of noninvasive methods in skin and skin imaging technology, scientists have developed efficacy-based skincare products based on the physiological characteristics of skin under different conditions. Currently, the emergence of skinomics and systems biology has facilitated the development of precision skincare. In this article, the evolution of skincare based on the physiological states of the skin (from traditional skincare and efficacy-based skincare to precision skincare) is described. In doing so, we highlight skinomics and systems biology, with particular emphasis on the importance of skin lipidomics and microbiomes in precision skincare. The emerging trends of precision skincare are anticipated. © 2018 Wiley Periodicals, Inc.

Invited review article: Advanced light microscopy for biological space research.

PubMed

De Vos, Winnok H; Beghuin, Didier; Schwarz, Christian J; Jones, David B; van Loon, Jack J W A; Bereiter-Hahn, Juergen; Stelzer, Ernst H K

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

NASA Astrophysics Data System (ADS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

A Trade Study of Two Membrane-Aerated Biological Water Processors

NASA Technical Reports Server (NTRS)

Allada, Ram; Lange, Kevin; Vega. Leticia; Roberts, Michael S.; Jackson, Andrew; Anderson, Molly; Pickering, Karen

2011-01-01

Biologically based systems are under evaluation as primary water processors for next generation life support systems due to their low power requirements and their inherent regenerative nature. This paper will summarize the results of two recent studies involving membrane aerated biological water processors and present results of a trade study comparing the two systems with regards to waste stream composition, nutrient loading and system design. Results of optimal configurations will be presented.

The "Biologically-Inspired Computing" Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2007-01-01

Self-managing systems, whether viewed from the perspective of Autonomic Computing, or from that of another initiative, offers a holistic vision for the development and evolution of biologically-inspired computer-based systems. It aims to bring new levels of automation and dependability to systems, while simultaneously hiding their complexity and reducing costs. A case can certainly be made that all computer-based systems should exhibit autonomic properties [6], and we envisage greater interest in, and uptake of, autonomic principles in future system development.

Biological standards for the Knowledge-Based BioEconomy: What is at stake.

PubMed

de Lorenzo, Víctor; Schmidt, Markus

2018-01-25

The contribution of life sciences to the Knowledge-Based Bioeconomy (KBBE) asks for the transition of contemporary, gene-based biotechnology from being a trial-and-error endeavour to becoming an authentic branch of engineering. One requisite to this end is the need for standards to measure and represent accurately biological functions, along with languages for data description and exchange. However, the inherent complexity of biological systems and the lack of quantitative tradition in the field have largely curbed this enterprise. Fortunately, the onset of systems and synthetic biology has emphasized the need for standards not only to manage omics data, but also to increase reproducibility and provide the means of engineering living systems in earnest. Some domains of biotechnology can be easily standardized (e.g. physical composition of DNA sequences, tools for genome editing, languages to encode workflows), while others might be standardized with some dedicated research (e.g. biological metrology, operative systems for bio-programming cells) and finally others will require a considerable effort, e.g. defining the rules that allow functional composition of biological activities. Despite difficulties, these are worthy attempts, as the history of technology shows that those who set/adopt standards gain a competitive advantage over those who do not. Copyright © 2017 Elsevier B.V. All rights reserved.

Computational systems chemical biology.

PubMed

Oprea, Tudor I; May, Elebeoba E; Leitão, Andrei; Tropsha, Alexander

2011-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology (SCB) (Nat Chem Biol 3: 447-450, 2007).The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules, and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology/systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology, and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology.

Computational Systems Chemical Biology

PubMed Central

Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

2013-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007). The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology / systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology. PMID:20838980

Systems Biology and Mode of Action Based Risk Assessment

EPA Science Inventory

The application of systems biology has increased in the past decade largely as a consequence of the human genome project and technological advances in genomics and proteomics. Systems approaches have been used in the medical & pharmaceutical realm for diagnostic purposes and targ...

Systems Biology and Mode of Action Based Risk Assessment.

EPA Science Inventory

The application of systems biology approaches has greatly increased in the past decade largely as a consequence of the human genome project and technological advances in genomics and proteomics. Systems approaches have been used in the medical & pharmaceutical realm for diagnost...

Hemojuvelin-hepcidin axis modeled and analyzed using Petri nets.

PubMed

Formanowicz, Dorota; Kozak, Adam; Głowacki, Tomasz; Radom, Marcin; Formanowicz, Piotr

2013-12-01

Systems biology approach to investigate biological phenomena seems to be very promising because it is capable to capture one of the fundamental properties of living organisms, i.e. their inherent complexity. It allows for analysis biological entities as complex systems of interacting objects. The first and necessary step of such an analysis is building a precise model of the studied biological system. This model is expressed in the language of some branch of mathematics, as for example, differential equations. During the last two decades the theory of Petri nets has appeared to be very well suited for building models of biological systems. The structure of these nets reflects the structure of interacting biological molecules and processes. Moreover, on one hand, Petri nets have intuitive graphical representation being very helpful in understanding the structure of the system and on the other hand, there is a lot of mathematical methods and software tools supporting an analysis of the properties of the nets. In this paper a Petri net based model of the hemojuvelin-hepcidin axis involved in the maintenance of the human body iron homeostasis is presented. The analysis based mainly on T-invariants of the model properties has been made and some biological conclusions have been drawn. Copyright © 2013 Elsevier Inc. All rights reserved.

Depth-resolved dual-beamlet vibrometry based on Fourier domain low coherence interferometry

PubMed Central

Choudhury, Niloy; Chen, Fangyi; Wang, Ruikang K.; Jacques, Steven L.; Nuttall, Alfred L.

2013-01-01

Abstract. We present an optical vibrometer based on delay-encoded, dual-beamlet phase-sensitive Fourier domain interferometric system to provide depth-resolved subnanometer scale vibration information from scattering biological specimens. System characterization, calibration, and preliminary vibrometry with biological specimens were performed. The proposed system has the potential to provide both amplitude and direction of vibration of tissue microstructures on a single two-dimensional plane. PMID:23455961

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

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent; Beghuin, Didier

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALMmore » ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.« less

Computer-Based Semantic Network in Molecular Biology: A Demonstration.

ERIC Educational Resources Information Center

Callman, Joshua L.; And Others

This paper analyzes the hardware and software features that would be desirable in a computer-based semantic network system for representing biology knowledge. It then describes in detail a prototype network of molecular biology knowledge that has been developed using Filevision software and a Macintosh computer. The prototype contains about 100…

Detecting Motion from a Moving Platform; Phase 3: Unification of Control and Sensing for More Advanced Situational Awareness

DTIC Science & Technology

2011-11-01

RX-TY-TR-2011-0096-01) develops a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica...01 summarizes the development of a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica

Translational Systems Biology and Voice Pathophysiology

PubMed Central

Li, Nicole Y. K.; Abbott, Katherine Verdolini; Rosen, Clark; An, Gary; Hebda, Patricia A.; Vodovotz, Yoram

2011-01-01

Objectives/Hypothesis Personalized medicine has been called upon to tailor healthcare to an individual's needs. Evidence-based medicine (EBM) has advocated using randomized clinical trials with large populations to evaluate treatment effects. However, due to large variations across patients, the results are likely not to apply to an individual patient. We suggest that a complementary, systems biology approach using computational modeling may help tackle biological complexity in order to improve ultimate patient care. The purpose of the article is: 1) to review the pros and cons of EBM, and 2) to discuss the alternative systems biology method and present its utility in clinical voice research. Study Design Tutorial Methods Literature review and discussion. Results We propose that translational systems biology can address many of the limitations of EBM pertinent to voice and other health care domains, and thus complement current health research models. In particular, recent work using mathematical modeling suggests that systems biology has the ability to quantify the highly complex biologic processes underlying voice pathophysiology. Recent data support the premise that this approach can be applied specifically in the case of phonotrauma and surgically induced vocal fold trauma, and may have particular power to address personalized medicine. Conclusions We propose that evidence around vocal health and disease be expanded beyond a population-based method to consider more fully issues of complexity and systems interactions, especially in implementing personalized medicine in voice care and beyond. PMID:20025041

Electrostatic thin film chemical and biological sensor

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

Prelas, Mark A.; Ghosh, Tushar K.; Tompson, Jr., Robert V.

A chemical and biological agent sensor includes an electrostatic thin film supported by a substrate. The film includes an electrostatic charged surface to attract predetermined biological and chemical agents of interest. A charge collector associated with said electrostatic thin film collects charge associated with surface defects in the electrostatic film induced by the predetermined biological and chemical agents of interest. A preferred sensing system includes a charge based deep level transient spectroscopy system to read out charges from the film and match responses to data sets regarding the agents of interest. A method for sensing biological and chemical agents includesmore » providing a thin sensing film having a predetermined electrostatic charge. The film is exposed to an environment suspected of containing the biological and chemical agents. Quantum surface effects on the film are measured. Biological and/or chemical agents can be detected, identified and quantified based on the measured quantum surface effects.« less

Bioinspired Infrared Sensing Materials and Systems.

PubMed

Shen, Qingchen; Luo, Zhen; Ma, Shuai; Tao, Peng; Song, Chengyi; Wu, Jianbo; Shang, Wen; Deng, Tao

2018-05-11

Bioinspired engineering offers a promising alternative approach in accelerating the development of many man-made systems. Next-generation infrared (IR) sensing systems can also benefit from such nature-inspired approach. The inherent compact and uncooled operation of biological IR sensing systems provides ample inspiration for the engineering of portable and high-performance artificial IR sensing systems. This review overviews the current understanding of the biological IR sensing systems, most of which are thermal-based IR sensors that rely on either bolometer-like or photomechanic sensing mechanism. The existing efforts inspired by the biological IR sensing systems and possible future bioinspired approaches in the development of new IR sensing systems are also discussed in the review. Besides these biological IR sensing systems, other biological systems that do not have IR sensing capabilities but can help advance the development of engineered IR sensing systems are also discussed, and the related engineering efforts are overviewed as well. Further efforts in understanding the biological IR sensing systems, the learning from the integration of multifunction in biological systems, and the reduction of barriers to maximize the multidiscipline collaborations are needed to move this research field forward. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Controllability and observability of Boolean networks arising from biology

NASA Astrophysics Data System (ADS)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

Knowledge-making distinctions in synthetic biology.

PubMed

O'Malley, Maureen A; Powell, Alexander; Davies, Jonathan F; Calvert, Jane

2008-01-01

Synthetic biology is an increasingly high-profile area of research that can be understood as encompassing three broad approaches towards the synthesis of living systems: DNA-based device construction, genome-driven cell engineering and protocell creation. Each approach is characterized by different aims, methods and constructs, in addition to a range of positions on intellectual property and regulatory regimes. We identify subtle but important differences between the schools in relation to their treatments of genetic determinism, cellular context and complexity. These distinctions tie into two broader issues that define synthetic biology: the relationships between biology and engineering, and between synthesis and analysis. These themes also illuminate synthetic biology's connections to genetic and other forms of biological engineering, as well as to systems biology. We suggest that all these knowledge-making distinctions in synthetic biology raise fundamental questions about the nature of biological investigation and its relationship to the construction of biological components and systems. (c) 2007 Wiley Periodicals, Inc.

Apoptosis and Self-Destruct: A Contribution to Autonomic Agents?

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2004-01-01

Autonomic Computing (AC), a self-managing systems initiative based on the biological metaphor of the autonomic nervous system, is increasingly gaining momentum as the way forward in designing reliable systems. Agent technologies have been identified as a key enabler for engineering autonomicity in systems, both in terms of retrofitting autonomicity into legacy systems and designing new systems. The AC initiative provides an opportunity to consider other biological systems and principles in seeking new design strategies. This paper reports on one such investigation; utilizing the apoptosis metaphor of biological systems to provide a dynamic health indicator signal between autonomic agents.

SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.

PubMed

Zi, Zhike; Klipp, Edda

2006-11-01

The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.

Plant MetGenMAP: an integrative analysis system for plant systems biology

USDA-ARS?s Scientific Manuscript database

We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. P...

Applications of cell-free protein synthesis in synthetic biology: Interfacing bio-machinery with synthetic environments.

PubMed

Lee, Kyung-Ho; Kim, Dong-Myung

2013-11-01

Synthetic biology is built on the synthesis, engineering, and assembly of biological parts. Proteins are the first components considered for the construction of systems with designed biological functions because proteins carry out most of the biological functions and chemical reactions inside cells. Protein synthesis is considered to comprise the most basic levels of the hierarchical structure of synthetic biology. Cell-free protein synthesis has emerged as a powerful technology that can potentially transform the concept of bioprocesses. With the ability to harness the synthetic power of biology without many of the constraints of cell-based systems, cell-free protein synthesis enables the rapid creation of protein molecules from diverse sources of genetic information. Cell-free protein synthesis is virtually free from the intrinsic constraints of cell-based methods and offers greater flexibility in system design and manipulability of biological synthetic machinery. Among its potential applications, cell-free protein synthesis can be combined with various man-made devices for rapid functional analysis of genomic sequences. This review covers recent efforts to integrate cell-free protein synthesis with various reaction devices and analytical platforms. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advancing metabolic engineering through systems biology of industrial microorganisms.

PubMed

Dai, Zongjie; Nielsen, Jens

2015-12-01

Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further. Copyright © 2015 Elsevier Ltd. All rights reserved.

Systems Biology-Based Investigation of Host-Plasmodium Interactions.

PubMed

Smith, Maren L; Styczynski, Mark P

2018-05-18

Malaria is a serious, complex disease caused by parasites of the genus Plasmodium. Plasmodium parasites affect multiple tissues as they evade immune responses, replicate, sexually reproduce, and transmit between vertebrate and invertebrate hosts. The explosion of omics technologies has enabled large-scale collection of Plasmodium infection data, revealing systems-scale patterns, mechanisms of pathogenesis, and the ways that host and pathogen affect each other. Here, we provide an overview of recent efforts using systems biology approaches to study host-Plasmodium interactions and the biological themes that have emerged from these efforts. We discuss some of the challenges in using systems biology for this goal, key research efforts needed to address those issues, and promising future malaria applications of systems biology. Copyright © 2018 Elsevier Ltd. All rights reserved.

The NASA Space Radiobiology Risk Assessment Project

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; Huff, Janice; Ponomarev, Artem; Patel, Zarana; Kim, Myung-Hee

The current first phase (2006-2011) has the three major goals of: 1) optimizing the conventional cancer risk models currently used based on the double-detriment life-table and radiation quality functions; 2) the integration of biophysical models of acute radiation syndromes; and 3) the development of new systems radiation biology models of cancer processes. The first-phase also includes continued uncertainty assessment of space radiation environmental models and transport codes, and relative biological effectiveness factors (RBE) based on flight data and NSRL results, respectively. The second phase of the (2012-2016) will: 1) develop biophysical models of central nervous system risks (CNS); 2) achieve comphrensive systems biology models of cancer processes using data from proton and heavy ion studies performed at NSRL; and 3) begin to identify computational models of biological countermeasures. Goals for the third phase (2017-2021) include: 1) the development of a systems biology model of cancer risks for operational use at NASA; 2) development of models of degenerative risks, 2) quantitative models of counter-measure impacts on cancer risks; and 3) indiviudal based risk assessments. Finally, we will support a decision point to continue NSRL research in support of NASA's exploration goals beyond 2021, and create an archival of NSRL research results for continued analysis. Details on near term goals, plans for a WEB based data resource of NSRL results, and a space radiation Wikepedia are described.

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

Illustrations of mathematical modeling in biology: epigenetics, meiosis, and an outlook.

PubMed

Richards, D; Berry, S; Howard, M

2012-01-01

In the past few years, mathematical modeling approaches in biology have begun to fulfill their promise by assisting in the dissection of complex biological systems. Here, we review two recent examples of predictive mathematical modeling in plant biology. The first involves the quantitative epigenetic silencing of the floral repressor gene FLC in Arabidopsis, mediated by a Polycomb-based system. The second involves the spatiotemporal dynamics of telomere bouquet formation in wheat-rye meiosis. Although both the biology and the modeling framework of the two systems are different, both exemplify how mathematical modeling can help to accelerate discovery of the underlying mechanisms in complex biological systems. In both cases, the models that developed were relatively minimal, including only essential features, but both nevertheless yielded fundamental insights. We also briefly review the current state of mathematical modeling in biology, difficulties inherent in its application, and its potential future development.

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

DOE PAGES

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting; ...

2018-03-28

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

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

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Ueno, Kazuko; Miyano, Satoru

2009-04-27

Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC) fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe) as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules - Rule I and Rule II - to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in 1986. Our simulation results suggest that: Rule I that cannot be applied with qualitative based model checking, is more reasonable than Rule II owing to the high coverage of predicted fate patterns (except for the genotype of lin-15ko; lin-12ko double mutants). More insights are also suggested. The quantitative simulation-based model checking approach is a useful means to provide us valuable biological insights and better understandings of biological systems and observation data that may be hard to capture with the qualitative one.

Animal protein production modules in biological life support systems: Novel combined aquaculture techniques based on the closed equilibrated biological aquatic system (C.E.B.A.S.)

NASA Astrophysics Data System (ADS)

Blüm, V.; Andriske, M.; Kreuzberg, K.; Schreibman, M. P.

Based on the experiences made with the Closed Equilibrated Biological Aquatic System (C.E.B.A.S.) which was primarily deveoloped for long-term and multi-generation experiments with aquatic animals and plants in a space station highly effective fresh water recycling modules were elaborated utilizing a combination of ammonia oxidizing bacteria filters and higher plants. These exhibit a high effectivity to eliminate phosphate and anorganic nitrogen compounds and arc. in addidition. able to contribute to the oxygen supply of the aquatic animals. The C.E.B.A.S. filter system is able to keep a closed artificial aquatic ecosystem containing teleost fishes and water snails biologically stable for several month and to eliminate waste products deriving from degraded dead fishes without a decrease of the oxygen concentration down to less than 3.5 mg/l at 25 °C. More advanced C.E.B.A.S. filter systems, the BIOCURE filters, were also developed for utilization in semiintensive and intensive aquaculture systems for fishes. In fact such combined animal-plant aquaculture systems represent highly effective productions sites for human food if proper plant and fish species are selected The present papers elucidates ways to novel aquaculture systems in which herbivorous fishes are raised by feeding them with plant biomass produced in the BIOCURE filters and presents the scheme of a modification which utilizes a plant species suitable also for human nutrition. Special attention is paid to the benefits of closed aquaculture system modules which may be integrated into bioregenerative life support systems of a higher complexity for, e. g.. lunar or planetary bases including some psychologiccal aspects of the introduction of animal protein production into plant-based life support systems. Moreover, the basic reproductive biological problems of aquatic animal breeding under reduced gravity are explained leading to a disposition of essential research programs in this context.

Ultra-Structure database design methodology for managing systems biology data and analyses

PubMed Central

Maier, Christopher W; Long, Jeffrey G; Hemminger, Bradley M; Giddings, Morgan C

2009-01-01

Background Modern, high-throughput biological experiments generate copious, heterogeneous, interconnected data sets. Research is dynamic, with frequently changing protocols, techniques, instruments, and file formats. Because of these factors, systems designed to manage and integrate modern biological data sets often end up as large, unwieldy databases that become difficult to maintain or evolve. The novel rule-based approach of the Ultra-Structure design methodology presents a potential solution to this problem. By representing both data and processes as formal rules within a database, an Ultra-Structure system constitutes a flexible framework that enables users to explicitly store domain knowledge in both a machine- and human-readable form. End users themselves can change the system's capabilities without programmer intervention, simply by altering database contents; no computer code or schemas need be modified. This provides flexibility in adapting to change, and allows integration of disparate, heterogenous data sets within a small core set of database tables, facilitating joint analysis and visualization without becoming unwieldy. Here, we examine the application of Ultra-Structure to our ongoing research program for the integration of large proteomic and genomic data sets (proteogenomic mapping). Results We transitioned our proteogenomic mapping information system from a traditional entity-relationship design to one based on Ultra-Structure. Our system integrates tandem mass spectrum data, genomic annotation sets, and spectrum/peptide mappings, all within a small, general framework implemented within a standard relational database system. General software procedures driven by user-modifiable rules can perform tasks such as logical deduction and location-based computations. The system is not tied specifically to proteogenomic research, but is rather designed to accommodate virtually any kind of biological research. Conclusion We find Ultra-Structure offers substantial benefits for biological information systems, the largest being the integration of diverse information sources into a common framework. This facilitates systems biology research by integrating data from disparate high-throughput techniques. It also enables us to readily incorporate new data types, sources, and domain knowledge with no change to the database structure or associated computer code. Ultra-Structure may be a significant step towards solving the hard problem of data management and integration in the systems biology era. PMID:19691849

Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics

NASA Astrophysics Data System (ADS)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

This chapter reviews quantum(-like) information biology (QIB). Here biology is treated widely as even covering cognition and its derivatives: psychology and decision making, sociology, and behavioral economics and finances. QIB provides an integrative description of information processing by bio-systems at all scales of life: from proteins and cells to cognition, ecological and social systems. Mathematically QIB is based on the theory of adaptive quantum systems (which covers also open quantum systems). Ideologically QIB is based on the quantum-like (QL) paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all bio-scales. QIB re ects the two fundamental principles: a) adaptivity; and, b) openness (bio-systems are fundamentally open). In addition, quantum adaptive dynamics provides the most generally possible mathematical representation of these principles.

Non-equilibrium assembly of microtubules: from molecules to autonomous chemical robots.

PubMed

Hess, H; Ross, Jennifer L

2017-09-18

Biological systems have evolved to harness non-equilibrium processes from the molecular to the macro scale. It is currently a grand challenge of chemistry, materials science, and engineering to understand and mimic biological systems that have the ability to autonomously sense stimuli, process these inputs, and respond by performing mechanical work. New chemical systems are responding to the challenge and form the basis for future responsive, adaptive, and active materials. In this article, we describe a particular biochemical-biomechanical network based on the microtubule cytoskeletal filament - itself a non-equilibrium chemical system. We trace the non-equilibrium aspects of the system from molecules to networks and describe how the cell uses this system to perform active work in essential processes. Finally, we discuss how microtubule-based engineered systems can serve as testbeds for autonomous chemical robots composed of biological and synthetic components.

Multi-level and hybrid modelling approaches for systems biology.

PubMed

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Nucleic Acid-Based Nanodevices in Biological Imaging.

PubMed

Chakraborty, Kasturi; Veetil, Aneesh T; Jaffrey, Samie R; Krishnan, Yamuna

2016-06-02

The nanoscale engineering of nucleic acids has led to exciting molecular technologies for high-end biological imaging. The predictable base pairing, high programmability, and superior new chemical and biological methods used to access nucleic acids with diverse lengths and in high purity, coupled with computational tools for their design, have allowed the creation of a stunning diversity of nucleic acid-based nanodevices. Given their biological origin, such synthetic devices have a tremendous capacity to interface with the biological world, and this capacity lies at the heart of several nucleic acid-based technologies that are finding applications in biological systems. We discuss these diverse applications and emphasize the advantage, in terms of physicochemical properties, that the nucleic acid scaffold brings to these contexts. As our ability to engineer this versatile scaffold increases, its applications in structural, cellular, and organismal biology are clearly poised to massively expand.

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

Reputation-based collaborative network biology.

PubMed

Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Fields, R Brett; Hayes, William; Hoeng, Julia; Park, Jennifer S; Peitsch, Manuel C

2015-01-01

A pilot reputation-based collaborative network biology platform, Bionet, was developed for use in the sbv IMPROVER Network Verification Challenge to verify and enhance previously developed networks describing key aspects of lung biology. Bionet was successful in capturing a more comprehensive view of the biology associated with each network using the collective intelligence and knowledge of the crowd. One key learning point from the pilot was that using a standardized biological knowledge representation language such as BEL is critical to the success of a collaborative network biology platform. Overall, Bionet demonstrated that this approach to collaborative network biology is highly viable. Improving this platform for de novo creation of biological networks and network curation with the suggested enhancements for scalability will serve both academic and industry systems biology communities.

Cancer systems biology: signal processing for cancer research

PubMed Central

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

2011-01-01

In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

Diagnostic of students' misconceptions using the Biological Concepts Instrument (BCI): A method for conducting an educational needs assessment

PubMed Central

Champagne Queloz, Annie; Klymkowsky, Michael W.; Stern, Elsbeth; Hafen, Ernst; Köhler, Katja

2017-01-01

Concept inventories, constructed based on an analysis of students’ thinking and their explanations of scientific situations, serve as diagnostics for identifying misconceptions and logical inconsistencies and provide data that can help direct curricular reforms. In the current project, we distributed the Biological Concepts Instrument (BCI) to 17-18-year-old students attending the highest track of the Swiss school system (Gymnasium). Students’ performances on many questions related to evolution, genetics, molecular properties and functions were diverse. Important common misunderstandings were identified in the areas of evolutionary processes, molecular properties and an appreciation of stochastic processes in biological systems. Our observations provide further evidence that the BCI is efficient in identifying specific areas where targeted instruction is required. Based on these observations we have initiated changes at several levels to reconsider how biological systems are presented to university biology studies with the goal of improving student’s foundational understanding. PMID:28493960

Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

PubMed

Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-03-01

"A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Membrane materials for storing biological samples intended for comparative nanotoxicological testing

NASA Astrophysics Data System (ADS)

Metelkin, A.; Kuznetsov, D.; Kolesnikov, E.; Chuprunov, K.; Kondakov, S.; Osipov, A.; Samsonova, J.

2015-11-01

The study is aimed at identifying the samples of most promising membrane materials for storing dry specimens of biological fluids (Dried Blood Spots, DBS technology). Existing sampling systems using cellulose fiber filter paper have a number of drawbacks such as uneven distribution of the sample spot, dependence of the spot spreading area on the individual biosample properties, incomplete washing-off of the sample due to partially inconvertible sorption of blood components on cellulose fibers, etc. Samples of membrane materials based on cellulose, polymers and glass fiber with applied biosamples were studied using methods of scanning electron microscopy, FT-IR spectroscopy and surface-wetting measurement. It was discovered that cellulose-based membrane materials sorb components of biological fluids inside their structure, while membranes based on glass fiber display almost no interaction with the samples and biological fluid components dry to films in the membrane pores between the structural fibers. This characteristic, together with the fact that membrane materials based on glass fiber possess sufficient strength, high wetting properties and good storage capacity, attests them as promising material for dry samples of biological fluids storage systems.

A research project-based and self-determined teaching system of molecular biology techniques for undergraduates.

PubMed

Zhang, Shuping

2008-05-01

Molecular biology techniques play a very important role in understanding the biological activity. Students who major in biology should know not only how to perform experiments, but also the reasons for performing them. Having the concept of conducting research by integrating various techniques is especially important. This paper introduces a research project-based and self-determined teaching system of molecular biology techniques for undergraduates. Its aim is to create an environment mimicking real research programs and to help students build up confidence in their research skills. The students are allowed to explore a set of commonly used molecular biology techniques to solve some fundamental problems about genes on their own. They find a gene of interest, write a mini-proposal, and give an oral presentation. This course provides students a foundation before entering the research laboratory and allows them to adapt easily to real research programs. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

Implementation of Multi-Agent Object Attention System Based on Biologically Inspired Attractor Selection

NASA Astrophysics Data System (ADS)

Hashimoto, Ryoji; Matsumura, Tomoya; Nozato, Yoshihiro; Watanabe, Kenji; Onoye, Takao

A multi-agent object attention system is proposed, which is based on biologically inspired attractor selection model. Object attention is facilitated by using a video sequence and a depth map obtained through a compound-eye image sensor TOMBO. Robustness of the multi-agent system over environmental changes is enhanced by utilizing the biological model of adaptive response by attractor selection. To implement the proposed system, an efficient VLSI architecture is employed with reducing enormous computational costs and memory accesses required for depth map processing and multi-agent attractor selection process. According to the FPGA implementation result of the proposed object attention system, which is accomplished by using 7,063 slices, 640×512 pixel input images can be processed in real-time with three agents at a rate of 9fps in 48MHz operation.

How Many Kingdoms? Current Views of Biological Classification.

ERIC Educational Resources Information Center

Margulis, Lynn

1981-01-01

Argues for the acceptance and use of a five-kingdom classification system for biology comprised of monera, protoctista, fungi, animals, and plants. Justifies the new system based upon the difference between prokaryotes and eukaryotes. Outlines each kingdom and describes its members. (DC)

Endobiogeny: a global approach to systems biology (part 1 of 2).

PubMed

Lapraz, Jean-Claude; Hedayat, Kamyar M

2013-01-01

Endobiogeny is a global systems approach to human biology that may offer an advancement in clinical medicine based in scientific principles of rigor and experimentation and the humanistic principles of individualization of care and alleviation of suffering with minimization of harm. Endobiogeny is neither a movement away from modern science nor an uncritical embracing of pre-rational methods of inquiry but a synthesis of quantitative and qualitative relationships reflected in a systems-approach to life and based on new mathematical paradigms of pattern recognition.

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

PubMed

Bosl, William J

2007-02-15

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer.

Materiomics: biological protein materials, from nano to macro.

PubMed

Cranford, Steven; Buehler, Markus J

2010-11-12

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics - discovering Nature's complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature's materials have been hindered by our lack of fundamental understanding of these materials' intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure-property-process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering.

Materiomics: biological protein materials, from nano to macro

PubMed Central

Cranford, Steven; Buehler, Markus J

2010-01-01

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics – discovering Nature’s complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature’s materials have been hindered by our lack of fundamental understanding of these materials’ intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure–property–process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering. PMID:24198478

Emerging systems biology approaches in nanotoxicology: Towards a mechanism-based understanding of nanomaterial hazard and risk

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

Costa, Pedro M.; Fadeel, Bengt, E-mail: Bengt.Fade

Engineered nanomaterials are being developed for a variety of technological applications. However, the increasing use of nanomaterials in society has led to concerns about their potential adverse effects on human health and the environment. During the first decade of nanotoxicological research, the realization has emerged that effective risk assessment of the multitudes of new nanomaterials would benefit from a comprehensive understanding of their toxicological mechanisms, which is difficult to achieve with traditional, low-throughput, single end-point oriented approaches. Therefore, systems biology approaches are being progressively applied within the nano(eco)toxicological sciences. This novel paradigm implies that the study of biological systems shouldmore » be integrative resulting in quantitative and predictive models of nanomaterial behaviour in a biological system. To this end, global ‘omics’ approaches with which to assess changes in genes, proteins, metabolites, etc. are deployed allowing for computational modelling of the biological effects of nanomaterials. Here, we highlight omics and systems biology studies in nanotoxicology, aiming towards the implementation of a systems nanotoxicology and mechanism-based risk assessment of nanomaterials. - Highlights: • Systems nanotoxicology is a multi-disciplinary approach to quantitative modelling. • Transcriptomics, proteomics and metabolomics remain the most common methods. • Global “omics” techniques should be coupled to computational modelling approaches. • The discovery of nano-specific toxicity pathways and biomarkers is a prioritized goal. • Overall, experimental nanosafety research must endeavour reproducibility and relevance.« less

The National Biological Information Infrastructure: Coming of age

USGS Publications Warehouse

Cotter, G.; Frame, M.; Sepic, R.; Zolly, L.

2000-01-01

Coordinated by the US Geological Survey, the National Biological Information Infrastructure (NBII) is a Web-based system that provides increased access to data and information on the nation's biological resources. The NBII can be viewed from a variety of perspectives. This article - an individual case study and not a broad survey with extensive references to the literature - addresses the structure of the NBII related to thematic sections, infrastructure sections and place-based sections, and other topics such as the Integrated Taxonomic Information System (one of our more innovative tools) and the development of our controlled vocabulary.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

PubMed

Nehaniv, Chrystopher L; Rhodes, John; Egri-Nagy, Attila; Dini, Paolo; Morris, Eric Rothstein; Horváth, Gábor; Karimi, Fariba; Schreckling, Daniel; Schilstra, Maria J

2015-07-28

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

[Biotechnological functional systems].

PubMed

Bokser, O Ia

1999-01-01

Based on the theory of functional systems and a concept of the quantum system of behavior, studies of the quantumsystems were conducted. Their structure, the interaction of biological and technical sections were analyzed. Mathematical, biophysical, and experimental models were designed. The paper shows that biotechnical quantumsystems are involved in the formation of biological feedback. A system with imperative feedback from the programmed and introduced current results of efforts has been developed and put into practice for the self-regulation of muscle tension. Training by using this biological feedback system causes a stable increase in the perception rate of proprioceptive stimulus in examinees (operates, sportsmen, neurological patients).

Dietary antioxidant synergy in chemical and biological systems.

PubMed

Wang, Sunan; Zhu, Fan

2017-07-24

Antioxidant (AOX) synergies have been much reported in chemical ("test-tube" based assays focusing on pure chemicals), biological (tissue culture, animal and clinical models), and food systems during the past decade. Tentative synergies differ from each other due to the composition of AOX and the quantification methods. Regeneration mechanism responsible for synergy in chemical systems has been discussed. Solvent effects could contribute to the artifacts of synergy observed in the chemical models. Synergy in chemical models may hardly be relevant to biological systems that have been much less studied. Apparent discrepancies exist in understanding the molecular mechanisms in both chemical and biological systems. This review discusses diverse variables associated with AOX synergy and molecular scenarios for explanation. Future research to better utilize the synergy is suggested.

Eugene--a domain specific language for specifying and constraining synthetic biological parts, devices, and systems.

PubMed

Bilitchenko, Lesia; Liu, Adam; Cheung, Sherine; Weeding, Emma; Xia, Bing; Leguia, Mariana; Anderson, J Christopher; Densmore, Douglas

2011-04-29

Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. We illustrate Eugene's capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugene's ability to create combinatorial design spaces and prune these spaces for simulation or physical assembly. Eugene creates functional designs quickly and cost-effectively. Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired abstraction hierarchy in synthetic biology. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and physical device assembly.

The quest for a new modelling framework in mathematical biology. Comment on "On the interplay between mathematics and biology: Hallmarks towards a new systems biology" by N. Bellomo et al.

NASA Astrophysics Data System (ADS)

Eftimie, Raluca

2015-03-01

One of the main unsolved problems of modern physics is finding a "theory of everything" - a theory that can explain, with the help of mathematics, all physical aspects of the universe. While the laws of physics could explain some aspects of the biology of living systems (e.g., the phenomenological interpretation of movement of cells and animals), there are other aspects specific to biology that cannot be captured by physics models. For example, it is generally accepted that the evolution of a cell-based system is influenced by the activation state of cells (e.g., only activated and functional immune cells can fight diseases); on the other hand, the evolution of an animal-based system can be influenced by the psychological state (e.g., distress) of animals. Therefore, the last 10-20 years have seen also a quest for a "theory of everything"-approach extended to biology, with researchers trying to propose mathematical modelling frameworks that can explain various biological phenomena ranging from ecology to developmental biology and medicine [1,2,6]. The basic idea behind this approach can be found in a few reviews on ecology and cell biology [6,7,9-11], where researchers suggested that due to the parallel between the micro-scale dynamics and the emerging macro-scale phenomena in both cell biology and in ecology, many mathematical methods used for ecological processes could be adapted to cancer modelling [7,9] or to modelling in immunology [11]. However, this approach generally involved the use of different models to describe different biological aspects (e.g., models for cell and animal movement, models for competition between cells or animals, etc.).

How do precision medicine and system biology response to human body's complex adaptability?

PubMed

Yuan, Bing

2016-12-01

In the field of life sciences, although system biology and "precision medicine" introduce some complex scientifific methods and techniques, it is still based on the "analysis-reconstruction" of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identifification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the "analysis-reconstruction" concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will fifind the adaptability of complex system is not the obstacle that increases the diffificulty of problem solving. It is the "exceptional", "right-hand man" that helping us to deal with the complexity of life more effectively.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach

PubMed Central

Laurent, Georges St.; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J.L.; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R.R.; Nicolas, Estelle; McCaffrey, Timothy A.; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-01-01

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlincRNAs genes likely function in cis to activate nearby genes. This effect while most pronounced in closely spaced vlincRNA–gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlincRNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. PMID:27001520

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

PubMed

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

Implementation of biological tissue Mueller matrix for polarization-sensitive optical coherence tomography based on LabVIEW

NASA Astrophysics Data System (ADS)

Lin, Yongping; Zhang, Xiyang; He, Youwu; Cai, Jianyong; Li, Hui

2018-02-01

The Jones matrix and the Mueller matrix are main tools to study polarization devices. The Mueller matrix can also be used for biological tissue research to get complete tissue properties, while the commercial optical coherence tomography system does not give relevant analysis function. Based on the LabVIEW, a near real time display method of Mueller matrix image of biological tissue is developed and it gives the corresponding phase retardant image simultaneously. A quarter-wave plate was placed at 45 in the sample arm. Experimental results of the two orthogonal channels show that the phase retardance based on incident light vector fixed mode and the Mueller matrix based on incident light vector dynamic mode can provide an effective analysis method of the existing system.

Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

PubMed

Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J

2015-08-21

In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

Systems biology of eukaryotic superorganisms and the holobiont concept.

PubMed

Kutschera, Ulrich

2018-06-14

The founders of modern biology (Jean Lamarck, Charles Darwin, August Weismann etc.) were organismic life scientists who attempted to understand the morphology and evolution of living beings as a whole (i.e., the phenotype). However, with the emergence of the study of animal and plant physiology in the nineteenth century, this "holistic view" of the living world changed and was ultimately replaced by a reductionistic perspective. Here, I summarize the history of systems biology, i.e., the modern approach to understand living beings as integrative organisms, from genotype to phenotype. It is documented that the physiologists Claude Bernard and Julius Sachs, who studied humans and plants, respectively, were early pioneers of this discipline, which was formally founded 50 years ago. In 1968, two influential monographs, authored by Ludwig von Bertalanffy and Mihajlo D. Mesarović, were published, wherein a "systems theory of biology" was outlined. Definitions of systems biology are presented with reference to metabolic or cell signaling networks, analyzed via genomics, proteomics, and other methods, combined with computer simulations/mathematical modeling. Then, key insights of this discipline with respect to epiphytic microbes (Methylobacterium sp.) and simple bacteria (Mycoplasma sp.) are described. The principles of homeostasis, molecular systems energetics, gnotobiology, and holobionts (i.e., complexities of host-microbiota interactions) are outlined, and the significance of systems biology for evolutionary theories is addressed. Based on the microbe-Homo sapiens-symbiosis, it is concluded that human biology and health should be interpreted in light of a view of the biomedical sciences that is based on the holobiont concept.

The Dominance Behavioral System and Psychopathology: Evidence from Self-Report, Observational, and Biological Studies

ERIC Educational Resources Information Center

Johnson, Sheri L.; Leedom, Liane J.; Muhtadie, Luma

2012-01-01

The dominance behavioral system (DBS) can be conceptualized as a biologically based system that guides dominance motivation, dominant and subordinate behavior, and responsivity to perceptions of power and subordination. A growing body of research suggests that problems with the DBS are evident across a broad range of psychopathologies. We begin by…

An overview: recycling nutrients from crop residues for space applications.

PubMed

Strayer, R F; Atkinson, C F

1997-01-01

Without some form of regenerative life support system, long duration space habitation or travel will be limited severely by the prohibitive costs of resupplying air, water, and food from Earth. Components under consideration for inclusion in a regenerative life support system are based on either physicochemical or biological processes. Physicochemical systems would use filtration and elemental phase changes to convert waste materials into usable products, while biological systems would use higher plants and bioreactors to supply crew needs. Neither a purely biological nor strictly a physicochemical approach can supply all crew needs, thus, the best each approach can offer will be combined into a hybrid regenerative life support system. Researchers at Kennedy Space Center (KSC) Advanced Life Support Breadboard Project have taken the lead on bioregenerative aspects of space life support. The major focus has been on utilization of higher plants for production of food, oxygen, and clean water. However, a key to any regenerative life support system is recycling and recovery of resources (wastes). In keeping with the emphasis at KSC on bioregenerative systems and with the focus on plants, this paper focuses on research with biologically-based options for resource recovery from inedible crop residues.

An overview: recycling nutrients from crop residues for space applications

NASA Technical Reports Server (NTRS)

Strayer, R. F.; Atkinson, C. F.

1997-01-01

Without some form of regenerative life support system, long duration space habitation or travel will be limited severely by the prohibitive costs of resupplying air, water, and food from Earth. Components under consideration for inclusion in a regenerative life support system are based on either physicochemical or biological processes. Physicochemical systems would use filtration and elemental phase changes to convert waste materials into usable products, while biological systems would use higher plants and bioreactors to supply crew needs. Neither a purely biological nor strictly a physicochemical approach can supply all crew needs, thus, the best each approach can offer will be combined into a hybrid regenerative life support system. Researchers at Kennedy Space Center (KSC) Advanced Life Support Breadboard Project have taken the lead on bioregenerative aspects of space life support. The major focus has been on utilization of higher plants for production of food, oxygen, and clean water. However, a key to any regenerative life support system is recycling and recovery of resources (wastes). In keeping with the emphasis at KSC on bioregenerative systems and with the focus on plants, this paper focuses on research with biologically-based options for resource recovery from inedible crop residues.

A Biochemistry and Molecular Biology Experiment and Evaluation System for Biotechnology Specialty Students: An Effective Evaluation System to Improve the Biochemistry and Molecular Biology Experiment Teaching

ERIC Educational Resources Information Center

Li, Suxia; Wu, Haizhen; Zhao, Jian; Ou, Ling; Zhang, Yuanxing

2010-01-01

In an effort to achieve high success in knowledge and technique acquisition as a whole, a biochemistry and molecular biology experiment was established for high-grade biotechnology specialty students after they had studied essential theory and received proper technique training. The experiment was based on cloning and expression of alkaline…

Application of sunlight and lamps for plant irradiation in space bases

NASA Astrophysics Data System (ADS)

Sager, J. C.; Wheeler, R. M.

The radiation sources used for plant growth on a space base must meet the biological requirements for photosynthesis and photomorphogensis. In addition the sources must be energy and volume efficient, while maintaining the required irradiance levels, spectral, spatial and temporal distribution. These requirements are not easily met, but as the biological and mission requirements are better defined, then specific facility designs can begin to accommodate both the biological requirements and the physical limitations of a space based plant growth system.

Application of sunlight and lamps for plant irradiation in space bases

NASA Technical Reports Server (NTRS)

Sager, J. C.; Wheeler, R. M.

1992-01-01

The radiation sources used for plant growth on a space base must meet the biological requirements for photosynthesis and photomorphogenesis. In addition, the sources must be energy and volume efficient, while maintaining the required irradiance levels, spectral, spatial and temporal distribution. These requirements are not easily met, but as the biological and mission requirements are better defined, then specific facility designs can begin to accommodate both the biological requirements and the physical limitations of a space-based plant growth system.

SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.

PubMed

Zi, Zhike

2011-04-01

Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

Next-Gen Gene Synthesis Enables Large-Scale Engineering in Biological Systems: Recent advances in synthetic biology are making this field more promising than ever.

PubMed

Leake, Devin

2015-01-01

As scientists make strides toward the goal of developing a form of biological engineering that's as predictive and reliable as chemical engineering is for chemistry, one technology component has become absolutely critical: gene synthesis. Gene synthesis is the process of building stretches of deoxyribonucleic acid (DNA) to order--some stretches based on DNA that exists already in nature, some based on novel designs intended to accomplish new functions. This process is the foundation of synthetic biology, which is rapidly becoming the engineering counterpart to biology.

Embodiment and Performance

ERIC Educational Resources Information Center

Bessell, Jacquelyn; Riddell, Patricia

2016-01-01

Evidence suggests that some cognitive processes are based on sensorimotor systems in the brain (embodied cognition). The premise of this is that "Biological brains are first and foremost the control systems for biological bodies". It has therefore been suggested that both online cognition (processing as we move through the world) and…

Systems Biology & Mode of Action Based Risk Assessment

EPA Science Inventory

The application of systems biology for risk assessment of environmental chemicals is a national extension of its use in pharmaceutical research. The basis for this is the concept of a key event network that builds on existing mode of action frameworks for risk assessment. The a...

Profiling Bioactivity of the ToxCast Chemical Library Using BioMAP Primary Human Cell Systems

EPA Science Inventory

The complexity of human biology has made prediction of health effects as a consequence of exposure to environmental chemicals especially challenging. Complex cell systems, such as the Biologically Multiplexed Activity Profiling (BioMAP) primary, human, cell-based disease models, ...

On the optimal design of molecular sensing interfaces with lipid bilayer assemblies - A knowledge based approach

NASA Astrophysics Data System (ADS)

Siontorou, Christina G.

2012-12-01

Biosensors are analytic devices that incorporate a biochemical recognition system (biological, biologicalderived or biomimic: enzyme, antibody, DNA, receptor, etc.) in close contact with a physicochemical transducer (electrochemical, optical, piezoelectric, conductimetric, etc.) that converts the biochemical information, produced by the specific biological recognition reaction (analyte-biomolecule binding), into a chemical or physical output signal, related to the concentration of the analyte in the measuring sample. The biosensing concept is based on natural chemoreception mechanisms, which are feasible over/within/by means of a biological membrane, i.e., a structured lipid bilayer, incorporating or attached to proteinaceous moieties that regulate molecular recognition events which trigger ion flux changes (facilitated or passive) through the bilayer. The creation of functional structures that are similar to natural signal transduction systems, correlating and interrelating compatibly and successfully the physicochemical transducer with the lipid film that is self-assembled on its surface while embedding the reconstituted biological recognition system, and at the same time manage to satisfy the basic conditions for measuring device development (simplicity, easy handling, ease of fabrication) is far from trivial. The aim of the present work is to present a methodological framework for designing such molecular sensing interfaces, functioning within a knowledge-based system built on an ontological platform for supplying sub-systems options, compatibilities, and optimization parameters.

[Concepts of rational taxonomy].

PubMed

Pavlinov, I Ia

2011-01-01

The problems are discussed related to development of concepts of rational taxonomy and rational classifications (taxonomic systems) in biology. Rational taxonomy is based on the assumption that the key characteristic of rationality is deductive inference of certain partial judgments about reality under study from other judgments taken as more general and a priory true. Respectively, two forms of rationality are discriminated--ontological and epistemological ones. The former implies inference of classifications properties from general (essential) properties of the reality being investigated. The latter implies inference of the partial rules of judgments about classifications from more general (formal) rules. The following principal concepts of ontologically rational biological taxonomy are considered: "crystallographic" approach, inference of the orderliness of organismal diversity from general laws of Nature, inference of the above orderliness from the orderliness of ontogenetic development programs, based on the concept of natural kind and Cassirer's series theory, based on the systemic concept, based on the idea of periodic systems. Various concepts of ontologically rational taxonomy can be generalized by an idea of the causal taxonomy, according to which any biologically sound classification is founded on a contentwise model of biological diversity that includes explicit indication of general causes responsible for that diversity. It is asserted that each category of general causation and respective background model may serve as a basis for a particular ontologically rational taxonomy as a distinctive research program. Concepts of epistemologically rational taxonomy and classifications (taxonomic systems) can be interpreted in terms of application of certain epistemological criteria of substantiation of scientific status of taxonomy in general and of taxonomic systems in particular. These concepts include: consideration of taxonomy consistency from the standpoint of inductive and hypothetico-deductive argumentation schemes and such fundamental criteria of classifications naturalness as their prognostic capabilities; foundation of a theory of "general taxonomy" as a "general logic", including elements of the axiomatic method. The latter concept constitutes a core of the program of general classiology; it is inconsistent due to absence of anything like "general logic". It is asserted that elaboration of a theory of taxonomy as a biological discipline based on the formal principles of epistemological rationality is not feasible. Instead, it is to be elaborated as ontologically rational one based on biologically sound metatheories about biological diversity causes.

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

Ogura, Toshihiko, E-mail: t-ogura@aist.go.jp

Scanning electron microscopy (SEM) has been widely used to examine biological specimens of bacteria, viruses and proteins. Until now, atmospheric and/or wet biological specimens have been examined using various atmospheric holders or special equipment involving SEM. Unfortunately, they undergo heavy radiation damage by the direct electron beam. In addition, images of unstained biological samples in water yield poor contrast. We recently developed a new analytical technology involving a frequency transmission electric-field (FTE) method based on thermionic SEM. This method is suitable for high-contrast imaging of unstained biological specimens. Our aim was to optimise the method. Here we describe a high-resolutionmore » FTE system based on field-emission SEM; it allows for imaging and nanoscale examination of various biological specimens in water without radiation damage. The spatial resolution is 8 nm, which is higher than 41 nm of the existing FTE system. Our new method can be easily utilised for examination of unstained biological specimens including bacteria, viruses and protein complexes. Furthermore, our high-resolution FTE system can be used for diverse liquid samples across a broad range of scientific fields, e.g. nanoparticles, nanotubes and organic and catalytic materials. - Highlights: • We developed a high-resolution frequency transmission electric-field (FTE) system. • High-resolution FTE system is introduced in the field-emission SEM. • The spatial resolution of high-resolution FTE method is 8 nm. • High-resolution FTE system enables observation of the intact IgM particles in water.« less

Synchronization of metronomes

NASA Astrophysics Data System (ADS)

Pantaleone, James

2002-10-01

Synchronization is a common phenomenon in physical and biological systems. We examine the synchronization of two (and more) metronomes placed on a freely moving base. The small motion of the base couples the pendulums causing synchronization. The synchronization is generally in-phase, with antiphase synchronization occurring only under special conditions. The metronome system provides a mechanical realization of the popular Kuramoto model for synchronization of biological oscillators, and is excellent for classroom demonstrations and an undergraduate physics lab.

Analysing hierarchy in the organization of biological and physical systems.

PubMed

Jagers op Akkerhuis, Gerard A J M

2008-02-01

A structured approach is discussed for analysing hierarchy in the organization of biological and physical systems. The need for a structured approach follows from the observation that many hierarchies in the literature apply conflicting hierarchy rules and include ill-defined systems. As an alternative, we suggest a framework that is based on the following analytical steps: determination of the succession stage of the universe, identification of a specific system as part of the universe, specification of external influences on a system's creation and analysis of a system's internal organization. At the end, the paper discusses practical implications of the proposed method for the analysis of system organization and hierarchy in biology, ecology and physics.

Inference of Gene Regulatory Networks Incorporating Multi-Source Biological Knowledge via a State Space Model with L1 Regularization

PubMed Central

Hasegawa, Takanori; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru; Imoto, Seiya

2014-01-01

Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in the field of systems biology. Currently, there are two main approaches in GRN analysis using time-course observation data, namely an ordinary differential equation (ODE)-based approach and a statistical model-based approach. The ODE-based approach can generate complex dynamics of GRNs according to biologically validated nonlinear models. However, it cannot be applied to ten or more genes to simultaneously estimate system dynamics and regulatory relationships due to the computational difficulties. The statistical model-based approach uses highly abstract models to simply describe biological systems and to infer relationships among several hundreds of genes from the data. However, the high abstraction generates false regulations that are not permitted biologically. Thus, when dealing with several tens of genes of which the relationships are partially known, a method that can infer regulatory relationships based on a model with low abstraction and that can emulate the dynamics of ODE-based models while incorporating prior knowledge is urgently required. To accomplish this, we propose a method for inference of GRNs using a state space representation of a vector auto-regressive (VAR) model with L1 regularization. This method can estimate the dynamic behavior of genes based on linear time-series modeling constructed from an ODE-based model and can infer the regulatory structure among several tens of genes maximizing prediction ability for the observational data. Furthermore, the method is capable of incorporating various types of existing biological knowledge, e.g., drug kinetics and literature-recorded pathways. The effectiveness of the proposed method is shown through a comparison of simulation studies with several previous methods. For an application example, we evaluated mRNA expression profiles over time upon corticosteroid stimulation in rats, thus incorporating corticosteroid kinetics/dynamics, literature-recorded pathways and transcription factor (TF) information. PMID:25162401

Robust Design of Biological Circuits: Evolutionary Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise. PMID:22187523

Robust design of biological circuits: evolutionary systems biology approach.

PubMed

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise.

A Research Project-Based and Self-Determined Teaching System of Molecular Biology Techniques for Undergraduates

ERIC Educational Resources Information Center

Zhang, Shuping

2008-01-01

Molecular biology techniques play a very important role in understanding the biological activity. Students who major in biology should know not only how to perform experiments, but also the reasons for performing them. Having the concept of conducting research by integrating various techniques is especially important. This paper introduces a…

Biological attachment devices: exploring nature's diversity for biomimetics.

PubMed

Gorb, Stanislav N

2008-05-13

Many species of animals and plants are supplied with diverse attachment devices, in which morphology depends on the species biology and the particular function in which the attachment device is involved. Many functional solutions have evolved independently in different lineages of animals and plants. Since the diversity of such biological structures is huge, there is a need for their classification. This paper, based on the original and literature data, proposes ordering of biological attachment systems according to several principles: (i) fundamental physical mechanism, according to which the system operates, (ii) biological function of the attachment device, and (iii) duration of the contact. Finally, we show a biomimetic potential of studies on biological attachment devices.

Coupling biology and oceanography in models.

PubMed

Fennel, W; Neumann, T

2001-08-01

The dynamics of marine ecosystems, i.e. the changes of observable chemical-biological quantities in space and time, are driven by biological and physical processes. Predictions of future developments of marine systems need a theoretical framework, i.e. models, solidly based on research and understanding of the different processes involved. The natural way to describe marine systems theoretically seems to be the embedding of chemical-biological models into circulation models. However, while circulation models are relatively advanced the quantitative theoretical description of chemical-biological processes lags behind. This paper discusses some of the approaches and problems in the development of consistent theories and indicates the beneficial potential of the coupling of marine biology and oceanography in models.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

PubMed

Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi

It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology

PubMed Central

Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi

2017-01-01

It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology. PMID:29267315

No Time To Kill: Entrainment and Accelerating Courseware Development.

ERIC Educational Resources Information Center

Millington, Paula Crnkovich

This paper examines the concept of time in multimedia, World Wide Web-based courseware development. The biological concept of entrainment (the alignment of rhythms within and between systems) to accelerate courseware development is explored. The discussion begins with the foundational concepts of entrainment from biological systems and social…

Biological sample evaluation using a line-scan based SWIR hyperspectral imaging system

USDA-ARS?s Scientific Manuscript database

A new line-scan hyperspectral imaging system was developed to enable short wavelength infrared (SWIR) imagery for biological sample evaluation. Critical sensing components include a SWIR imaging spectrograph and an HgCdTe (MCT) focal plane array detector. To date, agricultural applications of infra...

Biological Networks for Cancer Candidate Biomarkers Discovery

PubMed Central

Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

2016-01-01

Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. PMID:27625573

Modeling and simulation of biological systems using SPICE language

PubMed Central

Lallement, Christophe; Haiech, Jacques

2017-01-01

The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems), an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE). BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language), a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems) have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology). PMID:28787027

The Spring of Systems Biology-Driven Breeding.

PubMed

Lavarenne, Jérémy; Guyomarc'h, Soazig; Sallaud, Christophe; Gantet, Pascal; Lucas, Mikaël

2018-05-12

Genetics and molecular biology have contributed to the development of rationalized plant breeding programs. Recent developments in both high-throughput experimental analyses of biological systems and in silico data processing offer the possibility to address the whole gene regulatory network (GRN) controlling a given trait. GRN models can be applied to identify topological features helping to shortlist potential candidate genes for breeding purposes. Time-series data sets can be used to support dynamic modelling of the network. This will enable a deeper comprehension of network behaviour and the identification of the few elements to be genetically rewired to push the system towards a modified phenotype of interest. This paves the way to design more efficient, systems biology-based breeding strategies. Copyright © 2018 Elsevier Ltd. All rights reserved.

WebBio, a web-based management and analysis system for patient data of biological products in hospital.

PubMed

Lu, Ying-Hao; Kuo, Chen-Chun; Huang, Yaw-Bin

2011-08-01

We selected HTML, PHP and JavaScript as the programming languages to build "WebBio", a web-based system for patient data of biological products and used MySQL as database. WebBio is based on the PHP-MySQL suite and is run by Apache server on Linux machine. WebBio provides the functions of data management, searching function and data analysis for 20 kinds of biological products (plasma expanders, human immunoglobulin and hematological products). There are two particular features in WebBio: (1) pharmacists can rapidly find out whose patients used contaminated products for medication safety, and (2) the statistics charts for a specific product can be automatically generated to reduce pharmacist's work loading. WebBio has successfully turned traditional paper work into web-based data management.

[Research of urban eutrophic water repair by water/sediment biological bases].

PubMed

Zhou, Hui-Hua; Song, Xiao-Guang; Wu, Ge; Xie, Xin-Yuan

2013-10-01

A micro power turbine water aeration system with a water biological base and a sediment biological base was independently developed, aimed at urban water eutrophication. The results showed that the average removal rates of COD, NH+4 -N, TP by the water biological base were 82. 33% , 98. 00% and 54. 73% , respectively; The sediment reduction rate achieved by the sediment biological base could reach 20% within 5 days, and aeration in the overlying water could relieve the nutrient releasing caused by the degradation of organic matter; The effect of nutrient removal and organic matter reduction in sediment by the combined ecological restoration technology was perfect in pilot scale. The average removal rates of COD, NH+4 -N, TP were 52. 0%, 33. 6% and 23.4%, respectively, and the organic content in sediment was reduced from 38. 20% to 12.20% .

Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)

NASA Technical Reports Server (NTRS)

Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)

2004-01-01

These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.

Distance-dependent magnetic resonance tuning as a versatile MRI sensing platform for biological targets

NASA Astrophysics Data System (ADS)

Choi, Jin-Sil; Kim, Soojin; Yoo, Dongwon; Shin, Tae-Hyun; Kim, Hoyoung; Gomes, Muller D.; Kim, Sun Hee; Pines, Alexander; Cheon, Jinwoo

2017-05-01

Nanoscale distance-dependent phenomena, such as Förster resonance energy transfer, are important interactions for use in sensing and imaging, but their versatility for bioimaging can be limited by undesirable photon interactions with the surrounding biological matrix, especially in in vivo systems. Here, we report a new type of magnetism-based nanoscale distance-dependent phenomenon that can quantitatively and reversibly sense and image intra-/intermolecular interactions of biologically important targets. We introduce distance-dependent magnetic resonance tuning (MRET), which occurs between a paramagnetic `enhancer' and a superparamagnetic `quencher', where the T1 magnetic resonance imaging (MRI) signal is tuned ON or OFF depending on the separation distance between the quencher and the enhancer. With MRET, we demonstrate the principle of an MRI-based ruler for nanometre-scale distance measurement and the successful detection of both molecular interactions (for example, cleavage, binding, folding and unfolding) and biological targets in in vitro and in vivo systems. MRET can serve as a novel sensing principle to augment the exploration of a wide range of biological systems.

A versatile petri net based architecture for modeling and simulation of complex biological processes.

PubMed

Nagasaki, Masao; Doi, Atsushi; Matsuno, Hiroshi; Miyano, Satoru

2004-01-01

The research on modeling and simulation of complex biological systems is getting more important in Systems Biology. In this respect, we have developed Hybrid Function Petri net (HFPN) that was newly developed from existing Petri net because of their intuitive graphical representation and their capabilities for mathematical analyses. However, in the process of modeling metabolic, gene regulatory or signal transduction pathways with the architecture, we have realized three extensions of HFPN, (i) an entity should be extended to contain more than one value, (ii) an entity should be extended to handle other primitive types, e.g. boolean, string, (iii) an entity should be extended to handle more advanced type called object that consists of variables and methods, are necessary for modeling biological systems with Petri net based architecture. To deal with it, we define a new enhanced Petri net called hybrid functional Petri net with extension (HFPNe). To demonstrate the effectiveness of the enhancements, we model and simulate with HFPNe four biological processes that are diffcult to represent with the previous architecture HFPN.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Inspired Biological Engineering: Detection and Production of Polarized Light by Animals

DTIC Science & Technology

2009-05-26

polarizers in some mantis shrimps, where the animals’ cuticles combine dichroic polarizers based on the cuticular carotenoid, astaxanthin , with a... astaxanthin in animals - the first demonstration of a pigment-based polarizer intended for signaling in any biological system. We are preparing a paper for

[Smart therapeutics based on synthetic gene circuits].

PubMed

Peng, Shuguang; Xie, Zhen

2017-03-25

Synthetic biology has an important impact on biology research since its birth. Applying the thought and methods that reference from electrical engineering, synthetic biology uncovers many regulatory mechanisms of life systems, transforms and expands a series of biological components. Therefore, it brings a wide range of biomedical applications, including providing new ideas for disease diagnosis and treatment. This review describes the latest advances in the field of disease diagnosis and therapy based on mammalian cell or bacterial synthetic gene circuits, and provides new ideas for future smart therapy design.

KiMoSys: a web-based repository of experimental data for KInetic MOdels of biological SYStems

PubMed Central

2014-01-01

Background The kinetic modeling of biological systems is mainly composed of three steps that proceed iteratively: model building, simulation and analysis. In the first step, it is usually required to set initial metabolite concentrations, and to assign kinetic rate laws, along with estimating parameter values using kinetic data through optimization when these are not known. Although the rapid development of high-throughput methods has generated much omics data, experimentalists present only a summary of obtained results for publication, the experimental data files are not usually submitted to any public repository, or simply not available at all. In order to automatize as much as possible the steps of building kinetic models, there is a growing requirement in the systems biology community for easily exchanging data in combination with models, which represents the main motivation of KiMoSys development. Description KiMoSys is a user-friendly platform that includes a public data repository of published experimental data, containing concentration data of metabolites and enzymes and flux data. It was designed to ensure data management, storage and sharing for a wider systems biology community. This community repository offers a web-based interface and upload facility to turn available data into publicly accessible, centralized and structured-format data files. Moreover, it compiles and integrates available kinetic models associated with the data. KiMoSys also integrates some tools to facilitate the kinetic model construction process of large-scale metabolic networks, especially when the systems biologists perform computational research. Conclusions KiMoSys is a web-based system that integrates a public data and associated model(s) repository with computational tools, providing the systems biology community with a novel application facilitating data storage and sharing, thus supporting construction of ODE-based kinetic models and collaborative research projects. The web application implemented using Ruby on Rails framework is freely available for web access at http://kimosys.org, along with its full documentation. PMID:25115331

Methods for improving simulations of biological systems: systemic computation and fractal proteins

PubMed Central

Bentley, Peter J.

2009-01-01

Modelling and simulation are becoming essential for new fields such as synthetic biology. Perhaps the most important aspect of modelling is to follow a clear design methodology that will help to highlight unwanted deficiencies. The use of tools designed to aid the modelling process can be of benefit in many situations. In this paper, the modelling approach called systemic computation (SC) is introduced. SC is an interaction-based language, which enables individual-based expression and modelling of biological systems, and the interactions between them. SC permits a precise description of a hypothetical mechanism to be written using an intuitive graph-based or a calculus-based notation. The same description can then be directly run as a simulation, merging the hypothetical mechanism and the simulation into the same entity. However, even when using well-designed modelling tools to produce good models, the best model is not always the most accurate one. Frequently, computational constraints or lack of data make it infeasible to model an aspect of biology. Simplification may provide one way forward, but with inevitable consequences of decreased accuracy. Instead of attempting to replace an element with a simpler approximation, it is sometimes possible to substitute the element with a different but functionally similar component. In the second part of this paper, this modelling approach is described and its advantages are summarized using an exemplar: the fractal protein model. Finally, the paper ends with a discussion of good biological modelling practice by presenting lessons learned from the use of SC and the fractal protein model. PMID:19324681

Eugene – A Domain Specific Language for Specifying and Constraining Synthetic Biological Parts, Devices, and Systems

PubMed Central

Bilitchenko, Lesia; Liu, Adam; Cheung, Sherine; Weeding, Emma; Xia, Bing; Leguia, Mariana; Anderson, J. Christopher; Densmore, Douglas

2011-01-01

Background Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. Results We illustrate Eugene's capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugene's ability to create combinatorial design spaces and prune these spaces for simulation or physical assembly. Eugene creates functional designs quickly and cost-effectively. Conclusions Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired abstraction hierarchy in synthetic biology. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and physical device assembly. PMID:21559524

United States Air Force Training Management 2010. Volume 2. A Strategy for Superiority

DTIC Science & Technology

1989-03-01

decontaminate the ramp area with the remote robotic Chemical- Biological Warfare (CBW) sterilizers. If the Chemical- Biological (CB) attacks continue, she will be...Of Skilled Craftsmen Troubles Some Firms." The Wall Street Journal. 14 September 1987, pp. 1,8. 44. Naisbitt, John. Megatrends : Ten New Directions...Computer Based Training CBW Chemical- Biological Warfare CMAS Computer-Based Maintenance Aids System CMI Computer-Managed Instruction DOD Department of

Designing and testing a classroom curriculum to teach preschoolers about the biology of physical activity: The respiration system as an underlying biological causal mechanism

NASA Astrophysics Data System (ADS)

Ewing, Tracy S.

The present study examined young children's understanding of respiration and oxygen as a source of vital energy underlying physical activity. Specifically, the purpose of the study was to explore whether a coherent biological theory, characterized by an understanding that bodily parts (heart and lungs) and processes (oxygen in respiration) as part of a biological system, can be taught as a foundational concept to reason about physical activity. The effects of a biology-based intervention curriculum designed to teach preschool children about bodily functions as a part of the respiratory system, the role of oxygen as a vital substance and how physical activity acts an energy source were examined. Participants were recruited from three private preschool classrooms (two treatment; 1 control) in Southern California and included a total of 48 four-year-old children (30 treatment; 18 control). Findings from this study suggested that young children could be taught relevant biological concepts about the role of oxygen in respiratory processes. Children who received biology-based intervention curriculum made significant gains in their understanding of the biology of respiration, identification of physical and sedentary activities. In addition these children demonstrated that coherence of conceptual knowledge was correlated with improved accuracy at activity identification and reasoning about the inner workings of the body contributing to endurance. Findings from this study provided evidence to support the benefits of providing age appropriate but complex coherent biological instruction to children in early childhood settings.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach.

PubMed

St Laurent, Georges; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J L; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R R; Nicolas, Estelle; McCaffrey, Timothy A; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-04-20

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Clustering of 3D-Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities.

PubMed

Ohtana, Yuki; Abdullah, Azian Azamimi; Altaf-Ul-Amin, Md; Huang, Ming; Ono, Naoaki; Sato, Tetsuo; Sugiura, Tadao; Horai, Hisayuki; Nakamura, Yukiko; Morita Hirai, Aki; Lange, Klaus W; Kibinge, Nelson K; Katsuragi, Tetsuo; Shirai, Tsuyoshi; Kanaya, Shigehiko

2014-12-01

Developing database systems connecting diverse species based on omics is the most important theme in big data biology. To attain this purpose, we have developed KNApSAcK Family Databases, which are utilized in a number of researches in metabolomics. In the present study, we have developed a network-based approach to analyze relationships between 3D structure and biological activity of metabolites consisting of four steps as follows: construction of a network of metabolites based on structural similarity (Step 1), classification of metabolites into structure groups (Step 2), assessment of statistically significant relations between structure groups and biological activities (Step 3), and 2-dimensional clustering of the constructed data matrix based on statistically significant relations between structure groups and biological activities (Step 4). Applying this method to a data set consisting of 2072 secondary metabolites and 140 biological activities reported in KNApSAcK Metabolite Activity DB, we obtained 983 statistically significant structure group-biological activity pairs. As a whole, we systematically analyzed the relationship between 3D-chemical structures of metabolites and biological activities. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PerSubs: A Graph-Based Algorithm for the Identification of Perturbed Subpathways Caused by Complex Diseases.

PubMed

Vrahatis, Aristidis G; Rapti, Angeliki; Sioutas, Spyros; Tsakalidis, Athanasios

2017-01-01

In the era of Systems Biology and growing flow of omics experimental data from high throughput techniques, experimentalists are in need of more precise pathway-based tools to unravel the inherent complexity of diseases and biological processes. Subpathway-based approaches are the emerging generation of pathway-based analysis elucidating the biological mechanisms under the perspective of local topologies onto a complex pathway network. Towards this orientation, we developed PerSub, a graph-based algorithm which detects subpathways perturbed by a complex disease. The perturbations are imprinted through differentially expressed and co-expressed subpathways as recorded by RNA-seq experiments. Our novel algorithm is applied on data obtained from a real experimental study and the identified subpathways provide biological evidence for the brain aging.

Metabolic systems biology: a brief primer.

PubMed

Edwards, Lindsay M

2017-05-01

In the early to mid-20th century, reductionism as a concept in biology was challenged by key thinkers, including Ludwig von Bertalanffy. He proposed that living organisms were specific examples of complex systems and, as such, they should display characteristics including hierarchical organisation and emergent behaviour. Yet the true study of complete biological systems (for example, metabolism) was not possible until technological advances that occurred 60 years later. Technology now exists that permits the measurement of complete levels of the biological hierarchy, for example the genome and transcriptome. The complexity and scale of these data require computational models for their interpretation. The combination of these - systems thinking, high-dimensional data and computation - defines systems biology, typically accompanied by some notion of iterative model refinement. Only sequencing-based technologies, however, offer full coverage. Other 'omics' platforms trade coverage for sensitivity, although the densely connected nature of biological networks suggests that full coverage may not be necessary. Systems biology models are often characterised as either 'bottom-up' (mechanistic) or 'top-down' (statistical). This distinction can mislead, as all models rely on data and all are, to some degree, 'middle-out'. Systems biology has matured as a discipline, and its methods are commonplace in many laboratories. However, many challenges remain, especially those related to large-scale data integration. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Ontology- and graph-based similarity assessment in biological networks.

PubMed

Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-10-15

A standard systems-based approach to biomarker and drug target discovery consists of placing putative biomarkers in the context of a network of biological interactions, followed by different 'guilt-by-association' analyses. The latter is typically done based on network structural features. Here, an alternative analysis approach in which the networks are analyzed on a 'semantic similarity' space is reported. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment in biological networks. http://rosalind.infj.ulst.ac.uk/SimTrek.html francisco.azuaje@crp-sante.lu Supplementary data are available at Bioinformatics online.

A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems

PubMed Central

Cook, Daniel L; Farley, Joel F; Tapscott, Stephen J

2001-01-01

Background: We propose that a computerized, internet-based graphical description language for systems biology will be essential for describing, archiving and analyzing complex problems of biological function in health and disease. Results: We outline here a conceptual basis for designing such a language and describe BioD, a prototype language that we have used to explore the utility and feasibility of this approach to functional biology. Using example models, we demonstrate that a rather limited lexicon of icons and arrows suffices to describe complex cell-biological systems as discrete models that can be posted and linked on the internet. Conclusions: Given available computer and internet technology, BioD may be implemented as an extensible, multidisciplinary language that can be used to archive functional systems knowledge and be extended to support both qualitative and quantitative functional analysis. PMID:11305940

Microgravity Fluids for Biology, Workshop

NASA Technical Reports Server (NTRS)

Griffin, DeVon; Kohl, Fred; Massa, Gioia D.; Motil, Brian; Parsons-Wingerter, Patricia; Quincy, Charles; Sato, Kevin; Singh, Bhim; Smith, Jeffrey D.; Wheeler, Raymond M.

2013-01-01

Microgravity Fluids for Biology represents an intersection of biology and fluid physics that present exciting research challenges to the Space Life and Physical Sciences Division. Solving and managing the transport processes and fluid mechanics in physiological and biological systems and processes are essential for future space exploration and colonization of space by humans. Adequate understanding of the underlying fluid physics and transport mechanisms will provide new, necessary insights and technologies for analyzing and designing biological systems critical to NASAs mission. To enable this mission, the fluid physics discipline needs to work to enhance the understanding of the influence of gravity on the scales and types of fluids (i.e., non-Newtonian) important to biology and life sciences. In turn, biomimetic, bio-inspired and synthetic biology applications based on physiology and biology can enrich the fluid mechanics and transport phenomena capabilities of the microgravity fluid physics community.

Frontiers of optofluidics in synthetic biology.

PubMed

Tan, Cheemeng; Lo, Shih-Jie; LeDuc, Philip R; Cheng, Chao-Min

2012-10-07

The development of optofluidic-based technology has ushered in a new era of lab-on-a-chip functionality, including miniaturization of biomedical devices, enhanced sensitivity for molecular detection, and multiplexing of optical measurements. While having great potential, optofluidic devices have only begun to be exploited in many biotechnological applications. Here, we highlight the potential of integrating optofluidic devices with synthetic biological systems, which is a field focusing on creating novel cellular systems by engineering synthetic gene and protein networks. First, we review the development of synthetic biology at different length scales, ranging from single-molecule, single-cell, to cellular population. We emphasize light-sensitive synthetic biological systems that would be relevant for the integration with optofluidic devices. Next, we propose several areas for potential applications of optofluidics in synthetic biology. The integration of optofluidics and synthetic biology would have a broad impact on point-of-care diagnostics and biotechnology.

Life detection systems.

NASA Technical Reports Server (NTRS)

Mitz, M. A.

1972-01-01

Some promising newer approaches for detecting microorganisms are discussed, giving particular attention to the integration of different methods into a single instrument. Life detection methods may be divided into biological, chemical, and cytological methods. Biological methods are based on the biological properties of assimilation, metabolism, and growth. Devices for the detection of organic materials are considered, taking into account an instrument which volatilizes, separates, and analyzes a sample sequentially. Other instrumental systems described make use of a microscope and the cytochemical staining principle.

Organizing Community-Based Data Standards: Lessons from Developing a Successful Open Standard in Systems Biology

NASA Astrophysics Data System (ADS)

Hucka, M.

2015-09-01

In common with many fields, including astronomy, a vast number of software tools for computational modeling and simulation are available today in systems biology. This wealth of resources is a boon to researchers, but it also presents interoperability problems. Despite working with different software tools, researchers want to disseminate their work widely as well as reuse and extend the models of other researchers. This situation led in the year 2000 to an effort to create a tool-independent, machine-readable file format for representing models: SBML, the Systems Biology Markup Language. SBML has since become the de facto standard for its purpose. Its success and general approach has inspired and influenced other community-oriented standardization efforts in systems biology. Open standards are essential for the progress of science in all fields, but it is often difficult for academic researchers to organize successful community-based standards. I draw on personal experiences from the development of SBML and summarize some of the lessons learned, in the hope that this may be useful to other groups seeking to develop open standards in a community-oriented fashion.

Present systems and future needs for risk assessment of veterinary biologicals in Australia: the perspective of the regulator.

PubMed

Doyle, K A

1995-12-01

The increasing range and complexity of biologicals, and the greater demand for these products, have resulted in a greater volume of trade in animal-based biological material. This has given rise, in turn, to many approaches to the regulation of importation of these materials, as countries seek protection against the introduction of disease. Harmonization of these regulatory approaches would contribute significantly to the availability of veterinary biologicals, to their manufacture and trade, and to disease security. Australia has developed systems for the categorisation and evaluation of biologicals, control by import permits, and specific procedures at point-of-entry and in institutions where these products are used. Computerised records and precedents assist in evaluation and in the issuing of permits. Recognition that some materials must be subject to further control has led to a system of registration of institutions based on levels of biosecurity, and approved use and disposal programmes. Institutions vary from high-security animal health laboratories to human in vitro fertilisation clinics, which use animal-derived media and materials. Such institutions are regulated through quality assurance contracts. Quarantine authorities have linkages with other agencies which have an interest in these products. These linkages reflect the administrative structures of government in Australia, and provide for management of all forms of risk. The author describes these systems and overviews their biological basis.

Real-time Measurements of Biological Particles at Several Continental Sites using the WIBS-4A

NASA Astrophysics Data System (ADS)

McMeeking, G. R.; Kok, G. L.; Petters, M. D.; Wright, T.; Hader, J.; Mccubbin, I. B.; Hallar, A. G.; Twohy, C. H.; Toohey, D. W.; DeMott, P. J.; McCluskey, C.; Baumgardner, D.

2013-12-01

Biological particles (bacteria, fungi/fungal spores, viruses, algae and fragments of biological material) may play a significant role in modifying cloud properties by acting as ice nuclei and thus have an indirect effect on climate forcing. Little is known, however, regarding the abundance and distribution of biological particles and their importance to cloud microphysics in different environments. On-line, continuous measurement systems offer the potential to measure biological systems at high time resolution and sensitivity, providing greater insight into their distribution in the atmosphere, dispersal mechanisms and potential soures. The WIBS-4A (Wideband Integrated Bioaerosol Sensor) detects fluorescent biological material in real-time associated with individual particles. It measures five properties: a) optical size via light scattering, b) fluorescent emissions in the wavelength range 310-400 following excitation by 280 nm light, c) fluorescent emissions in the wavelength range 420-650 following excitation by 280 nm light, d) fluorescent emissions in the wavelength range 420-650 following excitation by 370 nm light, and e) particle asymmetry factor based on intensities of forward scattered light onto a 4-element detector. Together, these properties aid the classification of sampled particles that contain biofluorophores such as tryptophan or NAD(P)H, which can be found in biological particles. Here we present results from a series of laboratory, ground- and aircraft-based measurements of biological particles using the WIBS-4A. The studies include airborne measurements over the United States, ground-based measurements at a coastal site, an urban site in the southeast US and a high alpine site, and laboratory measurements of a variety of biological and non-biological particles. Our analysis focused on both the characterization of the instrument response as well as an evaluation of its suitability for performing ambient measurements and potential artifacts. We also present recommendations for field operation of the instrument, sample system design considerations, and data analysis approaches.

A System to Automatically Classify and Name Any Individual Genome-Sequenced Organism Independently of Current Biological Classification and Nomenclature

PubMed Central

Song, Yuhyun; Leman, Scotland; Monteil, Caroline L.; Heath, Lenwood S.; Vinatzer, Boris A.

2014-01-01

A broadly accepted and stable biological classification system is a prerequisite for biological sciences. It provides the means to describe and communicate about life without ambiguity. Current biological classification and nomenclature use the species as the basic unit and require lengthy and laborious species descriptions before newly discovered organisms can be assigned to a species and be named. The current system is thus inadequate to classify and name the immense genetic diversity within species that is now being revealed by genome sequencing on a daily basis. To address this lack of a general intra-species classification and naming system adequate for today’s speed of discovery of new diversity, we propose a classification and naming system that is exclusively based on genome similarity and that is suitable for automatic assignment of codes to any genome-sequenced organism without requiring any phenotypic or phylogenetic analysis. We provide examples demonstrating that genome similarity-based codes largely align with current taxonomic groups at many different levels in bacteria, animals, humans, plants, and viruses. Importantly, the proposed approach is only slightly affected by the order of code assignment and can thus provide codes that reflect similarity between organisms and that do not need to be revised upon discovery of new diversity. We envision genome similarity-based codes to complement current biological nomenclature and to provide a universal means to communicate unambiguously about any genome-sequenced organism in fields as diverse as biodiversity research, infectious disease control, human and microbial forensics, animal breed and plant cultivar certification, and human ancestry research. PMID:24586551

A system to evaluate the scientific quality of biological and restoration objectives using National Wildlife Refuge Comprehensive Conservation Plans as a case study

USGS Publications Warehouse

Schroeder, R.L.

2006-01-01

It is widely accepted that plans for restoration projects should contain specific, measurable, and science-based objectives to guide restoration efforts. The United States Fish and Wildlife Service (USFWS) is in the process of developing Comprehensive Conservation Plans (CCPs) for more than 500 units in the National Wildlife Refuge System (NWRS). These plans contain objectives for biological and ecosystem restoration efforts on the refuges. Based on USFWS policy, a system was developed to evaluate the scientific quality of such objectives based on three critical factors: (1) Is the objective specific, measurable, achievable, results-oriented, and time-fixed? (2) What is the extent of the rationale that explains the assumptions, logic, and reasoning for the objective? (3) How well was available science used in the development of the objective? The evaluation system scores each factor on a scale of 1 (poor) to 4 (excellent) according to detailed criteria. The biological and restoration objectives from CCPs published as of September 2004 (60 total) were evaluated. The overall average score for all biological and restoration objectives was 1.73. Average scores for each factor were: Factor 1-1.97; Factor 2-1.86; Factor 3-1.38. The overall scores increased from 1997 to 2004. Future restoration efforts may benefit by using this evaluation system during the process of plan development, to ensure that biological and restoration objectives are of the highest scientific quality possible prior to the implementation of restoration plans, and to allow for improved monitoring and adaptive management.

First-principles modeling of biological systems and structure-based drug-design.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

Molecular modeling techniques play a relevant role in drug design providing detailed information at atomistic level on the structural, dynamical, mechanistic and electronic properties of biological systems involved in diseases' onset, integrating and supporting commonly used experimental approaches. These information are often not accessible to the experimental techniques taken singularly, but are of crucial importance for drug design. Due to the enormous increase of the computer power in the last decades, quantum mechanical (QM) or first-principles-based methods have become often used to address biological issues of pharmaceutical relevance, providing relevant information for drug design. Due to their complexity and their size, biological systems are often investigated by means of a mixed quantum-classical (QM/MM) approach, which treats at an accurate QM level a limited chemically relevant portion of the system and at the molecular mechanics (MM) level the remaining of the biomolecule and its environment. This method provides a good compromise between computational cost and accuracy, allowing to characterize the properties of the biological system and the (free) energy landscape of the process in study with the accuracy of a QM description. In this review, after a brief introduction of QM and QM/MM methods, we will discuss few representative examples, taken from our work, of the application of these methods in the study of metallo-enzymes of pharmaceutical interest, of metal-containing anticancer drugs targeting the DNA as well as of neurodegenerative diseases. The information obtained from these studies may provide the basis for a rationale structure-based drug design of new and more efficient inhibitors or drugs.

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.

PubMed

Arakawa, Kazuharu; Yamada, Yohei; Shinoda, Kosaku; Nakayama, Yoichi; Tomita, Masaru

2006-03-23

Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

Method of improving system performance and survivability through changing function

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Vassev, Emil I. (Inventor)

2012-01-01

A biologically-inspired system and method is provided for self-adapting behavior of swarm-based exploration missions, whereby individual components, for example, spacecraft, in the system can sacrifice themselves for the greater good of the entire system. The swarm-based system can exhibit emergent self-adapting behavior. Each component can be configured to exhibit self-sacrifice behavior based on Autonomic System Specification Language (ASSL).

The Eugene language for synthetic biology.

PubMed

Bilitchenko, Lesia; Liu, Adam; Densmore, Douglas

2011-01-01

Synthetic biological systems are currently created by an ad hoc, iterative process of design, simulation, and assembly. These systems would greatly benefit from the introduction of a more formalized and rigorous specification of the desired system components as well as constraints on their composition. In order to do so, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) which allows for both the specification of synthetic biological designs based on biological parts as well as providing a very expressive constraint system to drive the creation of composite devices from collection of parts. This chapter provides an overview of the language primitives as well as instructions on installation and use of Eugene v0.03b. Copyright © 2011 Elsevier Inc. All rights reserved.

A Systems Biology Approach to Iron Metabolism

PubMed Central

Chifman, J.; Laubenbacher, R.; Torti, S.V.

2015-01-01

Iron is critical to the survival of almost all living organisms. However, inappropriately low or high levels of iron are detrimental and contribute to a wide range of diseases. Recent advances in the study of iron metabolism have revealed multiple intricate pathways that are essential to the maintenance of iron homeostasis. Further, iron regulation involves processes at several scales, ranging from the subcellular to the organismal. This complexity makes a systems biology approach crucial, with its enabling technology of computational models based on a mathematical description of regulatory systems. Systems biology may represent a new strategy for understanding imbalances in iron metabolism and their underlying causes. PMID:25480643

Biosensor Recognition Elements

DTIC Science & Technology

2008-01-01

Systematics, bioinformatics, systems biology, regulation, genetics, genomics, metabolism, ecology, development . Epstein - Barr Virus Latency and...and C, Simian immunodeficiency, Ebola, Rabies, Epstein – Barr , and Measles viruses as well as biological agents such as botulinum neurotoxin A/B...time metabolic vigilance via sensor based ligand specific biorecognition elements is immense. Virus -based nanoparticles have been developed for

A Project-Based Biologically-Inspired Robotics Module

ERIC Educational Resources Information Center

Crowder, R. M.; Zauner, K.-P.

2013-01-01

The design of any robotic system requires input from engineers from a variety of technical fields. This paper describes a project-based module, "Biologically-Inspired Robotics," that is offered to Electronics and Computer Science students at the University of Southampton, U.K. The overall objective of the module is for student groups to…

Metabolic cancer biology: structural-based analysis of cancer as a metabolic disease, new sights and opportunities for disease treatment.

PubMed

Masoudi-Nejad, Ali; Asgari, Yazdan

2015-02-01

The cancer cell metabolism or the Warburg effect discovery goes back to 1924 when, for the first time Otto Warburg observed, in contrast to the normal cells, cancer cells have different metabolism. With the initiation of high throughput technologies and computational systems biology, cancer cell metabolism renaissances and many attempts were performed to revise the Warburg effect. The development of experimental and analytical tools which generate high-throughput biological data including lots of information could lead to application of computational models in biological discovery and clinical medicine especially for cancer. Due to the recent availability of tissue-specific reconstructed models, new opportunities in studying metabolic alteration in various kinds of cancers open up. Structural approaches at genome-scale levels seem to be suitable for developing diagnostic and prognostic molecular signatures, as well as in identifying new drug targets. In this review, we have considered these recent advances in structural-based analysis of cancer as a metabolic disease view. Two different structural approaches have been described here: topological and constraint-based methods. The ultimate goal of this type of systems analysis is not only the discovery of novel drug targets but also the development of new systems-based therapy strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using two classification schemes to develop vegetation indices of biological integrity for wetlands in West Virginia, USA.

PubMed

Veselka, Walter; Rentch, James S; Grafton, William N; Kordek, Walter S; Anderson, James T

2010-11-01

Bioassessment methods for wetlands, and other bodies of water, have been developed worldwide to measure and quantify changes in "biological integrity." These assessments are based on a classification system, meant to ensure appropriate comparisons between wetland types. Using a local site-specific disturbance gradient, we built vegetation indices of biological integrity (Veg-IBIs) based on two commonly used wetland classification systems in the USA: One based on vegetative structure and the other based on a wetland's position in a landscape and sources of water. The resulting class-specific Veg-IBIs were comprised of 1-5 metrics that varied in their sensitivity to the disturbance gradient (R2=0.14-0.65). Moreover, the sensitivity to the disturbance gradient increased as metrics from each of the two classification schemes were combined (added). Using this information to monitor natural and created wetlands will help natural resource managers track changes in biological integrity of wetlands in response to anthropogenic disturbance and allows the use of vegetative communities to set ecological performance standards for mitigation banks.

Generation and characterization of biological aerosols for laser measurements

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

Cheng, Yung-Sung; Barr, E.B.

1995-12-01

Concerns for proliferation of biological weapons including bacteria, fungi, and viruses have prompted research and development on methods for the rapid detection of biological aerosols in the field. Real-time instruments that can distinguish biological aerosols from background dust would be especially useful. Sandia National Laboratories (SNL) is developing a laser-based, real-time instrument for rapid detection of biological aerosols, and ITRI is working with SNL scientists and engineers to evaluate this technology for a wide range of biological aerosols. This paper describes methods being used to generate the characterize the biological aerosols for these tests. In summary, a biosafe system hasmore » been developed for generating and characterizing biological aerosols and using those aerosols to test the SNL laser-based real-time instrument. Such tests are essential in studying methods for rapid detection of airborne biological materials.« less

Systems pharmacology - Towards the modeling of network interactions.

PubMed

Danhof, Meindert

2016-10-30

Mechanism-based pharmacokinetic and pharmacodynamics (PKPD) and disease system (DS) models have been introduced in drug discovery and development research, to predict in a quantitative manner the effect of drug treatment in vivo in health and disease. This requires consideration of several fundamental properties of biological systems behavior including: hysteresis, non-linearity, variability, interdependency, convergence, resilience, and multi-stationarity. Classical physiology-based PKPD models consider linear transduction pathways, connecting processes on the causal path between drug administration and effect, as the basis of drug action. Depending on the drug and its biological target, such models may contain expressions to characterize i) the disposition and the target site distribution kinetics of the drug under investigation, ii) the kinetics of target binding and activation and iii) the kinetics of transduction. When connected to physiology-based DS models, PKPD models can characterize the effect on disease progression in a mechanistic manner. These models have been found useful to characterize hysteresis and non-linearity, yet they fail to explain the effects of the other fundamental properties of biological systems behavior. Recently systems pharmacology has been introduced as novel approach to predict in vivo drug effects, in which biological networks rather than single transduction pathways are considered as the basis of drug action and disease progression. These models contain expressions to characterize the functional interactions within a biological network. Such interactions are relevant when drugs act at multiple targets in the network or when homeostatic feedback mechanisms are operative. As a result systems pharmacology models are particularly useful to describe complex patterns of drug action (i.e. synergy, oscillatory behavior) and disease progression (i.e. episodic disorders). In this contribution it is shown how physiology-based PKPD and disease models can be extended to account for internal systems interactions. It is demonstrated how SP models can be used to predict the effects of multi-target interactions and of homeostatic feedback on the pharmacological response. In addition it is shown how DS models may be used to distinguish symptomatic from disease modifying effects and to predict the long term effects on disease progression, from short term biomarker responses. It is concluded that incorporation of expressions to describe the interactions in biological network analysis opens new avenues to the understanding of the effects of drug treatment on the fundamental aspects of biological systems behavior. Copyright © 2016 The Author. Published by Elsevier B.V. All rights reserved.

Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

PubMed

Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

2017-03-01

Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Integration of ecological-biological thresholds in conservation decision making.

PubMed

Mavrommati, Georgia; Bithas, Kostas; Borsuk, Mark E; Howarth, Richard B

2016-12-01

In the Anthropocene, coupled human and natural systems dominate and only a few natural systems remain relatively unaffected by human influence. On the one hand, conservation criteria based on areas of minimal human impact are not relevant to much of the biosphere. On the other hand, conservation criteria based on economic factors are problematic with respect to their ability to arrive at operational indicators of well-being that can be applied in practice over multiple generations. Coupled human and natural systems are subject to economic development which, under current management structures, tends to affect natural systems and cross planetary boundaries. Hence, designing and applying conservation criteria applicable in real-world systems where human and natural systems need to interact and sustainably coexist is essential. By recognizing the criticality of satisfying basic needs as well as the great uncertainty over the needs and preferences of future generations, we sought to incorporate conservation criteria based on minimal human impact into economic evaluation. These criteria require the conservation of environmental conditions such that the opportunity for intergenerational welfare optimization is maintained. Toward this end, we propose the integration of ecological-biological thresholds into decision making and use as an example the planetary-boundaries approach. Both conservation scientists and economists must be involved in defining operational ecological-biological thresholds that can be incorporated into economic thinking and reflect the objectives of conservation, sustainability, and intergenerational welfare optimization. © 2016 Society for Conservation Biology.

Completing and Adapting Models of Biological Processes

NASA Technical Reports Server (NTRS)

Margaria, Tiziana; Hinchey, Michael G.; Raffelt, Harald; Rash, James L.; Rouff, Christopher A.; Steffen, Bernhard

2006-01-01

We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by generating models of biological procedures concerning gene activities in the production of proteins, although the main application is going to concern autonomic systems for space exploration.

Peptide π-Electron Conjugates: Organic Electronics for Biology?

PubMed

Ardoña, Herdeline Ann M; Tovar, John D

2015-12-16

Highly ordered arrays of π-conjugated molecules are often viewed as a prerequisite for effective charge-transporting materials. Studies involving these materials have traditionally focused on organic electronic devices, with more recent emphasis on biological systems. In order to facilitate the transition to biological environments, biomolecules that can promote hierarchical ordering and water solubility are often covalently appended to the π-electron unit. This review highlights recent work on π-conjugated systems bound to peptide moieties that exhibit self-assembly and aims to provide an overview on the development and emerging applications of peptide-based supramolecular π-electron systems.

Synthetic Biology and Microbial Fuel Cells: Towards Self-Sustaining Life Support Systems

NASA Technical Reports Server (NTRS)

Hogan, John Andrew

2014-01-01

NASA ARC and the J. Craig Venter Institute (JCVI) collaborated to investigate the development of advanced microbial fuels cells (MFCs) for biological wastewater treatment and electricity production (electrogenesis). Synthetic biology techniques and integrated hardware advances were investigated to increase system efficiency and robustness, with the intent of increasing power self-sufficiency and potential product formation from carbon dioxide. MFCs possess numerous advantages for space missions, including rapid processing, reduced biomass and effective removal of organics, nitrogen and phosphorus. Project efforts include developing space-based MFC concepts, integration analyses, increasing energy efficiency, and investigating novel bioelectrochemical system applications

Synthetic biology: insights into biological computation.

PubMed

Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

2016-04-18

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

A Best-Practice Model for Academic Advising of University Biology Majors

ERIC Educational Resources Information Center

Heekin, Jonathan Ralph Calvin

2013-01-01

Biology faculty at an East Coast university believed their undergraduate students were not being well served by the existing academic advising program. The purpose of this mixed methods project study was to evaluate the effectiveness of the academic advising model in a biology department. Guided by system-based organizational theory, a learning…

SER consensus statement on the use of biologic therapy for systemic lupus erythematosus.

PubMed

Calvo-Alén, Jaime; Silva-Fernández, Lucía; Úcar-Angulo, Eduardo; Pego-Reigosa, José María; Olivé, Alejandro; Martínez-Fernández, Carmen; Martínez-Taboada, Víctor; Luis Marenco, José; Loza, Estíbaliz; López-Longo, Javier; Gómez-Reino, Juan Jesús; Galindo-Izquierdo, María; Fernández-Nebro, Antonio; Cuadrado, María José; Aguirre-Zamorano, María Ángeles; Zea-Mendoza, Antonio; Rúa-Figueroa, Iñigo

2013-01-01

To provide a reference to rheumatologists and other physicians involved in the treatment of systemic lupus erythematosus (SLE) who are using, or about to use biologic therapies. Recommendations were developed following a nominal group methodology and based on systematic reviews. The level of evidence and degree of recommendation were classified according to a model proposed by the Center for Evidence Based Medicine at Oxford. The level of agreement was established through a Delphi technique. We have produced recommendations on the use of belimumab, the only biological agent with approved indications for SLE, and other biological agents without an indication for SLE. The objective of treatment is to achieve a complete clinical response, taken as the absence of perceived or evident disease activity. Nuances regarding the use of biologic therapies in SLE were reviewed as well, such as the evaluation that should be performed prior to administration and the follow up of patients undergoing these therapies. We present the SER recommendations for the use of biological therapies in patients with SLE. Copyright © 2013 Elsevier España, S.L. All rights reserved.

A Personal Journey of Discovery: Developing Technology and Changing Biology

NASA Astrophysics Data System (ADS)

Hood, Lee

2008-07-01

This autobiographical article describes my experiences in developing chemically based, biological technologies for deciphering biological information: DNA, RNA, proteins, interactions, and networks. The instruments developed include protein and DNA sequencers and synthesizers, as well as ink-jet technology for synthesizing DNA chips. Diverse new strategies for doing biology also arose from novel applications of these instruments. The functioning of these instruments can be integrated to generate powerful new approaches to cloning and characterizing genes from a small amount of protein sequence or to using gene sequences to synthesize peptide fragments so as to characterize various properties of the proteins. I also discuss the five paradigm changes in which I have participated: the development and integration of biological instrumentation; the human genome project; cross-disciplinary biology; systems biology; and predictive, personalized, preventive, and participatory (P4) medicine. Finally, I discuss the origins, the philosophy, some accomplishments, and the future trajectories of the Institute for Systems Biology.

Engineering stategies and implications of using higher plants for throttling gas and water exchange in a controlled ecological life support system

NASA Technical Reports Server (NTRS)

Chamberland, Dennis; Wheeler, Raymond M.; Corey, Kenneth A.

1993-01-01

Engineering stategies for advanced life support systems to be used on Lunar and Mars bases involve a wide spectrum of approaches. These range from purely physical-chemical life support strategies to purely biological approaches. Within the context of biological based systems, a bioengineered system can be devised that would utilize the metabolic mechanisms of plants to control the rates of CO2 uptake and O2 evolution (photosynthesis) and water production (transpiration). Such a mechanism of external engineering control has become known as throttling. Research conducted at the John F. Kennedy Space Center's Controlled Ecological Life Support System Breadboard Project has demonstrated the potential of throttling these fluxes by changing environmental parameters affecting the plant processes. Among the more effective environmental throttles are: light and CO2 concentration for controllingthe rate of photsynthesis and humidity and CO2 concentration for controlling transpiration. Such a bioengineered strategy implies control mechanisms that in the past have not been widely attributed to life support systems involving biological components and suggests a broad range of applications in advanced life support system design.

When physics is not "just physics": complexity science invites new measurement frames for exploring the physics of cognitive and biological development.

PubMed

Kelty-Stephen, Damian; Dixon, James A

2012-01-01

The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenomena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science offers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena.

Analyzing Defects in the "Caenorhabditis Elegans" Nervous System Using Organismal and Cell Biological Approaches

ERIC Educational Resources Information Center

Guziewicz, Megan; Vitullo, Toni; Simmons, Bethany; Kohn, Rebecca Eustance

2002-01-01

The goal of this laboratory exercise is to increase student understanding of the impact of nervous system function at both the organismal and cellular levels. This inquiry-based exercise is designed for an undergraduate course examining principles of cell biology. After observing the movement of "Caenorhabditis elegans" with defects in their…

Logic-based models in systems biology: a predictive and parameter-free network analysis method†

PubMed Central

Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

2012-01-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

Efficient digital implementation of a conductance-based globus pallidus neuron and the dynamics analysis

NASA Astrophysics Data System (ADS)

Yang, Shuangming; Wei, Xile; Deng, Bin; Liu, Chen; Li, Huiyan; Wang, Jiang

2018-03-01

Balance between biological plausibility of dynamical activities and computational efficiency is one of challenging problems in computational neuroscience and neural system engineering. This paper proposes a set of efficient methods for the hardware realization of the conductance-based neuron model with relevant dynamics, targeting reproducing the biological behaviors with low-cost implementation on digital programmable platform, which can be applied in wide range of conductance-based neuron models. Modified GP neuron models for efficient hardware implementation are presented to reproduce reliable pallidal dynamics, which decode the information of basal ganglia and regulate the movement disorder related voluntary activities. Implementation results on a field-programmable gate array (FPGA) demonstrate that the proposed techniques and models can reduce the resource cost significantly and reproduce the biological dynamics accurately. Besides, the biological behaviors with weak network coupling are explored on the proposed platform, and theoretical analysis is also made for the investigation of biological characteristics of the structured pallidal oscillator and network. The implementation techniques provide an essential step towards the large-scale neural network to explore the dynamical mechanisms in real time. Furthermore, the proposed methodology enables the FPGA-based system a powerful platform for the investigation on neurodegenerative diseases and real-time control of bio-inspired neuro-robotics.

Identification of nanoparticles and nanosystems in biological matrices with scanning probe microscopy.

PubMed

Angeloni, Livia; Reggente, Melania; Passeri, Daniele; Natali, Marco; Rossi, Marco

2018-04-17

Identification of nanoparticles and nanosystems into cells and biological matrices is a hot research topic in nanobiotechnologies. Because of their capability to map physical properties (mechanical, electric, magnetic, chemical, or optical), several scanning probe microscopy based techniques have been proposed for the subsurface detection of nanomaterials in biological systems. In particular, atomic force microscopy (AFM) can be used to reveal stiff nanoparticles in cells and other soft biomaterials by probing the sample mechanical properties through the acquisition of local indentation curves or through the combination of ultrasound-based methods, like contact resonance AFM (CR-AFM) or scanning near field ultrasound holography. Magnetic force microscopy can detect magnetic nanoparticles and other magnetic (bio)materials in nonmagnetic biological samples, while electric force microscopy, conductive AFM, and Kelvin probe force microscopy can reveal buried nanomaterials on the basis of the differences between their electric properties and those of the surrounding matrices. Finally, scanning near field optical microscopy and tip-enhanced Raman spectroscopy can visualize buried nanostructures on the basis of their optical and chemical properties. Despite at a still early stage, these methods are promising for detection of nanomaterials in biological systems as they could be truly noninvasive, would not require destructive and time-consuming specific sample preparation, could be performed in vitro, on alive samples and in water or physiological environment, and by continuously imaging the same sample could be used to dynamically monitor the diffusion paths and interaction mechanisms of nanomaterials into cells and biological systems. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology. © 2018 Wiley Periodicals, Inc.

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

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

Shumilov, V. N., E-mail: vnshumilov@rambler.ru; Syryamkin, V. I., E-mail: maximus70sir@gmail.com; Syryamkin, M. V., E-mail: maximus70sir@gmail.com

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervousmore » systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of formation of connections between neurons in simplest biological objects. Based on the correspondence of function of the created models to function of biological nervous systems we suggest the use of computational and electronic models of the brain for the study of its function under normal and pathological conditions, because operating principles of the models are built on principles imitating the function of biological nervous systems and the brain.« less

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

NASA Astrophysics Data System (ADS)

Shumilov, V. N.; Syryamkin, V. I.; Syryamkin, M. V.

2015-11-01

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervous systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of formation of connections between neurons in simplest biological objects. Based on the correspondence of function of the created models to function of biological nervous systems we suggest the use of computational and electronic models of the brain for the study of its function under normal and pathological conditions, because operating principles of the models are built on principles imitating the function of biological nervous systems and the brain.

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

PubMed Central

Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

Background The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. Methodology/Principal Findings To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes () and latency of the optimized engineered gene networks. Conclusions/Significance Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems. PMID:21850228

Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

PubMed

Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

Mobile-based biology edutainment application for secondary schools

NASA Astrophysics Data System (ADS)

AL-Modwahi, Ashraf Abbas M.; Kaisara, Onalenna; Parkizkar, Behrang; Habibi Lashkari, Arash

2013-03-01

The high increase of mobile technology is leading to mobilized learning environment, thus making traditional learning to diminish slowly and become inactive and unproductive. Learners worldwide are being attracted to mobile environment more so that it promotes anytime, anywhere learning. Biology as a secondary school subject will be applicable for mobile learning for such a time and generation as this. This paper is therefore an attempt to mobile based biology edutainment system for the students who normally range from the ages of thirteen to sixteen.

Structural and practical identifiability analysis of S-system.

PubMed

Zhan, Choujun; Li, Benjamin Yee Shing; Yeung, Lam Fat

2015-12-01

In the field of systems biology, biological reaction networks are usually modelled by ordinary differential equations. A sub-class, the S-systems representation, is a widely used form of modelling. Existing S-systems identification techniques assume that the system itself is always structurally identifiable. However, due to practical limitations, biological reaction networks are often only partially measured. In addition, the captured data only covers a limited trajectory, therefore data can only be considered as a local snapshot of the system responses with respect to the complete set of state trajectories over the entire state space. Hence the estimated model can only reflect partial system dynamics and may not be unique. To improve the identification quality, the structural and practical identifiablility of S-system are studied. The S-system is shown to be identifiable under a set of assumptions. Then, an application on yeast fermentation pathway was conducted. Two case studies were chosen; where the first case is based on a larger state trajectories and the second case is based on a smaller one. By expanding the dataset which span a relatively larger state space, the uncertainty of the estimated system can be reduced. The results indicated that initial concentration is related to the practical identifiablity.

Development and Deployment of Systems-Based Approaches for the Management of Soilborne Plant Pathogens.

PubMed

Chellemi, D O; Gamliel, A; Katan, J; Subbarao, K V

2016-03-01

Biological suppression of soilborne diseases with minimal use of outside interventive actions has been difficult to achieve in high input conventional crop production systems due to the inherent risk of pest resurgence. This review examines previous approaches to the management of soilborne disease as precursors to the evolution of a systems-based approach, in which plant disease suppression through natural biological feedback mechanisms in soil is incorporated into the design and operation of cropping systems. Two case studies are provided as examples in which a systems-based approach is being developed and deployed in the production of high value crops: lettuce/strawberry production in the coastal valleys of central California (United States) and sweet basil and other herb crop production in Israel. Considerations for developing and deploying system-based approaches are discussed and operational frameworks and metrics to guide their development are presented with the goal of offering a credible alternative to conventional approaches to soilborne disease management.

Integration of systems biology with bioprocess engineering: L: -threonine production by systems metabolic engineering of Escherichia coli.

PubMed

Lee, Sang Yup; Park, Jin Hwan

2010-01-01

Random mutation and selection or targeted metabolic engineering without consideration of its impact on the entire metabolic and regulatory networks can unintentionally cause genetic alterations in the region, which is not directly related to the target metabolite. This is one of the reasons why strategies for developing industrial strains are now shifted towards targeted metabolic engineering based on systems biology, which is termed systems metabolic engineering. Using systems metabolic engineering strategies, all the metabolic engineering works are conducted in systems biology framework, whereby entire metabolic and regulatory networks are thoroughly considered in an integrated manner. The targets for purposeful engineering are selected after all possible effects on the entire metabolic and regulatory networks are thoroughly considered. Finally, the strain, which is capable of producing the target metabolite to a high level close to the theoretical maximum value, can be constructed. Here we review strategies and applications of systems biology successfully implemented on bioprocess engineering, with particular focus on developing L: -threonine production strains of Escherichia coli.

Systems biology: An emerging strategy for discovering novel pathogenetic mechanisms that promote cardiovascular disease.

PubMed

Maron, Bradley A; Leopold, Jane A

2016-09-30

Reductionist theory proposes that analyzing complex systems according to their most fundamental components is required for problem resolution, and has served as the cornerstone of scientific methodology for more than four centuries. However, technological gains in the current scientific era now allow for the generation of large datasets that profile the proteomic, genomic, and metabolomic signatures of biological systems across a range of conditions. The accessibility of data on such a vast scale has, in turn, highlighted the limitations of reductionism, which is not conducive to analyses that consider multiple and contemporaneous interactions between intermediates within a pathway or across constructs. Systems biology has emerged as an alternative approach to analyze complex biological systems. This methodology is based on the generation of scale-free networks and, thus, provides a quantitative assessment of relationships between multiple intermediates, such as protein-protein interactions, within and between pathways of interest. In this way, systems biology is well positioned to identify novel targets implicated in the pathogenesis or treatment of diseases. In this review, the historical root and fundamental basis of systems biology, as well as the potential applications of this methodology are discussed with particular emphasis on integration of these concepts to further understanding of cardiovascular disorders such as coronary artery disease and pulmonary hypertension.

Integrated light-sheet imaging and flow-based enquiry (iLIFE) system for 3D in-vivo imaging of multicellular organism

NASA Astrophysics Data System (ADS)

Rasmi, Chelur K.; Padmanabhan, Sreedevi; Shirlekar, Kalyanee; Rajan, Kanhirodan; Manjithaya, Ravi; Singh, Varsha; Mondal, Partha Pratim

2017-12-01

We propose and demonstrate a light-sheet-based 3D interrogation system on a microfluidic platform for screening biological specimens during flow. To achieve this, a diffraction-limited light-sheet (with a large field-of-view) is employed to optically section the specimens flowing through the microfluidic channel. This necessitates optimization of the parameters for the illumination sub-system (illumination intensity, light-sheet width, and thickness), microfluidic specimen platform (channel-width and flow-rate), and detection sub-system (camera exposure time and frame rate). Once optimized, these parameters facilitate cross-sectional imaging and 3D reconstruction of biological specimens. The proposed integrated light-sheet imaging and flow-based enquiry (iLIFE) imaging technique enables single-shot sectional imaging of a range of specimens of varying dimensions, ranging from a single cell (HeLa cell) to a multicellular organism (C. elegans). 3D reconstruction of the entire C. elegans is achieved in real-time and with an exposure time of few hundred micro-seconds. A maximum likelihood technique is developed and optimized for the iLIFE imaging system. We observed an intracellular resolution for mitochondria-labeled HeLa cells, which demonstrates the dynamic resolution of the iLIFE system. The proposed technique is a step towards achieving flow-based 3D imaging. We expect potential applications in diverse fields such as structural biology and biophysics.

A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience.

PubMed

Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel

2012-11-01

Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control

PubMed Central

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms. PMID:25389391

Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control.

PubMed

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms.

Games network and application to PAs system.

PubMed

Chettaoui, C; Delaplace, F; Manceny, M; Malo, M

2007-02-01

In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.

Graphics processing units in bioinformatics, computational biology and systems biology.

PubMed

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

40 CFR Appendix E to Part 63 - Monitoring Procedure for Nonthoroughly Mixed Open Biological Treatment Systems at Kraft Pulp...

Code of Federal Regulations, 2012 CFR

2012-07-01

.... II. Definitions Biological treatment unit = wastewater treatment unit designed and operated to... last zone in the series and ending with the first zone. B. Data Collection Requirements This method is based upon modeling the nonthoroughly mixed open biological treatment unit as a series of well-mixed...

New applications in EPA’s ECOTOX Knowledge System: Assimilating relative potencies of metals across chemical and biological species from literature-based toxicity effects data.

EPA Science Inventory

Toxicity of metals in field settings can vary widely among ionic chemical species and across biological receptors. Thus, a challenge often found in developing TRVs for the risk assessment of metals is identifying the most appropriate metal and biological species combinations for...

Biological Life Support Technologies: Commercial Opportunities

NASA Technical Reports Server (NTRS)

Nelson, Mark (Editor); Soffen, Gerald (Editor)

1990-01-01

The papers from the workshop on Biological Life Support Technologies: Commercial Opportunities are presented. The meeting attracted researchers in environmental and bioregenerative systems. The role of biological support technologies was evaluated in the context of the global environmental challenge on Earth and the space exploration initiative, with its goal of a permanent space station, lunar base, and Mars exploration.

Systems biology of personalized nutrition

PubMed Central

van Ommen, Ben; van den Broek, Tim; de Hoogh, Iris; van Erk, Marjan; van Someren, Eugene; Rouhani-Rankouhi, Tanja; Anthony, Joshua C; Hogenelst, Koen; Pasman, Wilrike; Boorsma, André; Wopereis, Suzan

2017-01-01

Abstract Personalized nutrition is fast becoming a reality due to a number of technological, scientific, and societal developments that complement and extend current public health nutrition recommendations. Personalized nutrition tailors dietary recommendations to specific biological requirements on the basis of a person’s health status and goals. The biology underpinning these recommendations is complex, and thus any recommendations must account for multiple biological processes and subprocesses occurring in various tissues and must be formed with an appreciation for how these processes interact with dietary nutrients and environmental factors. Therefore, a systems biology–based approach that considers the most relevant interacting biological mechanisms is necessary to formulate the best recommendations to help people meet their wellness goals. Here, the concept of “systems flexibility” is introduced to personalized nutrition biology. Systems flexibility allows the real-time evaluation of metabolism and other processes that maintain homeostasis following an environmental challenge, thereby enabling the formulation of personalized recommendations. Examples in the area of macro- and micronutrients are reviewed. Genetic variations and performance goals are integrated into this systems approach to provide a strategy for a balanced evaluation and an introduction to personalized nutrition. Finally, modeling approaches that combine personalized diagnosis and nutritional intervention into practice are reviewed. PMID:28969366

Detection of biological molecules using boronate-based chemical amplification and optical sensors

DOEpatents

Van Antwerp, William Peter; Mastrototaro, John Joseph; Lane, Stephen M.; Satcher, Jr., Joe H.; Darrow, Christopher B.; Peyser, Thomas A.; Harder, Jennifer

1999-01-01

Methods are provided for the determination of the concentration of biological levels of polyhydroxylated compounds, particularly glucose. The methods utilize an amplification system that is an analyte transducer immobilized in a polymeric matrix, where the system is implantable and biocompatible. Upon interrogation by an optical system, the amplification system produces a signal capable of detection external to the skin of the patient. Quantitation of the analyte of interest is achieved by measurement of the emitted signal.

Detection of biological molecules using boronate-based chemical amplification and optical sensors

DOEpatents

Van Antwerp, William Peter; Mastrototaro, John Joseph; Lane, Stephen M.; Satcher, Jr., Joe H.; Darrow, Christopher B.; Peyser, Thomas A.; Harder, Jennifer

2004-06-15

Methods are provided for the determination of the concentration of biological levels of polyhydroxylated compounds, particularly glucose. The methods utilize an amplification system that is an analyte transducer immobilized in a polymeric matrix, where the system is implantable and biocompatible. Upon interrogation by an optical system, the amplification system produces a signal capable of detection external to the skin of the patient. Quantitation of the analyte of interest is achieved by measurement of the emitted signal.

Systems Medicine: Sketching the Landscape.

PubMed

Kirschner, Marc

2016-01-01

To understand the meaning of the term Systems Medicine and to distinguish it from seemingly related other expressions currently in use, such as precision, personalized, -omics, or big data medicine, its underlying history and development into present time needs to be highlighted. Having this development in mind, it becomes evident that Systems Medicine is a genuine concept as well as a novel way of tackling the manifold complexity that occurs in nowadays clinical medicine-and not just a rebranding of what has previously been done in the past. So looking back it seems clear to many in the field that Systems Medicine has its origin in an integrative method to unravel biocomplexity, namely, Systems Biology. Here scientist by now gained useful experience that is on the verge toward implementation in clinical research and practice.Systems Medicine and Systems Biology have the same underlying theoretical principle in systems-based thinking-a methodology to understand complexity that can be traced back to ancient Greece. During the last decade, however, and due to a rapid methodological development in the life sciences and computing/IT technologies, Systems Biology has evolved from a scientific concept into an independent discipline most competent to tackle key questions of biocomplexity-with the potential to transform medicine and how it will be practiced in the future. To understand this process in more detail, the following section will thus give a short summary of the foundation of systems-based thinking and the different developmental stages including systems theory, the development of modern Systems Biology, and its transition into clinical practice. These are the components to pave the way toward Systems Medicine.

Using Petri Net Tools to Study Properties and Dynamics of Biological Systems

PubMed Central

Peleg, Mor; Rubin, Daniel; Altman, Russ B.

2005-01-01

Petri Nets (PNs) and their extensions are promising methods for modeling and simulating biological systems. We surveyed PN formalisms and tools and compared them based on their mathematical capabilities as well as by their appropriateness to represent typical biological processes. We measured the ability of these tools to model specific features of biological systems and answer a set of biological questions that we defined. We found that different tools are required to provide all capabilities that we assessed. We created software to translate a generic PN model into most of the formalisms and tools discussed. We have also made available three models and suggest that a library of such models would catalyze progress in qualitative modeling via PNs. Development and wide adoption of common formats would enable researchers to share models and use different tools to analyze them without the need to convert to proprietary formats. PMID:15561791

Engineering plant metabolism into microbes: from systems biology to synthetic biology.

PubMed

Xu, Peng; Bhan, Namita; Koffas, Mattheos A G

2013-04-01

Plant metabolism represents an enormous repository of compounds that are of pharmaceutical and biotechnological importance. Engineering plant metabolism into microbes will provide sustainable solutions to produce pharmaceutical and fuel molecules that could one day replace substantial portions of the current fossil-fuel based economy. Metabolic engineering entails targeted manipulation of biosynthetic pathways to maximize yields of desired products. Recent advances in Systems Biology and the emergence of Synthetic Biology have accelerated our ability to design, construct and optimize cell factories for metabolic engineering applications. Progress in predicting and modeling genome-scale metabolic networks, versatile gene assembly platforms and delicate synthetic pathway optimization strategies has provided us exciting opportunities to exploit the full potential of cell metabolism. In this review, we will discuss how systems and synthetic biology tools can be integrated to create tailor-made cell factories for efficient production of natural products and fuel molecules in microorganisms. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cell phone radiation exposure on brain and associated biological systems.

PubMed

Kesari, Kavindra Kumar; Siddiqui, Mohd Haris; Meena, Ramovatar; Verma, H N; Kumar, Shivendra

2013-03-01

Wireless technologies are ubiquitous today and the mobile phones are one of the prodigious output of this technology. Although the familiarization and dependency of mobile phones is growing at an alarming pace, the biological effects due to the exposure of radiations have become a subject of intense debate. The present evidence on mobile phone radiation exposure is based on scientific research and public policy initiative to give an overview of what is known of biological effects that occur at radiofrequency (RF)/ electromagnetic fields (EMFs) exposure. The conflict in conclusions is mainly because of difficulty in controlling the affecting parameters. Biological effects are dependent not only on the distance and size of the object (with respect to the object) but also on the environmental parameters. Health endpoints reported to be associated with RF include childhood leukemia, brain tumors, genotoxic effects, neurological effects and neurodegenerative diseases, immune system deregulation, allergic and inflammatory responses, infertility and some cardiovascular effects. Most of the reports conclude a reasonable suspicion of mobile phone risk that exists based on clear evidence of bio-effects which with prolonged exposures may reasonably be presumed to result in health impacts. The present study summarizes the public issue based on mobile phone radiation exposure and their biological effects. This review concludes that the regular and long term use of microwave devices (mobile phone, microwave oven) at domestic level can have negative impact upon biological system especially on brain. It also suggests that increased reactive oxygen species (ROS) play an important role by enhancing the effect of microwave radiations which may cause neurodegenerative diseases.

Modular microfluidic system for biological sample preparation

DOEpatents

Rose, Klint A.; Mariella, Jr., Raymond P.; Bailey, Christopher G.; Ness, Kevin Dean

2015-09-29

A reconfigurable modular microfluidic system for preparation of a biological sample including a series of reconfigurable modules for automated sample preparation adapted to selectively include a) a microfluidic acoustic focusing filter module, b) a dielectrophoresis bacteria filter module, c) a dielectrophoresis virus filter module, d) an isotachophoresis nucleic acid filter module, e) a lyses module, and f) an isotachophoresis-based nucleic acid filter.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

PubMed

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

Reconstructing Anaximander's biological model unveils a theory of evolution akin to Darwin's, though centuries before the birth of science.

PubMed

Trevisanato, Siro Igino

2016-08-01

Anaximander's fragments on biology report a theory of evolution, which, unlike the development of other biological systems in the ancient Aegean, is naturalistic and is not based on metaphysics. According to Anaximander, evolution affected all living beings, including humans. The first biological systems formed in an aquatic environment, and were encased in a rugged and robust envelope. Evolution progressed with modifications that enabled the formation of more dynamic biological systems. For instance, after reaching land, the robust armors around aquatic beings dried up, and became brittle, This led to the loss of the armor and the development of more mobile life forms. Anaximander's theory combines observations of animals with speculations, and as such mirrors the more famous theory of evolution by Charles Darwin expressed 24 centuries later. The poor reception received by Anaximander's model in his time, illustrates a zeitgeist that would explain the contemporary lag phase in the development of biology and, as a result, medicine, in the ancient western world.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

In silico polypharmacology of natural products.

PubMed

Fang, Jiansong; Liu, Chuang; Wang, Qi; Lin, Ping; Cheng, Feixiong

2017-04-27

Natural products with polypharmacological profiles have demonstrated promise as novel therapeutics for various complex diseases, including cancer. Currently, many gaps exist in our knowledge of which compounds interact with which targets, and experimentally testing all possible interactions is infeasible. Recent advances and developments of systems pharmacology and computational (in silico) approaches provide powerful tools for exploring the polypharmacological profiles of natural products. In this review, we introduce recent progresses and advances of computational tools and systems pharmacology approaches for identifying drug targets of natural products by focusing on the development of targeted cancer therapy. We survey the polypharmacological and systems immunology profiles of five representative natural products that are being considered as cancer therapies. We summarize various chemoinformatics, bioinformatics and systems biology resources for reconstructing drug-target networks of natural products. We then review currently available computational approaches and tools for prediction of drug-target interactions by focusing on five domains: target-based, ligand-based, chemogenomics-based, network-based and omics-based systems biology approaches. In addition, we describe a practical example of the application of systems pharmacology approaches by integrating the polypharmacology of natural products and large-scale cancer genomics data for the development of precision oncology under the systems biology framework. Finally, we highlight the promise of cancer immunotherapies and combination therapies that target tumor ecosystems (e.g. clones or 'selfish' sub-clones) via exploiting the immunological and inflammatory 'side' effects of natural products in the cancer post-genomics era. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

NMR-based Metabolomics Applications in Biological and Environmental Science

EPA Science Inventory

As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

Hypothermic temperature effects on organ survival and restoration

PubMed Central

Ishikawa, Jun; Oshima, Masamitsu; Iwasaki, Fumitaka; Suzuki, Ryoji; Park, Joonhong; Nakao, Kazuhisa; Matsuzawa-Adachi, Yuki; Mizutsuki, Taro; Kobayashi, Ayaka; Abe, Yuta; Kobayashi, Eiji; Tezuka, Katsunari; Tsuji, Takashi

2015-01-01

A three-dimensional multicellular organism maintains the biological functions of life support by using the blood circulation to transport oxygen and nutrients and to regulate body temperature for intracellular enzymatic reactions. Donor organ transplantation using low-temperature storage is used as the fundamental treatment for dysfunctional organs. However, this approach has a serious problem in that donor organs maintain healthy conditions only during short-term storage. In this study, we developed a novel liver perfusion culture system based on biological metabolism that can maintain physiological functions, including albumin synthesis, bile secretion and urea production. This system also allows for the resurrection of a severely ischaemic liver. This study represents a significant advance for the development of an ex vivo organ perfusion system based on biological metabolism. It can be used not only to address donor organ shortages but also as the basis of future regenerative organ replacement therapy. PMID:25900715

A systems biology-led insight into the role of the proteome in neurodegenerative diseases.

PubMed

Fasano, Mauro; Monti, Chiara; Alberio, Tiziana

2016-09-01

Multifactorial disorders are the result of nonlinear interactions of several factors; therefore, a reductionist approach does not appear to be appropriate. Proteomics is a global approach that can be efficiently used to investigate pathogenetic mechanisms of neurodegenerative diseases. Here, we report a general introduction about the systems biology approach and mechanistic insights recently obtained by over-representation analysis of proteomics data of cellular and animal models of Alzheimer's disease, Parkinson's disease and other neurodegenerative disorders, as well as of affected human tissues. Expert commentary: As an inductive method, proteomics is based on unbiased observations that further require validation of generated hypotheses. Pathway databases and over-representation analysis tools allow researchers to assign an expectation value to pathogenetic mechanisms linked to neurodegenerative diseases. The systems biology approach based on omics data may be the key to unravel the complex mechanisms underlying neurodegeneration.

Bacteriophage-based synthetic biology for the study of infectious diseases

PubMed Central

Lu, Timothy K.

2014-01-01

Since their discovery, bacteriophages have contributed enormously to our understanding of molecular biology as model systems. Furthermore, bacteriophages have provided many tools that have advanced the fields of genetic engineering and synthetic biology. Here, we discuss bacteriophage-based technologies and their application to the study of infectious diseases. New strategies for engineering genomes have the potential to accelerate the design of novel phages as therapies, diagnostics, and tools. Though almost a century has elapsed since their discovery, bacteriophages continue to have a major impact on modern biological sciences, especially with the growth of multidrug-resistant bacteria and interest in the microbiome. PMID:24997401

Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2018-03-26

In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

Systems biology approaches to evaluate arsenic toxicity and carcinogenicity: an overview.

PubMed

Bhattacharjee, Pritha; Chatterjee, Debmita; Singh, Keshav K; Giri, Ashok K

2013-08-01

Long term exposure to arsenic, either through groundwater, food stuff or occupational sources, results in a plethora of dermatological and non-dermatological health effects including multi-organ cancer and early mortality. Several epidemiological studies, across the globe have reported arsenic-induced health effects and cancerous outcomes; but the prevalence of such diseases varies depending on environmental factors (geographical location, exposure level), and genetic makeup (and variants thereof); which is further modulated by several other factors like ethnicity, age-sex, smoking status, diet, etc. It is also interesting to note that, chronic arsenic exposure to a similar extent, even among the same family members, result in wide inter-individual variations. To understand the adverse effect of this toxic metabolite on biological system (cellular targets), and to unravel the underlying molecular basis (at the level of transcript, proteome, or metabolite), a holistic, systems biology approach was taken. Due to the paradoxical nature and unavailability of any suitable animal model system; the literature review is primarily based on cell line and population based studies. Thus, here we present a comprehensive review on the systems biology approaches to explore the underlying mechanism of arsenic-induced carcinogenicity, along with our own observations and an overview of mitigation strategies and their effectiveness till date. Copyright © 2013 Elsevier GmbH. All rights reserved.

Thiol/disulfide redox states in signaling and sensing

PubMed Central

Go, Young-Mi; Jones, Dean P.

2015-01-01

Rapid advances in redox systems biology are creating new opportunities to understand complexities of human disease and contributions of environmental exposures. New understanding of thiol-disulfide systems have occurred during the past decade as a consequence of the discoveries that thiol and disulfide systems are maintained in kinetically controlled steady-states displaced from thermodynamic equilibrium, that a widely distributed family of NADPH oxidases produces oxidants that function in cell signaling, and that a family of peroxiredoxins utilize thioredoxin as a reductant to complement the well-studied glutathione antioxidant system for peroxide elimination and redox regulation. This review focuses on thiol/disulfide redox state in biologic systems and the knowledge base available to support development of integrated redox systems biology models to better understand the function and dysfunction of thiol-disulfide redox systems. In particular, central principles have emerged concerning redox compartmentalization and utility of thiol/disulfide redox measures as indicators of physiologic function. Advances in redox proteomics show that, in addition to functioning in protein active sites and cell signaling, cysteine residues also serve as redox sensors to integrate biologic functions. These advances provide a framework for translation of redox systems biology concepts to practical use in understanding and treating human disease. Biological responses to cadmium, a widespread environmental agent, are used to illustrate the utility of these advances to the understanding of complex pleiotropic toxicities. PMID:23356510

Technology base for microgravity horticulture

NASA Technical Reports Server (NTRS)

Sauer, R. L.; Magnuson, J. W.; Scruby, R. R.; Scheld, H. W.

1987-01-01

Advanced microgravity plant biology research and life support system development for the spacecraft environment are critically hampered by the lack of a technology base. This inadequacy stems primarily from the fact that microgravity results in a lack of convective currents and phase separation as compared to the one gravity environment. A program plan is being initiated to develop this technology base. This program will provide an iterative flight development effort that will be closely integrated with both basic science investigations and advanced life support system development efforts incorporating biological processes. The critical considerations include optimum illumination methods, root aeration, root and shoot support, and heat rejection and gas exchange in the plant canopy.

[A study of culture-based easy identification system for Malassezia].

PubMed

Kaneko, Takamasa

2011-01-01

Most species of this genus are lipid-dependent yeasts, which colonize the seborrheic part of the skin, and they have been reported to be associated with pityriasis versicolor, Malassezia folliculitis, seborrheic dermatitis, and atopic dermatitis. Malassezia have been re-classified into 7 species based on molecular biological analysis of nuclear ribosomal DNA/RNA and new Malassezia species were reported. As members of the genus Malassezia share similar morphological and biochemical characteristics, it was thought to be difficult to differentiate between them based on phenotypic features. While molecular biological techniques are the most reliable methods for identification of Malassezia, they are not available in most clinical laboratories. We studied ( i ) development of an efficient isolation media and culture based easy identification system, ( ii ) the incidence of atypical biochemical features in Malassezia species and propose a culture-based easy identification system for clinically important Malassezia species, M. globosa, M. restricta, and M. furfur.

Vertically integrated photonic multichip module architecture for vision applications

NASA Astrophysics Data System (ADS)

Tanguay, Armand R., Jr.; Jenkins, B. Keith; von der Malsburg, Christoph; Mel, Bartlett; Holt, Gary; O'Brien, John D.; Biederman, Irving; Madhukar, Anupam; Nasiatka, Patrick; Huang, Yunsong

2000-05-01

The development of a truly smart camera, with inherent capability for low latency semi-autonomous object recognition, tracking, and optimal image capture, has remained an elusive goal notwithstanding tremendous advances in the processing power afforded by VLSI technologies. These features are essential for a number of emerging multimedia- based applications, including enhanced augmented reality systems. Recent advances in understanding of the mechanisms of biological vision systems, together with similar advances in hybrid electronic/photonic packaging technology, offer the possibility of artificial biologically-inspired vision systems with significantly different, yet complementary, strengths and weaknesses. We describe herein several system implementation architectures based on spatial and temporal integration techniques within a multilayered structure, as well as the corresponding hardware implementation of these architectures based on the hybrid vertical integration of multiple silicon VLSI vision chips by means of dense 3D photonic interconnections.

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. Results We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. Conclusion We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis. PMID:18257938

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

Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih; Synthetic Biology Research Program, National University of Singapore, Singapore

Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fattymore » acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes.« less

Mix-and-match nanobiosensor design: Logical and spatial programming of biosensors using self-assembled DNA nanostructures.

PubMed

Liu, Ying; Kumar, Sriram; Taylor, Rebecca E

2018-04-06

The evergrowing need to understand and engineer biological and biochemical mechanisms has led to the emergence of the field of nanobiosensing. Structural DNA nanotechnology, encompassing methods such as DNA origami and single-stranded tiles, involves the base pairing-driven knitting of DNA into discrete one-, two-, and three-dimensional shapes at nanoscale. Such nanostructures enable a versatile design and fabrication of nanobiosensors. These systems benefit from DNA's programmability, inherent biocompatibility, and the ability to incorporate and organize functional materials such as proteins and metallic nanoparticles. In this review, we present a mix-and-match taxonomy and approach to designing nanobiosensors in which the choices of bioanalyte and transduction mechanism are fully independent of each other. We also highlight opportunities for greater complexity and programmability of these systems that are built using structural DNA nanotechnology. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Diagnostic Tools > Biosensing Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures Nanotechnology Approaches to Biology > Nanoscale Systems in Biology. © 2018 Wiley Periodicals, Inc.

General method to find the attractors of discrete dynamic models of biological systems.

PubMed

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

Production of Fatty Acid-Derived Valuable Chemicals in Synthetic Microbes

PubMed Central

Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih; Leong, Susanna Su Jan; Chang, Matthew Wook

2014-01-01

Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fatty acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes. PMID:25566540

General method to find the attractors of discrete dynamic models of biological systems

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

Stigmatized Biologies: Examining the Cumulative Effects of Oral Health Disparities for Mexican American Farmworker Children

PubMed Central

Horton, Sarah; Barker, Judith C.

2012-01-01

Severe early childhood caries (ECC) can leave lasting effects on children’s physical development, including malformed oral arches and crooked permanent dentition. This article examines the way that ECC sets up Mexican American farm worker children in the United States for lasting dental problems and social stigma as young adults. We examine the role of dietary and environmental factors in contributing to what we call “stigmatized biologies,” and that of market-based dental public health insurance systems in cementing their enduring effects. We adapt Margaret Lock’s term, local biology, to illustrate the way that biology differs not only because of culture, diet, and environment but also because of disparities in insurance coverage. By showing the long-term effects of ECC and disparate dental treatment on farmworker adults, we show how the interaction of immigrant caregiving practices and underinsurance can have lasting social effects. An examination of the long-term effects of farm worker children’s ECC illustrates the ways that market-based health care systems can create embodied differences that in turn reproduce a system of social inequality. PMID:20550093

The Physics of Open Ended Evolution

NASA Astrophysics Data System (ADS)

Adams, Alyssa M.

What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed.

Metal-mediated DNA base pairing: alternatives to hydrogen-bonded Watson-Crick base pairs.

PubMed

Takezawa, Yusuke; Shionoya, Mitsuhiko

2012-12-18

With its capacity to store and transfer the genetic information within a sequence of monomers, DNA forms its central role in chemical evolution through replication and amplification. This elegant behavior is largely based on highly specific molecular recognition between nucleobases through the specific hydrogen bonds in the Watson-Crick base pairing system. While the native base pairs have been amazingly sophisticated through the long history of evolution, synthetic chemists have devoted considerable efforts to create alternative base pairing systems in recent decades. Most of these new systems were designed based on the shape complementarity of the pairs or the rearrangement of hydrogen-bonding patterns. We wondered whether metal coordination could serve as an alternative driving force for DNA base pairing and why hydrogen bonding was selected on Earth in the course of molecular evolution. Therefore, we envisioned an alternative design strategy: we replaced hydrogen bonding with another important scheme in biological systems, metal-coordination bonding. In this Account, we provide an overview of the chemistry of metal-mediated base pairing including basic concepts, molecular design, characteristic structures and properties, and possible applications of DNA-based molecular systems. We describe several examples of artificial metal-mediated base pairs, such as Cu(2+)-mediated hydroxypyridone base pair, H-Cu(2+)-H (where H denotes a hydroxypyridone-bearing nucleoside), developed by us and other researchers. To design the metallo-base pairs we carefully chose appropriate combinations of ligand-bearing nucleosides and metal ions. As expected from their stronger bonding through metal coordination, DNA duplexes possessing metallo-base pairs exhibited higher thermal stability than natural hydrogen-bonded DNAs. Furthermore, we could also use metal-mediated base pairs to construct or induce other high-order structures. These features could lead to metal-responsive functional DNA molecules such as artificial DNAzymes and DNA machines. In addition, the metallo-base pairing system is a powerful tool for the construction of homogeneous and heterogeneous metal arrays, which can lead to DNA-based nanomaterials such as electronic wires and magnetic devices. Recently researchers have investigated these systems as enzyme replacements, which may offer an additional contribution to chemical biology and synthetic biology through the expansion of the genetic alphabet.

Magnetic skyrmion-based artificial neuron device

NASA Astrophysics Data System (ADS)

Li, Sai; Kang, Wang; Huang, Yangqi; Zhang, Xichao; Zhou, Yan; Zhao, Weisheng

2017-08-01

Neuromorphic computing, inspired by the biological nervous system, has attracted considerable attention. Intensive research has been conducted in this field for developing artificial synapses and neurons, attempting to mimic the behaviors of biological synapses and neurons, which are two basic elements of a human brain. Recently, magnetic skyrmions have been investigated as promising candidates in neuromorphic computing design owing to their topologically protected particle-like behaviors, nanoscale size and low driving current density. In one of our previous studies, a skyrmion-based artificial synapse was proposed, with which both short-term plasticity and long-term potentiation functions have been demonstrated. In this work, we further report on a skyrmion-based artificial neuron by exploiting the tunable current-driven skyrmion motion dynamics, mimicking the leaky-integrate-fire function of a biological neuron. With a simple single-device implementation, this proposed artificial neuron may enable us to build a dense and energy-efficient spiking neuromorphic computing system.

Perspective: Reaches of chemical physics in biology.

PubMed

Gruebele, Martin; Thirumalai, D

2013-09-28

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry.

Perspective: Reaches of chemical physics in biology

PubMed Central

Gruebele, Martin; Thirumalai, D.

2013-01-01

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry. PMID:24089712

Convolving engineering and medical pedagogies for training of tomorrow's health care professionals.

PubMed

Lee, Raphael C

2013-03-01

Several fundamental benefits justify why biomedical engineering and medicine should form a more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers. Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the era of molecular biology well into today's era of molecular systems biology, which focuses on understanding the rules that govern the behavior of complex living systems. This has important medical implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in molecular systems biology to higher levels of biological organization (organ, system, and organismal levels) and then to develop new medical therapeutics based on simulation and medical informatics analysis. Higher education in biological and medical sciences must adapt to a new set of training objectives. This will involve a shifting away from reductionist problem solving toward more integrative, continuum, and predictive modeling approaches which traditionally have been more associated with engineering science. Future biomedical engineers and MDs must be able to predict clinical response to therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing rules of complex system behavior and skill sets in manipulating these systems to achieve a practical desired outcome are taught. Similarly, graduate biomedical engineering programs will include more practical exposure to clinical problem solving.

A unique large-scale undergraduate research experience in molecular systems biology for non-mathematics majors.

PubMed

Kappler, Ulrike; Rowland, Susan L; Pedwell, Rhianna K

2017-05-01

Systems biology is frequently taught with an emphasis on mathematical modeling approaches. This focus effectively excludes most biology, biochemistry, and molecular biology students, who are not mathematics majors. The mathematical focus can also present a misleading picture of systems biology, which is a multi-disciplinary pursuit requiring collaboration between biochemists, bioinformaticians, and mathematicians. This article describes an authentic large-scale undergraduate research experience (ALURE) in systems biology that incorporates proteomics, bacterial genomics, and bioinformatics in the one exercise. This project is designed to engage students who have a basic grounding in protein chemistry and metabolism and no mathematical modeling skills. The pedagogy around the research experience is designed to help students attack complex datasets and use their emergent metabolic knowledge to make meaning from large amounts of raw data. On completing the ALURE, participants reported a significant increase in their confidence around analyzing large datasets, while the majority of the cohort reported good or great gains in a variety of skills including "analysing data for patterns" and "conducting database or internet searches." An environmental scan shows that this ALURE is the only undergraduate-level system-biology research project offered on a large-scale in Australia; this speaks to the perceived difficulty of implementing such an opportunity for students. We argue however, that based on the student feedback, allowing undergraduate students to complete a systems-biology project is both feasible and desirable, even if the students are not maths and computing majors. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(3):235-248, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

Biocompatibility of Resin-based Dental Materials

PubMed Central

Moharamzadeh, Keyvan; Brook, Ian M.; Van Noort, Richard

2009-01-01

Oral and mucosal adverse reactions to resin-based dental materials have been reported. Numerous studies have examined the biocompatibility of restorative dental materials and their components, and a wide range of test systems for the evaluation of the biological effects of these materials have been developed. This article reviews the biological aspects of resin-based dental materials and discusses the conventional as well as the new techniques used for biocompatibility assessment of dental materials.

Thinking on building the network cardiovasology of Chinese medicine.

PubMed

Yu, Gui; Wang, Jie

2012-11-01

With advances in complex network theory, the thinking and methods regarding complex systems have changed revolutionarily. Network biology and network pharmacology were built by applying network-based approaches in biomedical research. The cardiovascular system may be regarded as a complex network, and cardiovascular diseases may be taken as the damage of structure and function of the cardiovascular network. Although Chinese medicine (CM) is effective in treating cardiovascular diseases, its mechanisms are still unclear. With the guidance of complex network theory, network biology and network pharmacology, network-based approaches could be used in the study of CM in preventing and treating cardiovascular diseases. A new discipline-network cardiovasology of CM was, therefore, developed. In this paper, complex network theory, network biology and network pharmacology were introduced and the connotation of "disease-syndrome-formula-herb" was illustrated from the network angle. Network biology could be used to analyze cardiovascular diseases and syndromes and network pharmacology could be used to analyze CM formulas and herbs. The "network-network"-based approaches could provide a new view for elucidating the mechanisms of CM treatment.

Leaf LIMS: A Flexible Laboratory Information Management System with a Synthetic Biology Focus.

PubMed

Craig, Thomas; Holland, Richard; D'Amore, Rosalinda; Johnson, James R; McCue, Hannah V; West, Anthony; Zulkower, Valentin; Tekotte, Hille; Cai, Yizhi; Swan, Daniel; Davey, Robert P; Hertz-Fowler, Christiane; Hall, Anthony; Caddick, Mark

2017-12-15

This paper presents Leaf LIMS, a flexible laboratory information management system (LIMS) designed to address the complexity of synthetic biology workflows. At the project's inception there was a lack of a LIMS designed specifically to address synthetic biology processes, with most systems focused on either next generation sequencing or biobanks and clinical sample handling. Leaf LIMS implements integrated project, item, and laboratory stock tracking, offering complete sample and construct genealogy, materials and lot tracking, and modular assay data capture. Hence, it enables highly configurable task-based workflows and supports data capture from project inception to completion. As such, in addition to it supporting synthetic biology it is ideal for many laboratory environments with multiple projects and users. The system is deployed as a web application through Docker and is provided under a permissive MIT license. It is freely available for download at https://leaflims.github.io .

Biological and Clinical Aspects of Lanthanide Coordination Compounds

PubMed Central

Misra, Sudhindra N.; M., Indira Devi; Shukla, Ram S.

2004-01-01

The coordinating chemistry of lanthanides, relevant to the biological, biochemical and medical aspects, makes a significant contribution to understanding the basis of application of lanthanides, particularly in biological and medical systems. The importance of the applications of lanthanides, as an excellent diagnostic and prognostic probe in clinical diagnostics, and an anticancer material, is remarkably increasing. Lanthanide complexes based X-ray contrast imaging and lanthanide chelates based contrast enhancing agents for magnetic resonance imaging (MRI) are being excessively used in radiological analysis in our body systems. The most important property of the chelating agents, in lanthanide chelate complex, is its ability to alter the behaviour of lanthanide ion with which it binds in biological systems, and the chelation markedly modifies the biodistribution and excretion profile of the lanthanide ions. The chelating agents, especially aminopoly carboxylic acids, being hydrophilic, increase the proportion of their complex excreted from complexed lanthanide ion form biological systems. Lanthanide polyamino carboxylate-chelate complexes are used as contrast enhancing agents for Magnetic Resonance Imaging. Conjugation of antibodies and other tissue specific molecules to lanthanide chelates has led to a new type of specific MRI contrast agents and their conjugated MRI contrast agents with improved relaxivity, functioning in the body similar to drugs. Many specific features of contrast agent assisted MRI make it particularly effective for musculoskeletal and cerebrospinal imaging. Lanthanide-chelate contrast agents are effectively used in clinical diagnostic investigations involving cerebrospinal diseases and in evaluation of central nervous system. Chelated lanthanide complexes shift reagent aided 23Na NMR spectroscopic analysis is used in cellular, tissue and whole organ systems. PMID:18365075

Results of the Alternative Water Processor Test, A Novel Technology for Exploration Wastewater Remediation

NASA Technical Reports Server (NTRS)

Meyer, Caitlin E.; Pensinger, Stuart; Adam, Niklas; Pickering, Karen D.; Barta, Daniel; Shull, Sarah A.; Vega, Leticia M.; Lange, Kevin; Christenson, Dylan; Jackson, W. Andrew

2016-01-01

Biologically-based water recovery systems are a regenerative, low energy alternative to physiochemical processes to reclaim water from wastewater. This report summarizes the results of the Alternative Water Processor (AWP) Integrated Test, conducted from June 2013 until April 2014. The system was comprised of four (4) membrane aerated bioreactors (MABRs) to remove carbon and nitrogen from an exploration mission wastewater and a coupled forward and reverse osmosis system to remove large organic and inorganic salts from the biological system effluent. The system exceeded the overall objectives of the test by recovering 90% of the influent wastewater processed into a near potable state and a 64% reduction of consumables from the current state of the art water recovery system on the International Space Station (ISS). However, the biological system fell short of its test goals, failing to remove 75% and 90% of the influent ammonium and organic carbon, respectively. Despite not meeting its test goals, the BWP demonstrated the feasibility of an attached-growth biological system for simultaneous nitrification and denitrification, an innovative, volume- and consumable-saving design that does not require toxic pretreatment.

Nanoscale platforms for messenger RNA delivery.

PubMed

Li, Bin; Zhang, Xinfu; Dong, Yizhou

2018-05-04

Messenger RNA (mRNA) has become a promising class of drugs for diverse therapeutic applications in the past few years. A series of clinical trials are ongoing or will be initiated in the near future for the treatment of a variety of diseases. Currently, mRNA-based therapeutics mainly focuses on ex vivo transfection and local administration in clinical studies. Efficient and safe delivery of therapeutically relevant mRNAs remains one of the major challenges for their broad applications in humans. Thus, effective delivery systems are urgently needed to overcome this limitation. In recent years, numerous nanoscale biomaterials have been constructed for mRNA delivery in order to protect mRNA from extracellular degradation and facilitate endosomal escape after cellular uptake. Nanoscale platforms have expanded the feasibility of mRNA-based therapeutics, and enabled its potential applications to protein replacement therapy, cancer immunotherapy, therapeutic vaccines, regenerative medicine, and genome editing. This review focuses on recent advances, challenges, and future directions in nanoscale platforms designed for mRNA delivery, including lipid and lipid-derived nanoparticles, polymer-based nanoparticles, protein derivatives mRNA complexes, and other types of nanomaterials. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Biology-Inspired Nanomaterials > Lipid-Based Structures Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures. © 2018 Wiley Periodicals, Inc.

Applications of NMR-based metabolomics in biological and environmental research

EPA Science Inventory

As a complimentary tool to other omics platforms, metabolomics is increasingly being used by biologists to study the dynamic response of biological systems (cells, tissues, or whole organisms) under diverse physiological or pathological conditions. Metabolomics deals with the qu...

Analysis of Effects of Organizational Behavior on Evolving System of Systems Acquisition Programs Through Agent Based Modeling

DTIC Science & Technology

2013-03-01

function is based on how individualistic or collectivistic a system is. Low individualism values mean the system is more collective and is less likely...Hofstede’s cultural dimensions, integrated with a modified version of the Bak- Sneppen biological evolutionary model, this research highlights which set...14 Hofstede’s Cultural Dimensions

A Biologically-Based Alternative Water Processor for Long Duration Space Missions

NASA Technical Reports Server (NTRS)

Barta, Daniel J.; Pickering, Karen D.; Meyer, Caitlin; Pensinger, Stuart; Vega, Leticia; Flynn, Michael; Jackson, Andrew; Wheeler, Raymond

2015-01-01

A wastewater recovery system has been developed that combines novel biological and physicochemical components for recycling wastewater on long duration space missions. Functionally, this Alternative Water Processor (AWP) would replace the Urine Processing Assembly on the International Space Station and reduce or eliminate the need for the multifiltration beds of the Water Processing Assembly (WPA). At its center are two unique game changing technologies: 1) a biological water processor (BWP) to mineralize organic forms of carbon and nitrogen and 2) an advanced membrane processor (Forward Osmosis Secondary Treatment) for removal of solids and inorganic ions. The AWP is designed for recycling larger quantities of wastewater from multiple sources expected during future exploration missions, including urine, hygiene (hand wash, shower, oral and shave) and laundry. The BWP utilizes a single-stage membrane-aerated biological reactor for simultaneous nitrification and denitrification. The Forward Osmosis Secondary Treatment (FOST) system uses a combination of forward osmosis (FO) and reverse osmosis (RO), is resistant to biofouling and can easily tolerate wastewaters high in non-volatile organics and solids associated with shower and/or hand washing. The BWP was operated continuously for over 300 days. After startup, the mature biological system averaged 85% organic carbon removal and 44% nitrogen removal, close to maximum based on available carbon. The FOST has averaged 93% water recovery, with a maximum of 98%. If the wastewater is slighty acidified, ammonia rejection is optimal. This paper will provide a description of the technology and summarize results from ground-based testing using real wastewater.

An online model composition tool for system biology models

PubMed Central

2013-01-01

Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well. PMID:24006914

Anticipatory dynamics of biological systems: from molecular quantum states to evolution

NASA Astrophysics Data System (ADS)

Igamberdiev, Abir U.

2015-08-01

Living systems possess anticipatory behaviour that is based on the flexibility of internal models generated by the system's embedded description. The idea was suggested by Aristotle and is explicitly introduced to theoretical biology by Rosen. The possibility of holding the embedded internal model is grounded in the principle of stable non-equilibrium (Bauer). From the quantum mechanical view, this principle aims to minimize energy dissipation in expense of long relaxation times. The ideas of stable non-equilibrium were developed by Liberman who viewed living systems as subdivided into the quantum regulator and the molecular computer supporting coherence of the regulator's internal quantum state. The computational power of the cell molecular computer is based on the possibility of molecular rearrangements according to molecular addresses. In evolution, the anticipatory strategies are realized both as a precession of phylogenesis by ontogenesis (Berg) and as the anticipatory search of genetic fixation of adaptive changes that incorporates them into the internal model of genetic system. We discuss how the fundamental ideas of anticipation can be introduced into the basic foundations of theoretical biology.

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

Modeling biochemical transformation processes and information processing with Narrator.

PubMed

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from http://www.narrator-tool.org.

Modeling biochemical transformation processes and information processing with Narrator

PubMed Central

Mandel, Johannes J; Fuß, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-01-01

Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from . PMID:17389034

Biologically inspired adaptive walking of a quadruped robot.

PubMed

Kimura, Hiroshi; Fukuoka, Yasuhiro; Cohen, Avis H

2007-01-15

We describe here the efforts to induce a quadruped robot to walk with medium-walking speed on irregular terrain based on biological concepts. We propose the necessary conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical and the neural systems by comparing biological concepts with those necessary conditions described in physical terms. PD-controller at joints constructs the virtual spring-damper system as the viscoelasticity model of a muscle. The neural system model consists of a central pattern generator (CPG), reflexes and responses. We validate the effectiveness of the proposed neural system model control using the quadruped robots called 'Tekken1&2'. MPEG footage of experiments can be seen at http://www.kimura.is.uec.ac.jp.

[Topical issues of biological safety under current conditions. Part 2. Conceptual, terminological, and definitive framework of biological safety].

PubMed

Onishchenko, G G; Smolenskiĭ, V Iu; Ezhlova, E B; Demina, Iu V; Toporkov, V P; Toporkov, A V; Liapin, M N; Kutyrev, V V

2013-01-01

In accordance with the established conceptual base for the up-to-date broad interpretation of biological safety, and IHR (2005), developed is the notional, terminological, and definitive framework, comprising 33 elements. Key item of the nomenclature is the biological safety that is identified as population safety (individual, social, national) from direct and (or) human environment mediated (occupational, socio-economic, geopolitical infrastructures, ecological system) exposures to hazardous biological factors. Ultimate objective of the biological safety provision is to prevent and liquidate aftermaths of emergency situations of biological character either of natural or human origin (anthropogenic) arising from direct and indirect impact of the biological threats to the public health compatible with national and international security hazard. Elaborated terminological framework allows for the construction of self-sufficient semantic content for biological safety provision, subject to formalization in legislative, normative and methodological respects and indicative of improvement as regards organizational and structural-functional groundwork of the Russian Federation National chemical and biological safety system, which is to become topical issue of Part 3.

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Bio-inspired spiking neural network for nonlinear systems control.

PubMed

Pérez, Javier; Cabrera, Juan A; Castillo, Juan J; Velasco, Juan M

2018-08-01

Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more complex computation. As demonstrated by biological organisms, they are a potentially good approach to designing controllers for highly nonlinear dynamic systems in which the performance of controllers developed by conventional techniques is not satisfactory or difficult to implement. SNN-based controllers exploit their ability for online learning and self-adaptation to evolve when transferred from simulations to the real world. SNN's inherent binary and temporary way of information codification facilitates their hardware implementation compared to analog neurons. Biological neural networks often require a lower number of neurons compared to other controllers based on artificial neural networks. In this work, these neuronal systems are imitated to perform the control of non-linear dynamic systems. For this purpose, a control structure based on spiking neural networks has been designed. Particular attention has been paid to optimizing the structure and size of the neural network. The proposed structure is able to control dynamic systems with a reduced number of neurons and connections. A supervised learning process using evolutionary algorithms has been carried out to perform controller training. The efficiency of the proposed network has been verified in two examples of dynamic systems control. Simulations show that the proposed control based on SNN exhibits superior performance compared to other approaches based on Neural Networks and SNNs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Molecular Force Spectroscopy on Cells

NASA Astrophysics Data System (ADS)

Liu, Baoyu; Chen, Wei; Zhu, Cheng

2015-04-01

Molecular force spectroscopy has become a powerful tool to study how mechanics regulates biology, especially the mechanical regulation of molecular interactions and its impact on cellular functions. This force-driven methodology has uncovered a wealth of new information of the physical chemistry of molecular bonds for various biological systems. The new concepts, qualitative and quantitative measures describing bond behavior under force, and structural bases underlying these phenomena have substantially advanced our fundamental understanding of the inner workings of biological systems from the nanoscale (molecule) to the microscale (cell), elucidated basic molecular mechanisms of a wide range of important biological processes, and provided opportunities for engineering applications. Here, we review major force spectroscopic assays, conceptual developments of mechanically regulated kinetics of molecular interactions, and their biological relevance. We also present current challenges and highlight future directions.

The relativity of biological function.

PubMed

Laubichler, Manfred D; Stadler, Peter F; Prohaska, Sonja J; Nowick, Katja

2015-12-01

Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

Scale-free flow of life: on the biology, economics, and physics of the cell

PubMed Central

Kurakin, Alexei

2009-01-01

The present work is intended to demonstrate that most of the paradoxes, controversies, and contradictions accumulated in molecular and cell biology over many years of research can be readily resolved if the cell and living systems in general are re-interpreted within an alternative paradigm of biological organization that is based on the concepts and empirical laws of nonequilibrium thermodynamics. In addition to resolving paradoxes and controversies, the proposed re-conceptualization of the cell and biological organization reveals hitherto unappreciated connections among many seemingly disparate phenomena and observations, and provides new and powerful insights into the universal principles governing the emergence and organizational dynamics of living systems on each and every scale of biological organizational hierarchy, from proteins and cells to economies and ecologies. PMID:19416527

Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

PubMed

Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

2013-08-01

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Quantum Information Biology: From Information Interpretation of Quantum Mechanics to Applications in Molecular Biology and Cognitive Psychology

NASA Astrophysics Data System (ADS)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2015-10-01

We discuss foundational issues of quantum information biology (QIB)—one of the most successful applications of the quantum formalism outside of physics. QIB provides a multi-scale model of information processing in bio-systems: from proteins and cells to cognitive and social systems. This theory has to be sharply distinguished from "traditional quantum biophysics". The latter is about quantum bio-physical processes, e.g., in cells or brains. QIB models the dynamics of information states of bio-systems. We argue that the information interpretation of quantum mechanics (its various forms were elaborated by Zeilinger and Brukner, Fuchs and Mermin, and D' Ariano) is the most natural interpretation of QIB. Biologically QIB is based on two principles: (a) adaptivity; (b) openness (bio-systems are fundamentally open). These principles are mathematically represented in the framework of a novel formalism— quantum adaptive dynamics which, in particular, contains the standard theory of open quantum systems.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

Conditional lethality strains for the biological control of Anastrepha species

USDA-ARS?s Scientific Manuscript database

Pro-apoptotic cell death genes are promising candidates for biologically-based autocidal control of pest insects as demonstrated by tetracycline (tet)-suppressible systems for conditional embryonic lethality in Drosophila melanogaster (Dm) and the medfly, Ceratitis capitata (Cc). However, for medfly...

Intelligence-based anti-doping from an equine biological passport.

PubMed

Cawley, Adam T; Keledjian, John

2017-09-01

The move towards personalized medicine derived from individually focused clinical chemistry measurements has been translated by the human anti-doping movement over the past decade into developing the athlete biological passport. There is considerable potential for animal sports to adapt this model to facilitate an intelligence-based anti-doping system. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Information security management system planning for CBRN facilities

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

Lenaeu, Joseph D.; O'Neil, Lori Ross; Leitch, Rosalyn M.

The focus of this document is to provide guidance for the development of information security management system planning documents at chemical, biological, radiological, or nuclear (CBRN) facilities. It describes a risk-based approach for planning information security programs based on the sensitivity of the data developed, processed, communicated, and stored on facility information systems.

Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

PubMed

Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

2016-10-28

Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

Modular analysis of biological networks.

PubMed

Kaltenbach, Hans-Michael; Stelling, Jörg

2012-01-01

The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

PubMed

Somvanshi, Pramod Rajaram; Venkatesh, K V

2014-03-01

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Physical constraints on biological integral control design for homeostasis and sensory adaptation.

PubMed

Ang, Jordan; McMillen, David R

2013-01-22

Synthetic biology includes an effort to use design-based approaches to create novel controllers, biological systems aimed at regulating the output of other biological processes. The design of such controllers can be guided by results from control theory, including the strategy of integral feedback control, which is central to regulation, sensory adaptation, and long-term robustness. Realization of integral control in a synthetic network is an attractive prospect, but the nature of biochemical networks can make the implementation of even basic control structures challenging. Here we present a study of the general challenges and important constraints that will arise in efforts to engineer biological integral feedback controllers or to analyze existing natural systems. Constraints arise from the need to identify target output values that the combined process-plus-controller system can reach, and to ensure that the controller implements a good approximation of integral feedback control. These constraints depend on mild assumptions about the shape of input-output relationships in the biological components, and thus will apply to a variety of biochemical systems. We summarize our results as a set of variable constraints intended to provide guidance for the design or analysis of a working biological integral feedback controller. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Pushing the lipid envelope: using bio-inspired nanocomposites to understand and exploit lipid membrane limitations

NASA Astrophysics Data System (ADS)

Montano, Gabriel

Lipids serve as the organizing matrix material for biological membranes, the site of interaction of cells with the external environment. . As such, lipids play a critical role in structure/function relationships of an extraordinary number of critical biological processes. In this talk, we will look at bio-inspired membrane assemblies to better understand the roles of lipids in biological systems as well as attempt to generate materials that can mimic and potentially advance upon biological membrane processes. First, we will investigate the response of lipids to adverse conditions. In particular, I will present data that demonstrates the response of lipids to harsh conditions and how such responses can be exploited to generate nanocomposite rearrangements. I will also show the effect of adding the endotoxin lipopolysaccharide (LPS) to lipid bilayer assemblies and describe implications on our understanding of LPS organization in biological systems as well as describe induced lipid modifications that can be exploited to organize membrane composites with precise, two-dimensional geometric control. Lastly, I will describe the use of amphiphilic block copolymers to create membrane nanocomposites capable of mimicking biological systems. In particular, I will describe the use of our polymer-based membranes in creating artificial photosynthetic assemblies that rival biological systems in function in a more flexible, dynamic matrix.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

Systems and methods of detecting force and stress using tetrapod nanocrystal

DOEpatents

Choi, Charina L.; Koski, Kristie J.; Sivasankar, Sanjeevi; Alivisatos, A. Paul

2013-08-20

Systems and methods of detecting force on the nanoscale including methods for detecting force using a tetrapod nanocrystal by exposing the tetrapod nanocrystal to light, which produces a luminescent response by the tetrapod nanocrystal. The method continues with detecting a difference in the luminescent response by the tetrapod nanocrystal relative to a base luminescent response that indicates a force between a first and second medium or stresses or strains experienced within a material. Such systems and methods find use with biological systems to measure forces in biological events or interactions.

[Habitability and biological life support systems for man].

PubMed

Gazenko, O G; Grigor'ev, A I; Meleshko, G I; Shepelev, E Ia

1990-01-01

This paper discusses general concepts and specific details of the habitability of space stations and planetary bases completely isolated from the Earth for long periods of time. It emphasizes inadequacy of the present-day knowledge about natural conditions that provide a biologically acceptable environment on the Earth as well as lack of information about life support systems as a source of consumables (oxygen, water, food) and a tool for waste management. The habitability of advanced space vehicles is closely related to closed bioregenerative systems used as life support systems.

Mass Spectrometry-Based Metabolomics to Elucidate Functions in Marine Organisms and Ecosystems

PubMed Central

Goulitquer, Sophie; Potin, Philippe; Tonon, Thierry

2012-01-01

Marine systems are very diverse and recognized as being sources of a wide range of biomolecules. This review provides an overview of metabolite profiling based on mass spectrometry (MS) approaches in marine organisms and their environments, focusing on recent advances in the field. We also point out some of the technical challenges that need to be overcome in order to increase applications of metabolomics in marine systems, including extraction of chemical compounds from different matrices and data management. Metabolites being important links between genotype and phenotype, we describe added value provided by integration of data from metabolite profiling with other layers of omics, as well as their importance for the development of systems biology approaches in marine systems to study several biological processes, and to analyze interactions between organisms within communities. The growing importance of MS-based metabolomics in chemical ecology studies in marine ecosystems is also illustrated. PMID:22690147

Evolving Relevance of Neuroproteomics in Alzheimer's Disease.

PubMed

Lista, Simone; Zetterberg, Henrik; O'Bryant, Sid E; Blennow, Kaj; Hampel, Harald

2017-01-01

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

Wearable System for Acquisition and Monitoring of Biological Signals

NASA Astrophysics Data System (ADS)

Piccinini, D. J.; Andino, N. B.; Ponce, S. D.; Roberti, MA; López, y. N.

2016-04-01

This paper presents a modular, wearable system for acquisition and wireless transmission of biological signals. Configurable slaves for different signals (such as ECG, EMG, inertial sensors, and temperature) based in the ADS1294 Medical Analog Front End are connected to a Master, based in the CC3200 microcontroller, both from Texas Instruments. The slaves are configurable according to the specific application, providing versatility to the wearable system. The battery consumption is reduced, through a couple of Li-ion batteries and the circuit has also a battery charger. A custom made box was designed and fabricated in a 3D printer, preserving the requirements of low cost, low weight and safety recommendations.

Synthetic Nanoelectronic Probes for Biological Cells and Tissue

PubMed Central

2013-01-01

Research at the interface between nanoscience and biology has the potential to produce breakthroughs in fundamental science and lead to revolutionary technologies. In this review, we focus on nanoelectronic/biological interfaces. First, we discuss nanoscale field effect transistors (nanoFETs) as probes to study cellular systems, including the realization of nanoFET comparable in size to biological nanostructures involved in communication using synthesized nanowires. Second, we overview current progress in multiplexed extracellular sensing using planar nanoFET arrays. Third, we describe the design and implementation of three distinct nanoFETs used to realize the first intracellular electrical recording from single cells. Fourth, we present recent progress in merging electronic and biological systems at the 3D tissue level by using macroporous nanoelectronic scaffolds. Finally, we discuss future development in this research area, the unique challenges and opportunities, and the tremendous impact these nanoFET based technologies might have in advancing biology and medical sciences. PMID:23451719

easyDAS: Automatic creation of DAS servers

PubMed Central

2011-01-01

Background The Distributed Annotation System (DAS) has proven to be a successful way to publish and share biological data. Although there are more than 750 active registered servers from around 50 organizations, setting up a DAS server comprises a fair amount of work, making it difficult for many research groups to share their biological annotations. Given the clear advantage that the generalized sharing of relevant biological data is for the research community it would be desirable to facilitate the sharing process. Results Here we present easyDAS, a web-based system enabling anyone to publish biological annotations with just some clicks. The system, available at http://www.ebi.ac.uk/panda-srv/easydas is capable of reading different standard data file formats, process the data and create a new publicly available DAS source in a completely automated way. The created sources are hosted on the EBI systems and can take advantage of its high storage capacity and network connection, freeing the data provider from any network management work. easyDAS is an open source project under the GNU LGPL license. Conclusions easyDAS is an automated DAS source creation system which can help many researchers in sharing their biological data, potentially increasing the amount of relevant biological data available to the scientific community. PMID:21244646

Impact of calcium and TOC on biological acidification assessment in Norwegian rivers.

PubMed

Schneider, Susanne C

2011-02-15

Acidification continues to be a major impact in freshwaters of northern Europe, and the biotic response to chemical recovery from acidification is often not a straightforward process. The focus on biological recovery is relevant within the context of the EU Water Framework Directive, where a biological monitoring system is needed that detects differences in fauna and flora compared to undisturbed reference conditions. In order to verify true reference sites for biological analyses, expected river pH is modeled based on Ca and TOC, and 94% of variability in pH at reference sites is explained by Ca alone, while 98% is explained by a combination of Ca and TOC. Based on 59 samples from 28 reference sites, compared to 547 samples from 285 non-reference sites, the impact of calcium and total organic carbon (TOC) on benthic algae species composition, expressed as acidification index periphyton (AIP), is analyzed. Rivers with a high Ca concentration have a naturally higher AIP, and TOC affects reference AIP only at low Ca concentrations. Four biological river types are needed for assessment of river acidification in Norway based on benthic algae: very calcium-poor, humic rivers (Ca<1 mg/l and TOC>2 mg/l); very calcium-poor, clear rivers (Ca<1 mg/l and TOC<2 mg/l); calcium-poor rivers (Ca between 1 and 4 mg/l); moderately calcium rich rivers (Ca>4 mg/l). A biological assessment system for river acidification in Norway based on benthic algae is presented, following the demands of the Water Framework Directive. Copyright © 2010 Elsevier B.V. All rights reserved.

Enhancing the role of veterinary vaccines reducing zoonotic diseases of humans: Linking systems biology with vaccine development

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

Adams, Leslie G.; Khare, Sangeeta; Lawhon, Sara D.

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhancedmore » approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic *sipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host's biosignatures to each infectious condition. Through this DBN computational approach, the method identified significantly perturbed pathways and GO category groups of genes that define the pathogenicity signatures of the infectious agent. Our preliminary results provide deeper understanding of the overall complexity of host innate immune response as well as the identification of host gene perturbations that defines a unique host temporal biosignature response to each pathogen. The application of advanced computational methods for developing interactome models based on DBNs has proven to be instrumental in elucidating novel host responses and improved functional biological insight into the host defensive mechanisms. Evaluating the unique differences in pathway and GO perturbations across pathogen conditions allowed the identification of plausible host pathogen interaction mechanisms. Accordingly, a systems biology approach to study molecular pathway gene expression profiles of host cellular responses to microbial pathogens holds great promise as a methodology to identify, model and predict the overall dynamics of the host pathogen interactome. Thus, we propose that such an approach has immediate application to the rational design of brucellosis and salmonellosis vaccines.« less

Enhancing the role of veterinary vaccines reducing zoonotic diseases of humans: linking systems biology with vaccine development.

PubMed

Adams, L Garry; Khare, Sangeeta; Lawhon, Sara D; Rossetti, Carlos A; Lewin, Harris A; Lipton, Mary S; Turse, Joshua E; Wylie, Dennis C; Bai, Yu; Drake, Kenneth L

2011-09-22

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhanced approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host-pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic ΔsipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host's biosignatures to each infectious condition. Through this DBN computational approach, the method identified significantly perturbed pathways and GO category groups of genes that define the pathogenicity signatures of the infectious agent. Our preliminary results provide deeper understanding of the overall complexity of host innate immune response as well as the identification of host gene perturbations that defines a unique host temporal biosignature response to each pathogen. The application of advanced computational methods for developing interactome models based on DBNs has proven to be instrumental in elucidating novel host responses and improved functional biological insight into the host defensive mechanisms. Evaluating the unique differences in pathway and GO perturbations across pathogen conditions allowed the identification of plausible host-pathogen interaction mechanisms. Accordingly, a systems biology approach to study molecular pathway gene expression profiles of host cellular responses to microbial pathogens holds great promise as a methodology to identify, model and predict the overall dynamics of the host-pathogen interactome. Thus, we propose that such an approach has immediate application to the rational design of brucellosis and salmonellosis vaccines. Copyright © 2011 Elsevier Ltd. All rights reserved.

Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is.

PubMed

Benson, Neil

2015-08-01

Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way. Copyright © 2015 Elsevier Ltd. All rights reserved.

Energy utilization in fluctuating biological energy converters

PubMed Central

Szőke, Abraham; Hajdu, Janos

2016-01-01

We have argued previously [Szoke et al., FEBS Lett. 553, 18–20 (2003); Curr. Chem. Biol. 1, 53–57 (2007)] that energy utilization and evolution are emergent properties based on a small number of established laws of physics and chemistry. The relevant laws constitute a framework for biology on a level intermediate between quantum chemistry and cell biology. There are legitimate questions whether these concepts are valid at the mesoscopic level. Such systems fluctuate appreciably, so it is not clear what their efficiency is. Advances in fluctuation theorems allow the description of such systems on a molecular level. We attempt to clarify this topic and bridge the biochemical and physical descriptions of mesoscopic systems. PMID:27191009

System Theory and Physiological Processes.

PubMed

Jones, R W

1963-05-03

Engineers and physiologists working together in experimental and theoretical studies predict that the application of system analysis to biological processes will increase understanding of these processes and broaden the base of system theory. Richard W. Jones, professor of electrical engineering at Northwestern University, Evanston, Illinois, and John S. Gray, professor of physiology at Northwestern's Medical School, discuss these developments. Their articles are adapted from addresses delivered in Chicago in November 1962 at the 15th Annual Conference on Engineering in Medicine and Biology.

Spatiotemporal Symmetry in Rings of Coupled Biological Oscillators of Physarum Plasmodial Slime Mold

NASA Astrophysics Data System (ADS)

Takamatsu, Atsuko; Tanaka, Reiko; Yamada, Hiroyasu; Nakagaki, Toshiyuki; Fujii, Teruo; Endo, Isao

2001-08-01

Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

Spatiotemporal symmetry in rings of coupled biological oscillators of Physarum plasmodial slime mold.

PubMed

Takamatsu, A; Tanaka, R; Yamada, H; Nakagaki, T; Fujii, T; Endo, I

2001-08-13

Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

Model-based design of experiments for cellular processes.

PubMed

Chakrabarty, Ankush; Buzzard, Gregery T; Rundell, Ann E

2013-01-01

Model-based design of experiments (MBDOE) assists in the planning of highly effective and efficient experiments. Although the foundations of this field are well-established, the application of these techniques to understand cellular processes is a fertile and rapidly advancing area as the community seeks to understand ever more complex cellular processes and systems. This review discusses the MBDOE paradigm along with applications and challenges within the context of cellular processes and systems. It also provides a brief tutorial on Fisher information matrix (FIM)-based and Bayesian experiment design methods along with an overview of existing software packages and computational advances that support MBDOE application and adoption within the Systems Biology community. As cell-based products and biologics progress into the commercial sector, it is anticipated that MBDOE will become an essential practice for design, quality control, and production. Copyright © 2013 Wiley Periodicals, Inc.

Nanomaterial-based electrochemical sensors for arsenic - A review.

PubMed

Kempahanumakkagari, Sureshkumar; Deep, Akash; Kim, Ki-Hyun; Kumar Kailasa, Suresh; Yoon, Hye-On

2017-09-15

The existence of arsenic in the environment poses severe global health threats. Considering its toxicity, the sensing of arsenic is extremely important. Due to the complexity of environmental and biological samples, many of the available detection methods for arsenic have serious limitations on selectivity and sensitivity. To improve sensitivity and selectivity and to circumvent interferences, different electrode systems have been developed based on surface modification with nanomaterials including carbonaceous nanomaterials, metallic nanoparticles (MNPs), metal nanotubes (MNTs), and even enzymes. Despite the progress made in electrochemical sensing of arsenic, some issues still need to be addressed to realize cost effective, portable, and flow-injection type sensor systems. The present review provides an in-depth evaluation of the nanoparticle-modified electrode (NME) based methods for the electrochemical sensing of arsenic. NME based sensing systems are projected to become an important option for monitoring hazardous pollutants in both environmental and biological media. Copyright © 2017 Elsevier B.V. All rights reserved.

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track

PubMed Central

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users—learning BEL, working with a completely new interface, and performing complex curation—a score so close to the overall SUS average highlights the usability of BELIEF. Database URL: BELIEF is available at http://www.scaiview.com/belief/ PMID:27694210

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

PubMed

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/. © The Author(s) 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Construction of new synthetic biology tools for the control of gene expression in the cyanobacterium Synechococcus sp. strain PCC 7002.

PubMed

Zess, Erin K; Begemann, Matthew B; Pfleger, Brian F

2016-02-01

Predictive control of gene expression is an essential tool for developing synthetic biological systems. The current toolbox for controlling gene expression in cyanobacteria is a barrier to more in-depth genetic analysis and manipulation. Towards relieving this bottleneck, this work describes the use of synthetic biology to construct an anhydrotetracycline-based induction system and adapt a trans-acting small RNA (sRNA) system for use in the cyanobacterium Synechococcus sp. strain PCC 7002. An anhydrotetracycline-inducible promoter was developed to maximize intrinsic strength and dynamic range. The resulting construct, PEZtet , exhibited tight repression and a maximum 32-fold induction upon addition of anhydrotetracycline. Additionally, a sRNA system based on the Escherichia coli IS10 RNA-IN/OUT regulator was adapted for use in Synechococcus sp. strain PCC 7002. This system exhibited 70% attenuation of target gene expression, providing a demonstration of the use of sRNAs for differential gene expression in cyanobacteria. These systems were combined to produce an inducible sRNA system, which demonstrated 59% attenuation of target gene expression. Lastly, the role of Hfq, a critical component of sRNA systems in E. coli, was investigated. Genetic studies showed that the Hfq homolog in Synechococcus sp. strain PCC 7002 did not impact repression by the engineered sRNA system. In summary, this work describes new synthetic biology tools that can be applied to physiological studies, metabolic engineering, or sRNA platforms in Synechococcus sp. strain PCC 7002. © 2015 Wiley Periodicals, Inc.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

A multimodal imaging platform with integrated simultaneous photoacoustic microscopy, optical coherence tomography, optical Doppler tomography and fluorescence microscopy

NASA Astrophysics Data System (ADS)

Dadkhah, Arash; Zhou, Jun; Yeasmin, Nusrat; Jiao, Shuliang

2018-02-01

Various optical imaging modalities with different optical contrast mechanisms have been developed over the past years. Although most of these imaging techniques are being used in many biomedical applications and researches, integration of these techniques will allow researchers to reach the full potential of these technologies. Nevertheless, combining different imaging techniques is always challenging due to the difference in optical and hardware requirements for different imaging systems. Here, we developed a multimodal optical imaging system with the capability of providing comprehensive structural, functional and molecular information of living tissue in micrometer scale. This imaging system integrates photoacoustic microscopy (PAM), optical coherence tomography (OCT), optical Doppler tomography (ODT) and fluorescence microscopy in one platform. Optical-resolution PAM (OR-PAM) provides absorption-based imaging of biological tissues. Spectral domain OCT is able to provide structural information based on the scattering property of biological sample with no need for exogenous contrast agents. In addition, ODT is a functional extension of OCT with the capability of measurement and visualization of blood flow based on the Doppler effect. Fluorescence microscopy allows to reveal molecular information of biological tissue using autofluoresce or exogenous fluorophores. In-vivo as well as ex-vivo imaging studies demonstrated the capability of our multimodal imaging system to provide comprehensive microscopic information on biological tissues. Integrating all the aforementioned imaging modalities for simultaneous multimodal imaging has promising potential for preclinical research and clinical practice in the near future.

Using Hi-FAME (High Feedback-Assessment-Multimedia-Environment) Instructional Model in WBI: A Case Study for Biology Teacher Education.

ERIC Educational Resources Information Center

Wang, Tzu-Hua; Wang, Wei-Lung; Wang, Kuo-Hua; Huang, Shih-Chieh

The study attempted to adapt two web tools, FFS system (Frontpage Feedback System) and WATA system (Web-based Assessment and Test Analysis System), to construct a Hi-FAME (High Feedback-Assessment-Multimedia-Environment) Model in WBI (Web-based Instruction) to facilitate pre-service teacher training. Participants were 30 junior pre-service…

Cooperative management of riparian forest habitats to maintain biological quality and ecosystem integrity

Treesearch

David Deardorff; Kathryn Wadsworth

1996-01-01

The New Mexico State Land Office has initiated a rare plant survey of state trust land, an inventory and assessment of riparian areas on the trust land, and the development of a biological resources data base and information management system. Some riparian sites that still belong to the trust have been negatively impacted by livestock such that biological quality and...

A Novel Technique for Performing Space Based Radiation Dosimetry Using DNA-Results from GRaDEx-I and the Design of GRaDEx-II

NASA Technical Reports Server (NTRS)

Ritter, Joe; Branly, R.; Theodorakis, C.; Bickham, J.; Swartz, C.; Friedfeld, R.; Ackerman, E.; Carruthers, C.; DiGirolamo, A.; Faranda, J.

1999-01-01

Because of the large amounts of cosmic radiation in the space environment relative to that on earth, the effects of radiation on the physiology of astronauts is of major concern. Doses of radiation which can cause acute or chronic biological effects are to be avoided, therefore determination of the amount of radiation exposure encountered during space flight and assessment of its impact on biological systems is critical. Quantifying the radiation dosage and damage to biological systems, especially to humans during repetitive high altitude flight and during long duration space flight is important for several reasons. Radiation can cause altered biosynthesis and long term genotoxicity resulting in cancer and birth defects etc. Radiation damage to biological systems depends in a complex way on incident radiation species and their energy spectra. Typically non-biological, i.e. film or electronic monitoring systems with narrow energy band sensitivity are used to perform dosimetry and then results are extrapolated to biological models. For this reason it may be desirable to perform radiation dosimetry by using biological molecules e.g. DNA or RNA strands as passive sensors. A lightweight genotoxicology experiment was constructed to determine the degree to which in vitro naked DNA extracted from tissues of a variety of vertebrate organisms is damaged by exposure to radiation in a space environment. The DNA is assayed by means of agarose gel electrophoresis to determine damage such as strand breakage caused by high momentum particles and photons, and base oxidation caused by free radicals. The length distribution of DNA fragments is directly correlated with the radiation dose. It is hoped that a low mass, low cost, passive biological system to determine dose response relationship (increase in strand breaks with increase in exposure) can be developed to perform radiation dosimetry in support of long duration space flight, and to predict negative effects on biological systems (e.g. astronauts and greenhouses) in space. The payload was flown in a 2.5 cubic foot Get Away Special (GAS) container through NASA's GAS program. It was subjected to the environment of the space shuttle cargo bay for the duration of the STS-91 mission (9 days). Results of the genotoxicology and radiation dosimetry experiment (GRaDEx-1) as well as the design of an improved follow on payload are presented.

A Novel Technique for Performing Space Based Radiation Dosimetry Using DNA: Results from GRaDEx-I and the Design of GRaDEx-II

NASA Technical Reports Server (NTRS)

Ritter, Joe; Branly, R.; Theodorakis, C.; Bickham, J.; Swartz, C.; Friedfeld, R.; Ackerman, E.; Carruthers, C.; DiGirolamo, A.; Faranda, J.;

NASA Space Biology Plant Research for 2010-2020

NASA Technical Reports Server (NTRS)

Levine, H. G.; Tomko, D. L.; Porterfield, D. M.

2012-01-01

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA's Space Biology research will optimize ISS research utilization, develop and demonstrate technology and hardware that will enable new science, and contribute to the base of fundamental knowledge that will facilitate development of new tools for human space exploration and Earth applications. By taking these steps, NASA will energize the Space Biology user community and advance our knowledge of the effect of the space flight environment on living systems.

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB.

PubMed

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K

2011-04-15

The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information. klingbeil@maths.ox.ac.uk Supplementary data are available at Bioinformatics online.

BIOLOGICALLY ENHANCED OXYGEN TRANSFER IN THE ACTIVATED SLUDGE PROCESS (JOURNAL)

EPA Science Inventory

Biologically enhanced oxgyen transfer has been a hypothesis to explain observed oxygen transfer rates in activated sludge systems that were well above that predicted from aerator clean-water testing. The enhanced oxygen transfer rates were based on tests using BOD bottle oxygen ...

Mobilizing the rhizosphere microbiome to enhance orchard system resilience

USDA-ARS?s Scientific Manuscript database

Soils possess a wealth of biological resources that can be harnessed for use in the optimization of plant performance in agroecosystems. Functional biological control outcomes, beyond those realized based upon introduction of synthetic microbiomes, have been documented in a variety of instances, an...

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

PubMed Central

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-01-01

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era. PMID:27649151

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.

PubMed

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-09-14

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

Advancing "Bio" Sensor Integration with Ocean Observing Systems to Support Ecosystem Based Approaches

NASA Astrophysics Data System (ADS)

Moustahfid, H.; Michaels, W.

2016-02-01

The vision of the US Integrated Ocean Observing System (U.S. IOOS) is to provide information and services to the nation for enhancing our understanding of the ecosystem and climate; sustaining living marine resources; improving public health and safety; reducing impacts of natural hazards and environmental changes; and expanding support for marine commerce and transportation. In the last decade, U.S. IOOS has made considerable progress in advancing physical and chemical observing systems, while further efforts are needed to fully integrate biological observing systems into U.S. IOOS. Recent technological advances in miniature, low power "bio" sensors deployed from fixed and mobile autonomous platforms enable remote sensing of biological components ranging from plankton greater than 20 micrometer with electro-optical technology to meso-zooplankton and nekton with hydroacoustic technology. Satellite communication linked to sensing technologies provide near real-time information of the movement and behavior of the biological organisms including the large marine predators. This opens up remarkable opportunities for observing the biotic realm at critical spatio-temporal scales for understanding how environmental changes impact on the productivity and health of our oceans. Biosensor technology has matured to be operationally integrated into ocean observation systems to provide synoptic bio-physical monitoring information. The operational objectives should be clearly defined and implemented by biological and physical oceanographers to optimize the integration of biological observing into U.S IOOS which will strengthen the national observing capabilities in response to the increasing demand for ecosystem observations to support ecosystem-based approaches for the sustainability of living marine resources and healthy oceans.

Vitamin C: electron emission, free radicals and biological versatility.

PubMed

Getoff, Nikola

2013-01-01

The many-sided biological role of vitamin C (ascorbate) is briefly illustrated by specific examples. It is demonstrated that in aqueous solutions, vitamin C emits solvated electrons (e(aq)(-)), when excited in single state. Vitamin C can also react with e(aq)(-) as well as transfer them to other biological systems and thereby acts as efficient electron mediator. Based on its chemical and biological properties, it is clear that vitamin C plays a very important role in various functions in the organism alongside biochemical processes.

Systematic Biological Filter Design with a Desired I/O Filtering Response Based on Promoter-RBS Libraries.

PubMed

Hsu, Chih-Yuan; Pan, Zhen-Ming; Hu, Rei-Hsing; Chang, Chih-Chun; Cheng, Hsiao-Chun; Lin, Che; Chen, Bor-Sen

2015-01-01

In this study, robust biological filters with an external control to match a desired input/output (I/O) filtering response are engineered based on the well-characterized promoter-RBS libraries and a cascade gene circuit topology. In the field of synthetic biology, the biological filter system serves as a powerful detector or sensor to sense different molecular signals and produces a specific output response only if the concentration of the input molecular signal is higher or lower than a specified threshold. The proposed systematic design method of robust biological filters is summarized into three steps. Firstly, several well-characterized promoter-RBS libraries are established for biological filter design by identifying and collecting the quantitative and qualitative characteristics of their promoter-RBS components via nonlinear parameter estimation method. Then, the topology of synthetic biological filter is decomposed into three cascade gene regulatory modules, and an appropriate promoter-RBS library is selected for each module to achieve the desired I/O specification of a biological filter. Finally, based on the proposed systematic method, a robust externally tunable biological filter is engineered by searching the promoter-RBS component libraries and a control inducer concentration library to achieve the optimal reference match for the specified I/O filtering response.

Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't

PubMed Central

Roudi, Yasser; Nirenberg, Sheila; Latham, Peter E.

2009-01-01

One of the most critical problems we face in the study of biological systems is building accurate statistical descriptions of them. This problem has been particularly challenging because biological systems typically contain large numbers of interacting elements, which precludes the use of standard brute force approaches. Recently, though, several groups have reported that there may be an alternate strategy. The reports show that reliable statistical models can be built without knowledge of all the interactions in a system; instead, pairwise interactions can suffice. These findings, however, are based on the analysis of small subsystems. Here, we ask whether the observations will generalize to systems of realistic size, that is, whether pairwise models will provide reliable descriptions of true biological systems. Our results show that, in most cases, they will not. The reason is that there is a crossover in the predictive power of pairwise models: If the size of the subsystem is below the crossover point, then the results have no predictive power for large systems. If the size is above the crossover point, then the results may have predictive power. This work thus provides a general framework for determining the extent to which pairwise models can be used to predict the behavior of large biological systems. Applied to neural data, the size of most systems studied so far is below the crossover point. PMID:19424487

The Chemo-Biological Outreach of Nano-Biomaterials: Implications for Tissue Engineering and Regenerative Medicine.

PubMed

Kumar, Pradeep; Choonara, Yahya E; Khan, Riaz A; Pillay, Viness

2017-01-01

Nanobiomaterials can be defined as materials interacting with and influencing the biological microenvironment at a nanointerface. Recently the basic as well as applied research related to nanobiomaterials - a conjugation of nano-, material- and life-sciences - has immensely evolved for therapeutics and related biotechnology areas. The current overview focused on the potential of nanobiomaterial-based substrates towards the generation of biocompatible surfaces, tissue engineering architectures, and regenerative medicine. Emphasis was given to chemomolecular functionalization of nanobiomaterials, nanobiomaterial composites, and morphomechanically modified nanoarchetypes and their inherent chemo-biological interaction with the biological microenvironment. Additionally, recent developments in nanobiomaterial substrate design and structure, chemo-biological interface related bio-systems uses and further evolving applications in health care, therapeutics and nanomedicine were discussed herein. Furthermore, a special emphasis was placed on the nano-chemo-biological interactions inherent to various nanobiomaterial substrates in close vicinity with biological systems. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Quantitative Analysis of the Trends Exhibited by the Three Interdisciplinary Biological Sciences: Biophysics, Bioinformatics, and Systems Biology.

PubMed

Kang, Jonghoon; Park, Seyeon; Venkat, Aarya; Gopinath, Adarsh

2015-12-01

New interdisciplinary biological sciences like bioinformatics, biophysics, and systems biology have become increasingly relevant in modern science. Many papers have suggested the importance of adding these subjects, particularly bioinformatics, to an undergraduate curriculum; however, most of their assertions have relied on qualitative arguments. In this paper, we will show our metadata analysis of a scientific literature database (PubMed) that quantitatively describes the importance of the subjects of bioinformatics, systems biology, and biophysics as compared with a well-established interdisciplinary subject, biochemistry. Specifically, we found that the development of each subject assessed by its publication volume was well described by a set of simple nonlinear equations, allowing us to characterize them quantitatively. Bioinformatics, which had the highest ratio of publications produced, was predicted to grow between 77% and 93% by 2025 according to the model. Due to the large number of publications produced in bioinformatics, which nearly matches the number published in biochemistry, it can be inferred that bioinformatics is almost equal in significance to biochemistry. Based on our analysis, we suggest that bioinformatics be added to the standard biology undergraduate curriculum. Adding this course to an undergraduate curriculum will better prepare students for future research in biology.

SEEK: a systems biology data and model management platform.

PubMed

Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L; Mueller, Wolfgang; Goble, Carole

2015-07-11

Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.

A Problem-Solving Environment for Biological Network Informatics: Bio-Spice

DTIC Science & Technology

2007-06-01

user an environment to access software tools. The Dashboard is built upon the NetBeans Integrated Development Environment (IDE), an open source Java...based integration platform was demonstrated. During the subsequent six month development cycle, the first version of the NetBeans based Bio-SPICE...frameworks (OAA, NetBeans , and Systems Biology Workbench (SBW)[15]), it becomes possible for Bio-SPICE tools to truly interoperate. This interoperation

Waste treatment integration in space

NASA Technical Reports Server (NTRS)

Baresi, L.; Kern, R.

1991-01-01

The circumstances and criteria for space-based waste treatment bioregenerative life-support systems differ in many ways from those needed in terrestrial applications. In fact, the term "waste" may not even be appropriate in the context of nearly closed, cycling, ecosystems such as those under consideration. Because of these constraints there is a need for innovative approaches to the problem of "materials recycling". Hybrid physico-chemico-biological systems offer advantages over both strictly physico-chemico or biological approaches that would be beneficial to material recycling. To effectively emulate terrestrial cycling, the use of various microbial consortia ("assemblies of interdependent microbes") should be seriously considered for the biological components of such systems. This paper will examine the use of consortia in the context of a hybrid-system for materials recycling in space.

Systems biology for understanding and engineering of heterotrophic oleaginous microorganisms.

PubMed

Park, Beom Gi; Kim, Minsuk; Kim, Joonwon; Yoo, Heewang; Kim, Byung-Gee

2017-01-01

Heterotrophic oleaginous microorganisms continue to draw interest as they can accumulate a large amount of lipids which is a promising feedstock for the production of biofuels and oleochemicals. Nutrient limitation, especially nitrogen limitation, is known to effectively trigger the lipid production in these microorganisms. For the aim of developing improved strains, the mechanisms behind the lipid production have been studied for a long time. Nowadays, system-level understanding of their metabolism and associated metabolic switches is attainable with modern systems biology tools. This work reviews the systems biology studies, based on (i) top-down, large-scale 'omics' tools, and (ii) bottom-up, mathematical modeling methods, on the heterotrophic oleaginous microorganisms with an emphasis on further application to metabolic engineering. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SynBioSS-aided design of synthetic biological constructs.

PubMed

Kaznessis, Yiannis N

2011-01-01

We present walkthrough examples of using SynBioSS to design, model, and simulate synthetic gene regulatory networks. SynBioSS stands for Synthetic Biology Software Suite, a platform that is publicly available with Open Licenses at www.synbioss.org. An important aim of computational synthetic biology is the development of a mathematical modeling formalism that is applicable to a wide variety of simple synthetic biological constructs. SynBioSS-based modeling of biomolecular ensembles that interact away from the thermodynamic limit and not necessarily at steady state affords for a theoretical framework that is generally applicable to known synthetic biological systems, such as bistable switches, AND gates, and oscillators. Here, we discuss how SynBioSS creates links between DNA sequences and targeted dynamic phenotypes of these simple systems. Copyright © 2011 Elsevier Inc. All rights reserved.

System and method for deriving a process-based specification

NASA Technical Reports Server (NTRS)

Hinchey, Michael Gerard (Inventor); Rouff, Christopher A. (Inventor); Rash, James Larry (Inventor)

2009-01-01

A system and method for deriving a process-based specification for a system is disclosed. The process-based specification is mathematically inferred from a trace-based specification. The trace-based specification is derived from a non-empty set of traces or natural language scenarios. The process-based specification is mathematically equivalent to the trace-based specification. Code is generated, if applicable, from the process-based specification. A process, or phases of a process, using the features disclosed can be reversed and repeated to allow for an interactive development and modification of legacy systems. The process is applicable to any class of system, including, but not limited to, biological and physical systems, electrical and electro-mechanical systems in addition to software, hardware and hybrid hardware-software systems.

Systems biology-based diagnostic principles as pillars of the bridge between Chinese and Western medicine.

PubMed

van der Greef, Jan; van Wietmarschen, Herman; Schroën, Jan; Wang, Mei; Hankemeier, Thomas; Xu, Guowang

2010-12-01

Innovative systems approaches to develop medicine and health care are emerging from the integration of Chinese and Western medicine strategies, philosophies and practices. The two medical systems are highly complementary as the reductionist aspects of Western medicine are favourable in acute disease situations and the holistic aspects of Chinese medicine offer more opportunities in chronic conditions and for prevention. In this article we argue that diagnosis plays a key role in building the bridge between Chinese and Western medicine. Recent advances in the study of health, healing, placebo effects and patient-physician interactions will be discussed pointing out the development of a system-based diagnosis. Especially, a system biology-based diagnosis can be used to capture phenotype information, leading towards a scientific basis for a more refined patient characterization, new diagnostic tools and personalized heath strategies. Subtyping of rheumatoid arthritis patients based on Chinese diagnostic principles is discussed as an example. New insights from this process of integrating Western and Chinese medicine will pave the way for a patient-centred health care ecosystem. © Georg Thieme Verlag KG Stuttgart · New York.

Microscopic video observation of capillary vessel systems using diffuse back lighting

NASA Astrophysics Data System (ADS)

Sakai, Minako; Arai, Hiroki; Iwai, Toshiaki

2017-04-01

We have been developing a simple and practical video microscopy system based on absorption spectra of biological substance to perform spectroscopic observation of living tissues. The diffuse backlighting effect is actively used in the developed system, which is generated by multiple light scattering in the tissue. It is demonstrated that the light specularly reflected from the skin surface can be completely suppressed in the microscopic observation and the biological activity of the capillary vessel systems distributed under the skin can be successfully observed. As a result, we can confirm the effectiveness of the video microscopy system using diffuse backlighting and the applicability of our developed system.

Phenomenological and molecular-level Petri net modeling and simulation of long-term potentiation.

PubMed

Hardy, S; Robillard, P N

2005-10-01

Petri net-based modeling methods have been used in many research projects to represent biological systems. Among these, the hybrid functional Petri net (HFPN) was developed especially for biological modeling in order to provide biologists with a more intuitive Petri net-based method. In the literature, HFPNs are used to represent kinetic models at the molecular level. We present two models of long-term potentiation previously represented by differential equations which we have transformed into HFPN models: a phenomenological synapse model and a molecular-level model of the CaMKII regulation pathway. Through simulation, we obtained results similar to those of previous studies using these models. Our results open the way to a new type of modeling for systems biology where HFPNs are used to combine different levels of abstraction within one model. This approach can be useful in fully modeling a system at the molecular level when kinetic data is missing or when a full study of a system at the molecular level it is not within the scope of the research.

Integrating biological redesign: where synthetic biology came from and where it needs to go.

PubMed

Way, Jeffrey C; Collins, James J; Keasling, Jay D; Silver, Pamela A

2014-03-27

Synthetic biology seeks to extend approaches from engineering and computation to redesign of biology, with goals such as generating new chemicals, improving human health, and addressing environmental issues. Early on, several guiding principles of synthetic biology were articulated, including design according to specification, separation of design from fabrication, use of standardized biological parts and organisms, and abstraction. We review the utility of these principles over the past decade in light of the field's accomplishments in building complex systems based on microbial transcription and metabolism and describe the progress in mammalian cell engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

Modeling biology with HDL languages: a first step toward a genetic design automation tool inspired from microelectronics.

PubMed

Gendrault, Yves; Madec, Morgan; Lallement, Christophe; Haiech, Jacques

2014-04-01

Nowadays, synthetic biology is a hot research topic. Each day, progresses are made to improve the complexity of artificial biological functions in order to tend to complex biodevices and biosystems. Up to now, these systems are handmade by bioengineers, which require strong technical skills and leads to nonreusable development. Besides, scientific fields that share the same design approach, such as microelectronics, have already overcome several issues and designers succeed in building extremely complex systems with many evolved functions. On the other hand, in systems engineering and more specifically in microelectronics, the development of the domain has been promoted by both the improvement of technological processes and electronic design automation tools. The work presented in this paper paves the way for the adaptation of microelectronics design tools to synthetic biology. Considering the similarities and differences between the synthetic biology and microelectronics, the milestones of this adaptation are described. The first one concerns the modeling of biological mechanisms. To do so, a new formalism is proposed, based on an extension of the generalized Kirchhoff laws to biology. This way, a description of all biological mechanisms can be made with languages widely used in microelectronics. Our approach is therefore successfully validated on specific examples drawn from the literature.

The semiotics of control and modeling relations in complex systems.

PubMed

Joslyn, C

2001-01-01

We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

Challenges and Rewards on the Road to Translational Systems Biology in Acute Illness: Four Case Reports from Interdisciplinary Teams

PubMed Central

An, Gary; Hunt, C. Anthony; Clermont, Gilles; Neugebauer, Edmund; Vodovotz, Yoram

2007-01-01

Introduction Translational systems biology approaches can be distinguished from mainstream systems biology in that their goal is to drive novel therapies and streamline clinical trials in critical illness. One systems biology approach, dynamic mathematical modeling (DMM), is increasingly used in dealing with the complexity of the inflammatory response and organ dysfunction. The use of DMM often requires a broadening of research methods and a multidisciplinary team approach that includes bioscientists, mathematicians, engineers, and computer scientists. However, the development of these groups must overcome domain-specific barriers to communication and understanding. Methods We present four case studies of successful translational, interdisciplinary systems biology efforts, which differ by organizational level from an individual to an entire research community. Results Case 1 is a single investigator involved in DMM of the acute inflammatory response at Cook County Hospital, in which extensive translational progress was made using agent-based models of inflammation and organ damage. Case 2 is a community-level effort from the University of Witten-Herdecke in Cologne, whose efforts have led to the formation of the Society for Complexity in Acute Illness. Case 3 is an institution-based group, the Biosystems Group at the University of California, San Francisco, whose work has included a focus on a common lexicon for DMM. Case 4 is an institution-based, trans-disciplinary research group (the Center for Inflammation and Regenerative Modeling at the University of Pittsburgh, whose modeling work has led to internal education efforts, grant support, and commercialization. Conclusion A transdisciplinary approach, which involves team interaction in an iterative fashion to address ambiguity and is supported by educational initiatives, is likely to be necessary for DMM in acute illness. Community-wide organizations such as the Society of Complexity in Acute Illness (SCAI) must strive to facilitate the implementation of DMM in sepsis/trauma research into the research community as a whole. PMID:17548029

Erythrocytes-based synthetic delivery systems: transition from conventional to novel engineering strategies.

PubMed

Bhateria, Manisha; Rachumallu, Ramakrishna; Singh, Rajbir; Bhatta, Rabi Sankar

2014-08-01

Erythrocytes (red blood cells [RBCs]) and artificial or synthetic delivery systems such as liposomes, nanoparticles (NPs) are the most investigated carrier systems. Herein, progress made from conventional approach of using RBC as delivery systems to novel approach of using synthetic delivery systems based on RBC properties will be reviewed. We aim to highlight both conventional and novel approaches of using RBCs as potential carrier system. Conventional approaches which include two main strategies are: i) directly loading therapeutic moieties in RBCs; and ii) coupling them with RBCs whereas novel approaches exploit structural, mechanical and biological properties of RBCs to design synthetic delivery systems through various engineering strategies. Initial attempts included coupling of antibodies to liposomes to specifically target RBCs. Knowledge obtained from several studies led to the development of RBC membrane derived liposomes (nanoerythrosomes), inspiring future application of RBC or its structural features in other attractive delivery systems (hydrogels, filomicelles, microcapsules, micro- and NPs) for even greater potential. In conclusion, this review dwells upon comparative analysis of various conventional and novel engineering strategies in developing RBC based drug delivery systems, diversifying their applications in arena of drug delivery. Regardless of the challenges in front of us, RBC based delivery systems offer an exciting approach of exploiting biological entities in a multitude of medical applications.

Machine vision for digital microfluidics

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun; Lee, Jeong-Bong

2010-01-01

Machine vision is widely used in an industrial environment today. It can perform various tasks, such as inspecting and controlling production processes, that may require humanlike intelligence. The importance of imaging technology for biological research or medical diagnosis is greater than ever. For example, fluorescent reporter imaging enables scientists to study the dynamics of gene networks with high spatial and temporal resolution. Such high-throughput imaging is increasingly demanding the use of machine vision for real-time analysis and control. Digital microfluidics is a relatively new technology with expectations of becoming a true lab-on-a-chip platform. Utilizing digital microfluidics, only small amounts of biological samples are required and the experimental procedures can be automatically controlled. There is a strong need for the development of a digital microfluidics system integrated with machine vision for innovative biological research today. In this paper, we show how machine vision can be applied to digital microfluidics by demonstrating two applications: machine vision-based measurement of the kinetics of biomolecular interactions and machine vision-based droplet motion control. It is expected that digital microfluidics-based machine vision system will add intelligence and automation to high-throughput biological imaging in the future.

Systems biology approach to developing S(2)RM-based "systems therapeutics" and naturally induced pluripotent stem cells.

PubMed

Maguire, Greg; Friedman, Peter

2015-05-26

The degree to, and the mechanisms through, which stem cells are able to build, maintain, and heal the body have only recently begun to be understood. Much of the stem cell's power resides in the release of a multitude of molecules, called stem cell released molecules (SRM). A fundamentally new type of therapeutic, namely "systems therapeutic", can be realized by reverse engineering the mechanisms of the SRM processes. Recent data demonstrates that the composition of the SRM is different for each type of stem cell, as well as for different states of each cell type. Although systems biology has been successfully used to analyze multiple pathways, the approach is often used to develop a small molecule interacting at only one pathway in the system. A new model is emerging in biology where systems biology is used to develop a new technology acting at multiple pathways called "systems therapeutics". A natural set of healing pathways in the human that uses SRM is instructive and of practical use in developing systems therapeutics. Endogenous SRM processes in the human body use a combination of SRM from two or more stem cell types, designated as S(2)RM, doing so under various state dependent conditions for each cell type. Here we describe our approach in using state-dependent SRM from two or more stem cell types, S(2)RM technology, to develop a new class of therapeutics called "systems therapeutics." Given the ubiquitous and powerful nature of innate S(2)RM-based healing in the human body, this "systems therapeutic" approach using S(2)RM technology will be important for the development of anti-cancer therapeutics, antimicrobials, wound care products and procedures, and a number of other therapeutics for many indications.

Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods

PubMed Central

2015-01-01

Background Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. Methods In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. Results We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. Conclusions Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy. PMID:26680552

Additive manufacturing of biologically-inspired materials.

PubMed

Studart, André R

2016-01-21

Additive manufacturing (AM) technologies offer an attractive pathway towards the fabrication of functional materials featuring complex heterogeneous architectures inspired by biological systems. In this paper, recent research on the use of AM approaches to program the local chemical composition, structure and properties of biologically-inspired materials is reviewed. A variety of structural motifs found in biological composites have been successfully emulated in synthetic systems using inkjet-based, direct-writing, stereolithography and slip casting technologies. The replication in synthetic systems of design principles underlying such structural motifs has enabled the fabrication of lightweight cellular materials, strong and tough composites, soft robots and autonomously shaping structures with unprecedented properties and functionalities. Pushing the current limits of AM technologies in future research should bring us closer to the manufacturing capabilities of living organisms, opening the way for the digital fabrication of advanced materials with superior performance, lower environmental impact and new functionalities.

Advanced treatment of biologically pretreated coal gasification wastewater by a novel integration of heterogeneous Fenton oxidation and biological process.

PubMed

Xu, Peng; Han, Hongjun; Zhuang, Haifeng; Hou, Baolin; Jia, Shengyong; Xu, Chunyan; Wang, Dexin

2015-04-01

Laboratorial scale experiments were conducted in order to investigate a novel system integrating heterogeneous Fenton oxidation (HFO) with anoxic moving bed biofilm reactor (ANMBBR) and biological aerated filter (BAF) process on advanced treatment of biologically pretreated coal gasification wastewater (CGW). The results indicated that HFO with the prepared catalyst (FeOx/SBAC, sewage sludge based activated carbon (SBAC) which loaded Fe oxides) played a key role in eliminating COD and COLOR as well as in improving the biodegradability of raw wastewater. The surface reaction and hydroxyl radicals (OH) oxidation were the mechanisms for FeOx/SBAC catalytic reaction. Compared with ANMBBR-BAF process, the integrated system was more effective in abating COD, BOD5, total phenols (TPs), total nitrogen (TN) and COLOR and could shorten the retention time. Therefore, the integrated system was a promising technology for engineering applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biomimetic machine vision system.

PubMed

Harman, William M; Barrett, Steven F; Wright, Cameron H G; Wilcox, Michael

2005-01-01

Real-time application of digital imaging for use in machine vision systems has proven to be prohibitive when used within control systems that employ low-power single processors without compromising the scope of vision or resolution of captured images. Development of a real-time machine analog vision system is the focus of research taking place at the University of Wyoming. This new vision system is based upon the biological vision system of the common house fly. Development of a single sensor is accomplished, representing a single facet of the fly's eye. This new sensor is then incorporated into an array of sensors capable of detecting objects and tracking motion in 2-D space. This system "preprocesses" incoming image data resulting in minimal data processing to determine the location of a target object. Due to the nature of the sensors in the array, hyperacuity is achieved thereby eliminating resolutions issues found in digital vision systems. In this paper, we will discuss the biological traits of the fly eye and the specific traits that led to the development of this machine vision system. We will also discuss the process of developing an analog based sensor that mimics the characteristics of interest in the biological vision system. This paper will conclude with a discussion of how an array of these sensors can be applied toward solving real-world machine vision issues.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.

PubMed

Thiele, Ines; Hyduke, Daniel R; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan M T; Hsiung, Chao A; De Keersmaecker, Sigrid C J; Liao, Yu-Chieh; Marchal, Kathleen; Mo, Monica L; Özdemir, Emre; Raghunathan, Anu; Reed, Jennifer L; Shin, Sook-il; Sigurbjörnsdóttir, Sara; Steinmann, Jonas; Sudarsan, Suresh; Swainston, Neil; Thijs, Inge M; Zengler, Karsten; Palsson, Bernhard O; Adkins, Joshua N; Bumann, Dirk

2011-01-18

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

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

Thiele, Ines; Hyduke, Daniel R.; Steeb, Benjamin

2011-01-01

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of thismore » reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Finally, taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.« less

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.

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Quantifying control effort of biological and technical movements: an information-entropy-based approach.

PubMed

Haeufle, D F B; Günther, M; Wunner, G; Schmitt, S

2014-01-01

In biomechanics and biorobotics, muscles are often associated with reduced movement control effort and simplified control compared to technical actuators. This is based on evidence that the nonlinear muscle properties positively influence movement control. It is, however, open how to quantify the simplicity aspect of control effort and compare it between systems. Physical measures, such as energy consumption, stability, or jerk, have already been applied to compare biological and technical systems. Here a physical measure of control effort based on information entropy is presented. The idea is that control is simpler if a specific movement is generated with less processed sensor information, depending on the control scheme and the physical properties of the systems being compared. By calculating the Shannon information entropy of all sensor signals required for control, an information cost function can be formulated allowing the comparison of models of biological and technical control systems. Exemplarily applied to (bio-)mechanical models of hopping, the method reveals that the required information for generating hopping with a muscle driven by a simple reflex control scheme is only I=32 bits versus I=660 bits with a DC motor and a proportional differential controller. This approach to quantifying control effort captures the simplicity of a control scheme and can be used to compare completely different actuators and control approaches.

Nanothermite-Based Microsystem for Drug Delivery and Cell Transfection

DTIC Science & Technology

2008-12-01

micropyrotechnic-based system in which a nanothermite energy source is coupled to a biological target for gene transfer and drug delivery ... delivery of particulate vaccines and drugs to human skin with a practical, hand-held shock tube-based system . Shock Waves, 12, 23-30. Kodama, T., M...1 NANOTHERMITE-BASED MICROSYSTEM FOR DRUG DELIVERY AND CELL TRANSFECTION S. Apperson, R. Thiruvengadathan, A. Bezmelnitsyn, K. Gangopadhyay, S

Discovering the intelligence in molecular biology.

PubMed

Uberbacher, E

1995-12-01

The Third International Conference on Intelligent Systems in Molecular Biology was truly an outstanding event. Computational methods in molecular biology have reached a new level of maturity and utility, resulting in many high-impact applications. The success of this meeting bodes well for the rapid and continuing development of computational methods, intelligent systems and information-based approaches for the biosciences. The basic technology, originally most often applied to 'feasibility' problems, is now dealing effectively with the most difficult real-world problems. Significant progress has been made in understanding protein-structure information, structural classification, and how functional information and the relevant features of active-site geometry can be gleaned from structures by automated computational approaches. The value and limits of homology-based methods, and the ability to classify proteins by structure in the absence of homology, have reached a new level of sophistication. New methods for covariation analysis in the folding of large structures such as RNAs have shown remarkably good results, indicating the long-term potential to understand very complicated molecules and multimolecular complexes using computational means. Novel methods, such as HMMs, context-free grammars and the uses of mutual information theory, have taken center stage as highly valuable tools in our quest to represent and characterize biological information. A focus on creative uses of intelligent systems technologies and the trend toward biological application will undoubtedly continue and grow at the 1996 ISMB meeting in St Louis.

Recent perspectives on the delivery of biologics to back of the eye

PubMed Central

Joseph, Mary; Trinh, Hoang M.; Cholkar, Kishore; Pal, Dhananjay; Mitra, Ashim K.

2017-01-01

Introduction Biologics are generally macromolecules, large in size with poor stability in biological environments. Delivery of biologics to tissues at the back of the eye remains a challenge. To overcome these challenges and treat posterior ocular diseases, several novel approaches have been developed. Nanotechnology-based delivery systems, like drug encapsulation technology, macromolecule implants and gene delivery are under investigation. We provide an overview of emerging technologies for biologics delivery to back of the eye tissues. Moreover, new biologic drugs currently in clinical trials for ocular neovascular diseases have been discussed. Areas Covered Anatomy of the eye, posterior segment disease and diagnosis, barriers to biologic delivery, ocular pharmacokinetic, novel biologic delivery system Expert Opinion Anti-VEGF therapy represents a significant advance in developing biologics for the treatment of ocular neovascular diseases. Various strategies for biologic delivery to posterior ocular tissues are under development with some in early or late stages of clinical trials. Despite significant progress in the delivery of biologics, there is unmet need to develop sustained delivery of biologics with nearly zero-order release kinetics to the back of the eye tissues. In addition, elevated intraocular pressure associated with frequent intravitreal injections of macromolecules is another concern that needs to be addressed. PMID:27573097

Microfluidic 3D cell culture: potential application for tissue-based bioassays

PubMed Central

Li, XiuJun (James); Valadez, Alejandra V.; Zuo, Peng; Nie, Zhihong

2014-01-01

Current fundamental investigations of human biology and the development of therapeutic drugs, commonly rely on two-dimensional (2D) monolayer cell culture systems. However, 2D cell culture systems do not accurately recapitulate the structure, function, physiology of living tissues, as well as highly complex and dynamic three-dimensional (3D) environments in vivo. The microfluidic technology can provide micro-scale complex structures and well-controlled parameters to mimic the in vivo environment of cells. The combination of microfluidic technology with 3D cell culture offers great potential for in vivo-like tissue-based applications, such as the emerging organ-on-a-chip system. This article will review recent advances in microfluidic technology for 3D cell culture and their biological applications. PMID:22793034

Recent Advances in Nanomaterials for Gene Delivery—A Review

DOE PAGES

Riley, Michael; Vermerris, Wilfred

2017-04-28

With the rapid development of nanotechnology in the recent decade, novel DNA and RNA delivery systems for gene therapy have become available that can be used instead of viral vectors. These non-viral vectors can be made of a variety of materials, including inorganic nanoparticles, carbon nanotubes, liposomes, protein and peptide-based nanoparticles, as well as nanoscale polymeric materials. They have as advantages over viral vectors a decreased immune response, and additionally offer flexibility in design, allowing them to be functionalized and targeted to specific sites in a biological system with low cytotoxicity. The focus of this review is to provide anmore » overview of novel nanotechnology-based methods to deliver DNA and small interfering RNAs into biological systems.« less

Three-Dimensional Printing of Human Skeletal Muscle Cells: An Interdisciplinary Approach for Studying Biological Systems

ERIC Educational Resources Information Center

Bagley, James R.; Galpin, Andrew J.

2015-01-01

Interdisciplinary exploration is vital to education in the 21st century. This manuscript outlines an innovative laboratory-based teaching method that combines elements of biochemistry/molecular biology, kinesiology/health science, computer science, and manufacturing engineering to give students the ability to better conceptualize complex…

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

76 FR 74040 - Emerging Technology and Research Advisory Committee (ETRAC): Notice of Recruitment of Private...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-30

...-manufacturing activity in biological sciences (particularly bio electronics and synthetic biology), chemical engineering, directed energy, materials, space technologies (including satellite systems). The purpose of this... science and engineering to conduct a ``zero- based'' annual review of the list of technologies on the CCL...

River Pollution: Part II. Biological Methods for Assessing Water Quality.

ERIC Educational Resources Information Center

Openshaw, Peter

1984-01-01

Discusses methods used in the biological assessment of river quality and such indicators of clean and polluted waters as the Trent Biotic Index, Chandler Score System, and species diversity indexes. Includes a summary of a river classification scheme based on quality criteria related to water use. (JN)

Modeling languages for biochemical network simulation: reaction vs equation based approaches.

PubMed

Wiechert, Wolfgang; Noack, Stephan; Elsheikh, Atya

2010-01-01

Biochemical network modeling and simulation is an essential task in any systems biology project. The systems biology markup language (SBML) was established as a standardized model exchange language for mechanistic models. A specific strength of SBML is that numerous tools for formulating, processing, simulation and analysis of models are freely available. Interestingly, in the field of multidisciplinary simulation, the problem of model exchange between different simulation tools occurred much earlier. Several general modeling languages like Modelica have been developed in the 1990s. Modelica enables an equation based modular specification of arbitrary hierarchical differential algebraic equation models. Moreover, libraries for special application domains can be rapidly developed. This contribution compares the reaction based approach of SBML with the equation based approach of Modelica and explains the specific strengths of both tools. Several biological examples illustrating essential SBML and Modelica concepts are given. The chosen criteria for tool comparison are flexibility for constraint specification, different modeling flavors, hierarchical, modular and multidisciplinary modeling. Additionally, support for spatially distributed systems, event handling and network analysis features is discussed. As a major result it is shown that the choice of the modeling tool has a strong impact on the expressivity of the specified models but also strongly depends on the requirements of the application context.

Preservation of Specific Protein Signaling States Using Heat Based Stabilizor System.

PubMed

Borén, Mats

2017-01-01

The ability to adequately measure the phosphorylation state of a protein has major biological as well as clinical relevance. Due to its variable nature, reversible protein phosphorylations are sensitive to changes in the tissue environment. Stabilizor TM T1 is a system for rapid inactivation of enzymatic activity in biological samples. Enzyme inactivation is accomplished using thermal denaturation in a rapid, homogeneous, and reproducible fashion without the need of added chemical inhibitors. Using pCREB(Ser133) as a model system, the applicability of the Stabilizor system to preserve a rapidly lost phosphorylation is shown.

On a biologically inspired topology optimization method

NASA Astrophysics Data System (ADS)

Kobayashi, Marcelo H.

2010-03-01

This work concerns the development of a biologically inspired methodology for the study of topology optimization in engineering and natural systems. The methodology is based on L systems and its turtle interpretation for the genotype-phenotype modeling of the topology development. The topology is analyzed using the finite element method, and optimized using an evolutionary algorithm with the genetic encoding of the L system and its turtle interpretation, as well as, body shape and physical characteristics. The test cases considered in this work clearly show the suitability of the proposed method for the study of engineering and natural complex systems.

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

PubMed

Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

2009-10-15

Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich--data poor' paradox in Systems Biology.

Macro to microfluidics system for biological environmental monitoring.

PubMed

Delattre, Cyril; Allier, Cédric P; Fouillet, Yves; Jary, Dorothée; Bottausci, Frederic; Bouvier, Denis; Delapierre, Guillaume; Quinaud, Manuelle; Rival, Arnaud; Davoust, Laurent; Peponnet, Christine

2012-01-01

Biological environmental monitoring (BEM) is a growing field of research which challenges both microfluidics and system automation. The aim is to develop a transportable system with analysis throughput which satisfies the requirements: (i) fully autonomous, (ii) complete protocol integration from sample collection to final analysis, (iii) detection of diluted molecules or biological species in a large real life environmental sample volume, (iv) robustness and (v) flexibility and versatility. This paper discusses all these specifications in order to define an original fluidic architecture based on three connected modules, a sampling module, a sample preparation module and a detection module. The sample preparation module highly concentrates on the pathogens present in a few mL samples of complex and unknown solutions and purifies the pathogens' nucleic acids into a few μL of a controlled buffer. To do so, a two-step concentration protocol based on magnetic beads is automated in a reusable macro-to-micro fluidic system. The detection module is a PCR based miniaturized platform using digital microfluidics, where reactions are performed in 64 nL droplets handled by electrowetting on dielectric (EWOD) actuation. The design and manufacture of the two modules are reported as well as their respective performances. To demonstrate the integration of the complete protocol in the same system, first results of pathogen detection are shown. Copyright © 2012 Elsevier B.V. All rights reserved.

FMM: a web server for metabolic pathway reconstruction and comparative analysis.

PubMed

Chou, Chih-Hung; Chang, Wen-Chi; Chiu, Chih-Min; Huang, Chih-Chang; Huang, Hsien-Da

2009-07-01

Synthetic Biology, a multidisciplinary field, is growing rapidly. Improving the understanding of biological systems through mimicry and producing bio-orthogonal systems with new functions are two complementary pursuits in this field. A web server called FMM (From Metabolite to Metabolite) was developed for this purpose. FMM can reconstruct metabolic pathways form one metabolite to another metabolite among different species, based mainly on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and other integrated biological databases. Novel presentation for connecting different KEGG maps is newly provided. Both local and global graphical views of the metabolic pathways are designed. FMM has many applications in Synthetic Biology and Metabolic Engineering. For example, the reconstruction of metabolic pathways to produce valuable metabolites or secondary metabolites in bacteria or yeast is a promising strategy for drug production. FMM provides a highly effective way to elucidate the genes from which species should be cloned into those microorganisms based on FMM pathway comparative analysis. Consequently, FMM is an effective tool for applications in synthetic biology to produce both drugs and biofuels. This novel and innovative resource is now freely available at http://FMM.mbc.nctu.edu.tw/.

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework

PubMed Central

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

PubMed

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

Revision of species inventory checklists for Sandia National Laboratories, Albuquerque, Bernalillo County, New Mexico

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

Fischer, N.T.

1990-10-01

This report revises and updates the 1974 report by W. C. Martin and W. L. Wagner, Biological Survey of Kirtland Air Force Base (East). The biological communities of Kirtland Air Force Base (KAFB) are described with respect to the Biome classification system of Brown (1982), and a standardized system of habitat types is proposed based on biome and soil type. The potential occurrence of state or federally endangered species is discussed. No species listed as endangered or threatened is known to occur on KAFB, although five are identified as potentially occurring. Updated lists of amphibians, reptiles, breeding birds, mammals, andmore » plants are presented. 18 refs., 3 figs., 8 tabs.« less

The effectiveness of marine reserve systems constructed using different surrogates of biodiversity.

PubMed

Sutcliffe, P R; Klein, C J; Pitcher, C R; Possingham, H P

2015-06-01

Biological sampling in marine systems is often limited, and the cost of acquiring new data is high. We sought to assess whether systematic reserves designed using abiotic domains adequately conserve a comprehensive range of species in a tropical marine inter-reef system. We based our assessment on data from the Great Barrier Reef, Australia. We designed reserve systems aiming to conserve 30% of each species based on 4 abiotic surrogate types (abiotic domains; weighted abiotic domains; pre-defined bioregions; and random selection of areas). We evaluated each surrogate in scenarios with and without cost (cost to fishery) and clumping (size of conservation area) constraints. To measure the efficacy of each reserve system for conservation purposes, we evaluated how well 842 species collected at 1155 sites across the Great Barrier Reef seabed were represented in each reserve system. When reserve design included both cost and clumping constraints, the mean proportion of species reaching the conservation target was 20-27% higher for reserve systems that were biologically informed than reserves designed using unweighted environmental data. All domains performed substantially better than random, except when there were no spatial or economic constraints placed on the system design. Under the scenario with no constraints, the mean proportion of species reaching the conservation target ranged from 98.5% to 99.99% across all surrogate domains, whereas the range was 90-96% across all domains when both cost and clumping were considered. This proportion did not change considerably between scenarios where one constraint was imposed and scenarios where both cost and clumping constraints were considered. We conclude that representative reserve systems can be designed using abiotic domains; however, there are substantial benefits if some biological information is incorporated. © 2015 Society for Conservation Biology.

Mass fractionation processes of transition metal isotopes

NASA Astrophysics Data System (ADS)

Zhu, X. K.; Guo, Y.; Williams, R. J. P.; O'Nions, R. K.; Matthews, A.; Belshaw, N. S.; Canters, G. W.; de Waal, E. C.; Weser, U.; Burgess, B. K.; Salvato, B.

2002-06-01

Recent advances in mass spectrometry make it possible to utilise isotope variations of transition metals to address some important issues in solar system and biological sciences. Realisation of the potential offered by these new isotope systems however requires an adequate understanding of the factors controlling their isotope fractionation. Here we show the results of a broadly based study on copper and iron isotope fractionation during various inorganic and biological processes. These results demonstrate that: (1) naturally occurring inorganic processes can fractionate Fe isotope to a detectable level even at temperature ˜1000°C, which challenges the previous view that Fe isotope variations in natural system are unique biosignatures; (2) multiple-step equilibrium processes at low temperatures may cause large mass fractionation of transition metal isotopes even when the fractionation per single step is small; (3) oxidation-reduction is an importation controlling factor of isotope fractionation of transition metal elements with multiple valences, which opens a wide range of applications of these new isotope systems, ranging from metal-silicate fractionation in the solar system to uptake pathways of these elements in biological systems; (4) organisms incorporate lighter isotopes of transition metals preferentially, and transition metal isotope fractionation occurs stepwise along their pathways within biological systems during their uptake.

Population dynamics in controlled unsteady-state systems: An application to the degradation of glyphosate in a sequencing batch reactor

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

Devarakonda, M.S.

1988-01-01

Control over population dynamics and organism selection in a biological waste treatment system provides an effective means of engineering process efficiency. Examples of applications of organism selection include control of filamentous organisms, biological nutrient removal, industrial waste treatment requiring the removal of specific substrates, and hazardous waste treatment. Inherently, full scale biological waste treatment systems are unsteady state systems due to the variations in the waste streams and mass flow rates of the substrates. Some systems, however, have the capacity to impose controlled selective pressures on the biological population by means of their operation. An example of such a systemmore » is the Sequencing Batch Reactor (SBR) which was the experimental system utilized in this research work. The concepts of organism selection were studied in detail for the biodegradation of a herbicide waste stream, with glyphosate as the target compound. The SBR provided a reactor configuration capable of exerting the necessary selective pressures to select and enrich for a glyphosate degrading population. Based on results for bench scale SBRs, a hypothesis was developed to explain population dynamics in glyphosate degrading systems.« less

Biologically inspired dynamic material systems.

PubMed

Studart, André R

2015-03-09

Numerous examples of material systems that dynamically interact with and adapt to the surrounding environment are found in nature, from hair-based mechanoreceptors in animals to self-shaping seed dispersal units in plants to remodeling bone in vertebrates. Inspired by such fascinating biological structures, a wide range of synthetic material systems have been created to replicate the design concepts of dynamic natural architectures. Examples of biological structures and their man-made counterparts are herein revisited to illustrate how dynamic and adaptive responses emerge from the intimate microscale combination of building blocks with intrinsic nanoscale properties. By using top-down photolithographic methods and bottom-up assembly approaches, biologically inspired dynamic material systems have been created 1) to sense liquid flow with hair-inspired microelectromechanical systems, 2) to autonomously change shape by utilizing plantlike heterogeneous architectures, 3) to homeostatically influence the surrounding environment through self-regulating adaptive surfaces, and 4) to spatially concentrate chemical species by using synthetic microcompartments. The ever-increasing complexity and remarkable functionalities of such synthetic systems offer an encouraging perspective to the rich set of dynamic and adaptive properties that can potentially be implemented in future man-made material systems. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

PubMed

de Dumast, Priscille; Mirabel, Clément; Cevidanes, Lucia; Ruellas, Antonio; Yatabe, Marilia; Ioshida, Marcos; Ribera, Nina Tubau; Michoud, Loic; Gomes, Liliane; Huang, Chao; Zhu, Hongtu; Muniz, Luciana; Shoukri, Brandon; Paniagua, Beatriz; Styner, Martin; Pieper, Steve; Budin, Francois; Vimort, Jean-Baptiste; Pascal, Laura; Prieto, Juan Carlos

2018-07-01

The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. The findings of this study demonstrate a comprehensive phenotypic characterization of TMJ health and disease at clinical, imaging and biological levels, using novel flexible and versatile open-source tools for a web-based system that provides advanced shape statistical analysis and a neural network based classification of temporomandibular joint osteoarthritis. Published by Elsevier Ltd.

Mass balances for a biological life support system simulation model

NASA Technical Reports Server (NTRS)

Volk, Tyler; Rumel, John D.

1987-01-01

Design decisions to aid the development of future space-based biological life support systems (BLSS) can be made with simulation models. Here the biochemical stoichiometry is developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady-state system with wheat as the sole food source.

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

The role of bacillus-based biological control agents in integrated pest management systems: plant diseases.

PubMed

Jacobsen, B J; Zidack, N K; Larson, B J

2004-11-01

ABSTRACT Bacillus-based biological control agents (BCAs) have great potential in integrated pest management (IPM) systems; however, relatively little work has been published on integration with other IPM management tools. Unfortunately, most research has focused on BCAs as alternatives to synthetic chemical fungicides or bactericides and not as part of an integrated management system. IPM has had many definitions and this review will use the national coalition for IPM definition: "A sustainable approach to managing pests by combining biological, cultural, physical and chemical tools in a way that minimizes economic, health and environmental risks." This review will examine the integrated use of Bacillus-based BCAs with disease management tools, including resistant cultivars, fungicides or bactericides, or other BCAs. This integration is important because the consistency and degree of disease control by Bacillus-based BCAs is rarely equal to the control afforded by the best fungicides or bactericides. In theory, integration of several tools brings stability to disease management programs. Integration of BCAs with other disease management tools often provides broader crop adaptation and both more efficacious and consistent levels of disease control. This review will also discuss the use of Bacillus-based BCAs in fungicide resistance management. Work with Bacillus thuringiensis and insect pest management is the exception to the relative paucity of reports but will not be the focus of this review.

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

PubMed Central

Walpole, J.; Chappell, J.C.; Cluceru, J.G.; Mac Gabhann, F.; Bautch, V.L.; Peirce, S. M.

2015-01-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods. PMID:26158406

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

PubMed

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-01

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation. Electronic supplementary information (ESI) available: Additional figures (Tables S1-S3 and Fig. S1-S6). See DOI: 10.1039/c6nr01072e

Power Provision Based on Self-Sacrificing Craft

NASA Technical Reports Server (NTRS)

Hinchey, Michael G. (Inventor); Sterrit, Roy (Inventor); Vassev, Emil I. (Inventor); Hinchey, Bridget (Inventor)

2015-01-01

A biologically-inspired system and method is provided for self-adapting behavior of swarm-based exploration missions, whereby individual components, for example, spacecraft, in the system can sacrifice themselves for the greater good of the entire system. The self-sacrifice can involve donating resources or assets, such as power provisions, to a different component of an autonomous system. A receiving component of the system can benefit from receiving the donated resource or power provision.

Simbios: an NIH national center for physics-based simulation of biological structures.

PubMed

Delp, Scott L; Ku, Joy P; Pande, Vijay S; Sherman, Michael A; Altman, Russ B

2012-01-01

Physics-based simulation provides a powerful framework for understanding biological form and function. Simulations can be used by biologists to study macromolecular assemblies and by clinicians to design treatments for diseases. Simulations help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, synthetic tissues, medical devices, and surgical interventions. Although individual biomedical investigators make outstanding contributions to physics-based simulation, the field has been fragmented. Applications are typically limited to a single physical scale, and individual investigators usually must create their own software. These conditions created a major barrier to advancing simulation capabilities. In 2004, we established a National Center for Physics-Based Simulation of Biological Structures (Simbios) to help integrate the field and accelerate biomedical research. In 6 years, Simbios has become a vibrant national center, with collaborators in 16 states and eight countries. Simbios focuses on problems at both the molecular scale and the organismal level, with a long-term goal of uniting these in accurate multiscale simulations.

Structure-Based Virtual Screening of Protein Tyrosine Phosphatase Inhibitors: Significance, Challenges, and Solutions.

PubMed

Reddy, Rallabandi Harikrishna; Kim, Hackyoung; Cha, Seungbin; Lee, Bongsoo; Kim, Young Jun

2017-05-28

Phosphorylation, a critical mechanism in biological systems, is estimated to be indispensable for about 30% of key biological activities, such as cell cycle progression, migration, and division. It is synergistically balanced by kinases and phosphatases, and any deviation from this balance leads to disease conditions. Pathway or biological activity-based abnormalities in phosphorylation and the type of involved phosphatase influence the outcome, and cause diverse diseases ranging from diabetes, rheumatoid arthritis, and numerous cancers. Protein tyrosine phosphatases (PTPs) are of prime importance in the process of dephosphorylation and catalyze several biological functions. Abnormal PTP activities are reported to result in several human diseases. Consequently, there is an increased demand for potential PTP inhibitory small molecules. Several strategies in structure-based drug designing techniques for potential inhibitory small molecules of PTPs have been explored along with traditional drug designing methods in order to overcome the hurdles in PTP inhibitor discovery. In this review, we discuss druggable PTPs and structure-based virtual screening efforts for successful PTP inhibitor design.

Simbios: an NIH national center for physics-based simulation of biological structures

PubMed Central

Delp, Scott L; Ku, Joy P; Pande, Vijay S; Sherman, Michael A

2011-01-01

Physics-based simulation provides a powerful framework for understanding biological form and function. Simulations can be used by biologists to study macromolecular assemblies and by clinicians to design treatments for diseases. Simulations help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, synthetic tissues, medical devices, and surgical interventions. Although individual biomedical investigators make outstanding contributions to physics-based simulation, the field has been fragmented. Applications are typically limited to a single physical scale, and individual investigators usually must create their own software. These conditions created a major barrier to advancing simulation capabilities. In 2004, we established a National Center for Physics-Based Simulation of Biological Structures (Simbios) to help integrate the field and accelerate biomedical research. In 6 years, Simbios has become a vibrant national center, with collaborators in 16 states and eight countries. Simbios focuses on problems at both the molecular scale and the organismal level, with a long-term goal of uniting these in accurate multiscale simulations. PMID:22081222

Novel biomaterials: plasma-enabled nanostructures and functions

NASA Astrophysics Data System (ADS)

Levchenko, Igor; Keidar, Michael; Cvelbar, Uroš; Mariotti, Davide; Mai-Prochnow, Anne; Fang, Jinghua; (Ken Ostrikov, Kostya

2016-07-01

Material processing techniques utilizing low-temperature plasmas as the main process tool feature many unique capabilities for the fabrication of various nanostructured materials. As compared with the neutral-gas based techniques and methods, the plasma-based approaches offer higher levels of energy and flux controllability, often leading to higher quality of the fabricated nanomaterials and sometimes to the synthesis of the hierarchical materials with interesting properties. Among others, nanoscale biomaterials attract significant attention due to their special properties towards the biological materials (proteins, enzymes), living cells and tissues. This review briefly examines various approaches based on the use of low-temperature plasma environments to fabricate nanoscale biomaterials exhibiting high biological activity, biological inertness for drug delivery system, and other features of the biomaterials make them highly attractive. In particular, we briefly discuss the plasma-assisted fabrication of gold and silicon nanoparticles for bio-applications; carbon nanoparticles for bioimaging and cancer therapy; carbon nanotube-based platforms for enzyme production and bacteria growth control, and other applications of low-temperature plasmas in the production of biologically-active materials.

Biomaterials-Based Electronics: Polymers and Interfaces for Biology and Medicine

PubMed Central

Muskovich, Meredith; Bettinger, Christopher J.

2012-01-01

Advanced polymeric biomaterials continue to serve as a cornerstone of new medical technologies and therapies. The vast majority of these materials, both natural and synthetic, interact with biological matter without direct electronic communication. However, biological systems have evolved to synthesize and employ naturally-derived materials for the generation and modulation of electrical potentials, voltage gradients, and ion flows. Bioelectric phenomena can be interpreted as potent signaling cues for intra- and inter-cellular communication. These cues can serve as a gateway to link synthetic devices with biological systems. This progress report will provide an update on advances in the application of electronically active biomaterials for use in organic electronics and bio-interfaces. Specific focus will be granted to the use of natural and synthetic biological materials as integral components in technologies such as thin film electronics, in vitro cell culture models, and implantable medical devices. Future perspectives and emerging challenges will also be highlighted. PMID:23184740

NMR spectroscopy of Group 13 metal ions: biologically relevant aspects.

PubMed

André, J P; Mäcke, H R

2003-12-01

In spite of the fact that Group 13 metal ions (Al(3+), Ga(3+), In(3+) and Tl(+/3+)) show no main biological role, they are NMR-active nuclides which can be used in magnetic resonance spectroscopy of biologically relevant systems. The fact that these metal ions are quadrupolar (with the exception of thallium) means that they are particularly sensitive to ligand type and coordination geometry. The line width of the NMR signals of their complexes shows a strong dependence on the symmetry of coordination, which constitutes an effective tool in the elucidation of structures. Here we report published NMR studies of this family of elements, applied to systems of biological importance. Special emphasis is given to binding studies of these cations to biological molecules, such as proteins, and to chelating agents of radiopharmaceutical interest. The possibility of in vivo NMR studies is also stressed, with extension to (27)Al-based MRI (magnetic resonance imaging) experiments.

Engineering emergent multicellular behavior through synthetic adhesion

NASA Astrophysics Data System (ADS)

Glass, David; Riedel-Kruse, Ingmar

In over a decade, synthetic biology has developed increasingly robust gene networks within single cells, but constructed very few systems that demonstrate multicellular spatio-temporal dynamics. We are filling this gap in synthetic biology's toolbox by developing an E. coli self-assembly platform based on modular cell-cell adhesion. We developed a system in which adhesive selectivity is provided by a library of outer membrane-displayed peptides with intra-library specificities, while affinity is provided by consistent expression across the entire library. We further provide a biophysical model to help understand the parameter regimes in which this tool can be used to self-assemble into cellular clusters, filaments, or meshes. The combined platform will enable future development of synthetic multicellular systems for use in consortia-based metabolic engineering, in living materials, and in controlled study of minimal multicellular systems. Stanford Bio-X Bowes Fellowship.

Overview of chemical imaging methods to address biological questions.

PubMed

da Cunha, Marcel Menezes Lyra; Trepout, Sylvain; Messaoudi, Cédric; Wu, Ting-Di; Ortega, Richard; Guerquin-Kern, Jean-Luc; Marco, Sergio

2016-05-01

Chemical imaging offers extensive possibilities for better understanding of biological systems by allowing the identification of chemical components at the tissue, cellular, and subcellular levels. In this review, we introduce modern methods for chemical imaging that can be applied to biological samples. This work is mainly addressed to the biological sciences community and includes the bases of different technologies, some examples of its application, as well as an introduction to approaches on combining multimodal data. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Technology development for lunar base water recycling

NASA Technical Reports Server (NTRS)

Schultz, John R.; Sauer, Richard L.

1992-01-01

This paper will review previous and ongoing work in aerospace water recycling and identify research activities required to support development of a lunar base. The development of a water recycle system for use in the life support systems envisioned for a lunar base will require considerable research work. A review of previous work on aerospace water recycle systems indicates that more efficient physical and chemical processes are needed to reduce expendable and power requirements. Development work on biological processes that can be applied to microgravity and lunar environments also needs to be initiated. Biological processes are inherently more efficient than physical and chemical processes and may be used to minimize resupply and waste disposal requirements. Processes for recovering and recycling nutrients such as nitrogen, phosphorus, and sulfur also need to be developed to support plant growth units. The development of efficient water quality monitors to be used for process control and environmental monitoring also needs to be initiated.

Extending and expanding the Darwinian synthesis: the role of complex systems dynamics.

PubMed

Weber, Bruce H

2011-03-01

Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself. Copyright © 2010 Elsevier Ltd. All rights reserved.

Determining the transport mechanism of an enzyme-catalytic complex metabolic network based on biological robustness.

PubMed

Wang, Lei

2013-04-01

Understanding the transport mechanism of 1,3-propanediol (1,3-PD) is of critical importance to do further research on gene regulation. Due to the lack of intracellular information, on the basis of enzyme-catalytic system, using biological robustness as performance index, we present a system identification model to infer the most possible transport mechanism of 1,3-PD, in which the performance index consists of the relative error of the extracellular substance concentrations and biological robustness of the intracellular substance concentrations. We will not use a Boolean framework but prefer a model description based on ordinary differential equations. Among other advantages, this also facilitates the robustness analysis, which is the main goal of this paper. An algorithm is constructed to seek the solution of the identification model. Numerical results show that the most possible transport way is active transport coupled with passive diffusion.

Wetting of silicone oil onto a cell-seeded substrate

NASA Astrophysics Data System (ADS)

Lu, Yongjie; Chan, Yau Kei; Chao, Youchuang; Shum, Ho Cheung

2017-11-01

Wetting behavior of solid substrates in three-phase systems containing two immiscible liquids are widely studied. There exist many three-phase systems in biological environments, such as droplet-based microfluidics or tamponade of silicone oil for eye surgery. However, few studies focus on wetting behavior of biological surfaces with cells. Here we investigate wetting of silicone oil onto cell-seeded PMMA sheet immersed in water. Using a simple parallel-plate cell, we show the effect of cell density, viscosity of silicone oil, morphology of silicone oil drops and interfacial tension on the wetting phenomenon. The dynamics of wetting is also observed by squeezing silicone oil drop using two parallel plates. Experimental results are explained based on disjoining pressure which is dependent on the interaction of biological surfaces and liquid used. These findings are useful for explaining emulsification of silicone oil in ophthalmological applications.

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

PubMed

Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-03-22

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

PubMed Central

Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-01-01

Background Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. Methodology We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. Conclusions This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. PMID:21445339

Microcantilever technology for law enforcement and anti-terrorism applications: chemical, biological, and explosive material detection

NASA Astrophysics Data System (ADS)

Adams, J. D.; Rogers, B.; Whitten, R.

2005-05-01

The remarkable sensitivity, compactness, low cost, low power-consumption, scalability, and versatility of microcantilever sensors make this technology among the most promising solutions for detection of chemical and biological agents, as well as explosives. The University of Nevada, Reno, and Nevada Nanotech Systems, Inc (NNTS) are currently developing a microcantilever-based detection system that will measure trace concentrations of explosives, toxic chemicals, and biological agents in air. A baseline sensor unit design that includes the sensor array, electronics, power supply and air handling has been created and preliminary demonstrations of the microcantilever platform have been conducted. The envisioned device would measure about two cubic inches, run on a small watch battery and cost a few hundred dollars. The device could be operated by untrained law enforcement personnel. Microcantilever-based devices could be used to "sniff out" illegal and/or hazardous chemical and biological agents in high traffic public areas, or be packaged as a compact, low-power system used to monitor cargo in shipping containers. Among the best detectors for such applications at present is the dog, an animal which is expensive, requires significant training and can only be made to work for limited time periods. The public is already accustomed to explosives and metal detection systems in airports and other public venues, making the integration of the proposed device into such security protocols straightforward.

PathCase-SB architecture and database design

PubMed Central

2011-01-01

Background Integration of metabolic pathways resources and regulatory metabolic network models, and deploying new tools on the integrated platform can help perform more effective and more efficient systems biology research on understanding the regulation in metabolic networks. Therefore, the tasks of (a) integrating under a single database environment regulatory metabolic networks and existing models, and (b) building tools to help with modeling and analysis are desirable and intellectually challenging computational tasks. Description PathCase Systems Biology (PathCase-SB) is built and released. The PathCase-SB database provides data and API for multiple user interfaces and software tools. The current PathCase-SB system provides a database-enabled framework and web-based computational tools towards facilitating the development of kinetic models for biological systems. PathCase-SB aims to integrate data of selected biological data sources on the web (currently, BioModels database and KEGG), and to provide more powerful and/or new capabilities via the new web-based integrative framework. This paper describes architecture and database design issues encountered in PathCase-SB's design and implementation, and presents the current design of PathCase-SB's architecture and database. Conclusions PathCase-SB architecture and database provide a highly extensible and scalable environment with easy and fast (real-time) access to the data in the database. PathCase-SB itself is already being used by researchers across the world. PMID:22070889

On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics

PubMed Central

Calcagno, Cristina; Coppo, Mario

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed. PMID:25050327

Will Quantitative Proteomics Redefine Some of the Key Concepts in Skeletal Muscle Physiology?

PubMed

Gizak, Agnieszka; Rakus, Dariusz

2016-01-11

Molecular and cellular biology methodology is traditionally based on the reasoning called "the mechanistic explanation". In practice, this means identifying and selecting correlations between biological processes which result from our manipulation of a biological system. In theory, a successful application of this approach requires precise knowledge about all parameters of a studied system. However, in practice, due to the systems' complexity, this requirement is rarely, if ever, accomplished. Typically, it is limited to a quantitative or semi-quantitative measurements of selected parameters (e.g., concentrations of some metabolites), and a qualitative or semi-quantitative description of expression/post-translational modifications changes within selected proteins. A quantitative proteomics approach gives a possibility of quantitative characterization of the entire proteome of a biological system, in the context of the titer of proteins as well as their post-translational modifications. This enables not only more accurate testing of novel hypotheses but also provides tools that can be used to verify some of the most fundamental dogmas of modern biology. In this short review, we discuss some of the consequences of using quantitative proteomics to verify several key concepts in skeletal muscle physiology.

On designing multicore-aware simulators for systems biology endowed with OnLine statistics.

PubMed

Aldinucci, Marco; Calcagno, Cristina; Coppo, Mario; Damiani, Ferruccio; Drocco, Maurizio; Sciacca, Eva; Spinella, Salvatore; Torquati, Massimo; Troina, Angelo

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

PREFACE: 9th International Fröhlich's Symposium: Electrodynamic Activity of Living Cells (Including Microtubule Coherent Modes and Cancer Cell Physics)

NASA Astrophysics Data System (ADS)

Cifra, Michal; Pokorný, Jirí; Kucera, Ondrej

2011-12-01

This volume contains papers presented at the International Fröhlich's Symposium entitled 'Electrodynamic Activity of Living Cells' (1-3 July 2011, Prague, Czech Republic). The Symposium was the 9th meeting devoted to physical processes in living matter organized in Prague since 1987. The hypothesis of oscillation systems in living cells featured by non-linear interaction between elastic and electrical polarization fields, non-linear interactions between the system and the heat bath leading to energy downconversion along the frequency scale, energy condensation in the lowest frequency mode and creation of a coherent state was formulated by H Fröhlich, founder of the theory of dielectric materials. He assumed that biological activity is based not only on biochemical but also on biophysical mechanisms and that their disturbances form basic links along the cancer transformation pathway. Fröhlich outlined general ideas of non-linear physical processes in biological systems. The downconversion and the elastic-polarization interactions should be connected in a unified theory and the solution based on comprehensive non-linear characteristics. Biochemical and genetic research of biological systems are highly developed and have disclosed a variety of cellular and subcellular structures, chemical reactions, molecular information transfer, and genetic code sequences - including their pathological development. Nevertheless, the cancer problem is still a big challenge. Warburg's discovery of suppressed oxidative metabolism in mitochondria in cancer cells suggested the essential role of physical mechanisms (but his discovery has remained without impact on cancer research and on the study of physical properties of biological systems for a long time). Mitochondria, the power plants of the cell, have several areas of activity-oxidative energy production is connected with the formation of a strong static electric field around them, water ordering, and liberation of non-utilized energy to their surroundings. Mitochondrial function connected with water ordering and excitation of oscillations in microtubules may play a central role in biological activity, in particular in transport, organization, interactions, and information transfer. Mitochondrial disfunction results in disturbances of the generated electrodynamic field with bad consequences in biological activity and the creation of pathological states. A special issue of the biological activity concerns the brain function (consciousness is not yet adequately understood). Experimental investigation using nanotechnology would supply yet unknown data and parameters of physical mechanisms in living systems. Extremely weak biological signals have to be separated from technical noise under conditions of possible non-linear mutual interactions. Some authors questioned the validity of the Fröhlich hypothesis. Foster and Baish (J. Biol. Phys. 26 2000, 255) neglected water ordering and concluded that strong damping by water viscosity effects prevents the formation of a coherent state. Reimers et al (PNAS 106 2009, 4219) and McKemmish et al (Phys. Rev. E 80 2009, 021912-1) omitted non-linear elastic-electrical polarization interactions and analyzed a linearized model of downconversion with strong damping that cannot represent the Fröhlich system. Fröhlich assumed a high quality non-linear system with energy supply. Some methods used for analysis of linear systems (for instance the method of superposition) are not valid in non-linear systems. For this reason also experimental analysis based on subtraction of the noise from the measured signal spectrum is not a simple question. There is another special issue concerning biological activity. The living state and in particular consciousness are very often connected with an idea of a non-material and non-measurable entity entering the biological system from outside. There is a splendid harmony and order in nature. Science should disclose measurable mechanisms of the harmony and order. But human knowledge about the electrodynamic and electromagnetic fields in biological systems is still at a low level. The Symposium continued in the series of international scientific meetings devoted to physical processes in living cells organized in Prague. The first meeting was entitled 'Biophysical Aspects of Cancer' (6-9 July 1987). On this occasion the Anglo-German physicist H Fröhlich presented a lecture 'Coherence in Biology'. The next meeting which was devoted to the Fröhlich coherent systems, information transfer, and neural activity was in 1993. The role of the Fröhlich coherence in the neural activity was included in the meeting 'Biophysical Aspects of Coherence' in 1995 too. The subsequent symposia were entitled 'Electromagnetic Fields in Biological Systems' (1998), 'Electromagnetic Aspects of Selforganization in Biology' (2000), 'Endogenous Physical Fields in Biology' (2002), 'Coherence and Electromagnetic Fields in Biological Systems' (2005), and 'Biophysical Aspects of Cancer - Electromagnetic Mechanisms' (2008). In 2008 a novel project for research of convergence of physics and oncology was triggered in the USA by the National Cancer Institute and the Institute of Public Health. This volume contains the a large number of the papers presented at the Symposium. The ideas presented at the Symposium might have impact on the future research of physical processes and mechanisms in biological systems. Experimental research may provide a background for understanding the neglected part of biological activity and reveal the physical mechanisms of the cancer transformation pathway. The Symposium and this volume were prepared by a scientific team whose members were M Cifra, D Havelka, A Jandová, F Jelínek, O Kucera, M Nedbalová, and F Šrobár. Jirí Pokorný A list of committees, sponsors, the list of talks and some photographs from the conference can be found in the PDF file.

Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

PubMed Central

Chen, Bor-Sen; Wu, Chia-Chou

2013-01-01

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

PubMed

Chen, Bor-Sen; Wu, Chia-Chou

2013-10-11

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

Towards systems metabolic engineering of microorganisms for amino acid production.

PubMed

Park, Jin Hwan; Lee, Sang Yup

2008-10-01

Microorganisms capable of efficient production of amino acids have traditionally been developed by random mutation and selection method, which might cause unwanted physiological changes in cellular metabolism. Rational genome-wide metabolic engineering based on systems and synthetic biology tools, which is termed 'systems metabolic engineering', is rising as an alternative to overcome these problems. Recently, several amino acid producers have been successfully developed by systems metabolic engineering, where the metabolic engineering procedures were performed within a systems biology framework, and entire metabolic networks, including complex regulatory circuits, were engineered in an integrated manner. Here we review the current status of systems metabolic engineering successfully applied for developing amino acid producing strains and discuss future prospects.

Towards programming languages for genetic engineering of living cells

PubMed Central

Pedersen, Michael; Phillips, Andrew

2009-01-01

Synthetic biology aims at producing novel biological systems to carry out some desired and well-defined functions. An ultimate dream is to design these systems at a high level of abstraction using engineering-based tools and programming languages, press a button, and have the design translated to DNA sequences that can be synthesized and put to work in living cells. We introduce such a programming language, which allows logical interactions between potentially undetermined proteins and genes to be expressed in a modular manner. Programs can be translated by a compiler into sequences of standard biological parts, a process that relies on logic programming and prototype databases that contain known biological parts and protein interactions. Programs can also be translated to reactions, allowing simulations to be carried out. While current limitations on available data prevent full use of the language in practical applications, the language can be used to develop formal models of synthetic systems, which are otherwise often presented by informal notations. The language can also serve as a concrete proposal on which future language designs can be discussed, and can help to guide the emerging standard of biological parts which so far has focused on biological, rather than logical, properties of parts. PMID:19369220

Towards programming languages for genetic engineering of living cells.

PubMed

Pedersen, Michael; Phillips, Andrew

2009-08-06

Synthetic biology aims at producing novel biological systems to carry out some desired and well-defined functions. An ultimate dream is to design these systems at a high level of abstraction using engineering-based tools and programming languages, press a button, and have the design translated to DNA sequences that can be synthesized and put to work in living cells. We introduce such a programming language, which allows logical interactions between potentially undetermined proteins and genes to be expressed in a modular manner. Programs can be translated by a compiler into sequences of standard biological parts, a process that relies on logic programming and prototype databases that contain known biological parts and protein interactions. Programs can also be translated to reactions, allowing simulations to be carried out. While current limitations on available data prevent full use of the language in practical applications, the language can be used to develop formal models of synthetic systems, which are otherwise often presented by informal notations. The language can also serve as a concrete proposal on which future language designs can be discussed, and can help to guide the emerging standard of biological parts which so far has focused on biological, rather than logical, properties of parts.

Agents in bioinformatics, computational and systems biology.

PubMed

Merelli, Emanuela; Armano, Giuliano; Cannata, Nicola; Corradini, Flavio; d'Inverno, Mark; Doms, Andreas; Lord, Phillip; Martin, Andrew; Milanesi, Luciano; Möller, Steffen; Schroeder, Michael; Luck, Michael

2007-01-01

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

Nanotechnology-Based Strategies for siRNA Brain Delivery for Disease Therapy.

PubMed

Zheng, Meng; Tao, Wei; Zou, Yan; Farokhzad, Omid C; Shi, Bingyang

2018-05-01

Small interfering RNA (siRNA)-based gene silencing technology has demonstrated significant potential for treating brain-associated diseases. However, effective and safe systemic delivery of siRNA into the brain remains challenging because of biological barriers such as enzymatic degradation, short circulation lifetime, the blood-brain barrier (BBB), insufficient tissue penetration, cell endocytosis, and cytosolic transport. Nanotechnology offers intriguing potential for addressing these challenges in siRNA brain delivery in conjunction with chemical and biological modification strategies. In this review, we outline the challenges of systemic delivery of siRNA-based therapy for brain diseases, highlight recent advances in the development and engineering of siRNA nanomedicines for various brain diseases, and discuss our perspectives on this exciting research field for siRNA-based therapy towards more effective brain disease therapy. Copyright © 2018 Elsevier Ltd. All rights reserved.

Biological interaction of living cells with COSAN-based synthetic vesicles

PubMed Central

Tarrés, Màrius; Canetta, Elisabetta; Paul, Eleanor; Forbes, Jordan; Azzouni, Karima; Viñas, Clara; Teixidor, Francesc; Harwood, Adrian J.

2015-01-01

Cobaltabisdicarbollide (COSAN) [3,3′-Co(1,2-C2B9H11)2]−, is a complex boron-based anion that has the unusual property of self-assembly into membranes and vesicles. These membranes have similar dimensions to biological membranes found in cells, and previously COSAN has been shown to pass through synthetic lipid membranes and those of living cells without causing breakdown of membrane barrier properties. Here, we investigate the interaction of this inorganic membrane system with living cells. We show that COSAN has no immediate effect on cell viability, and cells fully recover when COSAN is removed following exposure for hours to days. COSAN elicits a range of cell biological effects, including altered cell morphology, inhibition of cell growth and, in some cases, apoptosis. These observations reveal a new biology at the interface between inorganic, synthetic COSAN membranes and naturally occurring biological membranes. PMID:25588708

Biological interaction of living cells with COSAN-based synthetic vesicles.

PubMed

Tarrés, Màrius; Canetta, Elisabetta; Paul, Eleanor; Forbes, Jordan; Azzouni, Karima; Viñas, Clara; Teixidor, Francesc; Harwood, Adrian J

2015-01-15

Cobaltabisdicarbollide (COSAN) [3,3'-Co(1,2-C2B9H11)2](-), is a complex boron-based anion that has the unusual property of self-assembly into membranes and vesicles. These membranes have similar dimensions to biological membranes found in cells, and previously COSAN has been shown to pass through synthetic lipid membranes and those of living cells without causing breakdown of membrane barrier properties. Here, we investigate the interaction of this inorganic membrane system with living cells. We show that COSAN has no immediate effect on cell viability, and cells fully recover when COSAN is removed following exposure for hours to days. COSAN elicits a range of cell biological effects, including altered cell morphology, inhibition of cell growth and, in some cases, apoptosis. These observations reveal a new biology at the interface between inorganic, synthetic COSAN membranes and naturally occurring biological membranes.

Systems Biology for Organotypic Cell Cultures

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

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis J.

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

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

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE PAGES

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph; ...

2016-11-14

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Systems biology for organotypic cell cultures.

PubMed

Grego, Sonia; Dougherty, Edward R; Alexander, Francis J; Auerbach, Scott S; Berridge, Brian R; Bittner, Michael L; Casey, Warren; Cooley, Philip C; Dash, Ajit; Ferguson, Stephen S; Fennell, Timothy R; Hawkins, Brian T; Hickey, Anthony J; Kleensang, Andre; Liebman, Michael N J; Martin, Florian; Maull, Elizabeth A; Paragas, Jason; Qiao, Guilin Gary; Ramaiahgari, Sreenivasa; Sumner, Susan J; Yoon, Miyoung

2017-01-01

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, "organotypic" cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

Subcellular Carrier-Based Optical Ion-Selective Nanosensors

PubMed Central

Carregal-Romero, Susana; Montenegro, Jose-Maria; Parak, Wolfgang J.; Rivera_Gil, Pilar

2012-01-01

In this review, two carrier systems based on nanotechnology for real-time sensing of biologically relevant analytes (ions or other biological molecules) inside cells in a non-invasive way are discussed. One system is based on inorganic nanoparticles with an organic coating, whereas the second system is based on organic microcapsules. The sensor molecules presented within this work use an optical read-out. Due to the different physicochemical properties, both sensors show distinctive geometries that directly affect their internalization patterns. The nanoparticles carry the sensor molecule attached to their surfaces whereas the microcapsules encapsulate the sensor within their cavities. Their different size (nano and micro) enable each sensors to locate in different cellular regions. For example, the nanoparticles are mostly found in endolysosomal compartments but the microcapsules are rather found in phagolysosomal vesicles. Thus, allowing creating a tool of sensors that sense differently. Both sensor systems enable to measure ratiometrically however, only the microcapsules have the unique ability of multiplexing. At the end, an outlook on how more sophisticated sensors can be created by confining the nano-scaled sensors within the microcapsules will be given. PMID:22557969

Improvement of up-converting phosphor technology-based biosensor

NASA Astrophysics Data System (ADS)

Xie, Chengke; Huang, Lihua; Zhang, Youbao; Guo, Xiaoxian; Qu, Jianfeng; Huang, Huijie

2008-12-01

A novel biosensor based on up-converting phosphor technology (UPT) was developed several years ago. It is a kind of optical biosensor using up-converting phosphor (UCP) particles as the biological marker. From then on, some improvements have been made for this UPT-based biosensor. The primary aspects of the improvement lie in the control system. On one hand, the hardware of the control system has been optimized, including replacing two single chip microcomputers (SCM) with only one, the optimal design of the keyboard interface circuit and the liquid crystal module (LCM) control circuit et al.. These result in lower power consumption and higher reliability. On the other hand, a novel signal processing algorithm is proposed in this paper, which can improve the automation and operating simplicity of the UPT-based biosensor. It has proved to have high sensitivity (~ng/ml), high stability and good repeatability (CV<5%), which is better than the former system. It can meet the need of some various applications such as rapid immunoassay, chemical and biological detection and so on.

Generation of Diverse Biological Forms through Combinatorial Interactions between Tissue Polarity and Growth

PubMed Central

Kennaway, Richard; Coen, Enrico; Green, Amelia; Bangham, Andrew

2011-01-01

A major problem in biology is to understand how complex tissue shapes may arise through growth. In many cases this process involves preferential growth along particular orientations raising the question of how these orientations are specified. One view is that orientations are specified through stresses in the tissue (axiality-based system). Another possibility is that orientations can be specified independently of stresses through molecular signalling (polarity-based system). The axiality-based system has recently been explored through computational modelling. Here we develop and apply a polarity-based system which we call the Growing Polarised Tissue (GPT) framework. Tissue is treated as a continuous material within which regionally expressed factors under genetic control may interact and propagate. Polarity is established by signals that propagate through the tissue and is anchored in regions termed tissue polarity organisers that are also under genetic control. Rates of growth parallel or perpendicular to the local polarity may then be specified through a regulatory network. The resulting growth depends on how specified growth patterns interact within the constraints of mechanically connected tissue. This constraint leads to the emergence of features such as curvature that were not directly specified by the regulatory networks. Resultant growth feeds back to influence spatial arrangements and local orientations of tissue, allowing complex shapes to emerge from simple rules. Moreover, asymmetries may emerge through interactions between polarity fields. We illustrate the value of the GPT-framework for understanding morphogenesis by applying it to a growing Snapdragon flower and indicate how the underlying hypotheses may be tested by computational simulation. We propose that combinatorial intractions between orientations and rates of growth, which are a key feature of polarity-based systems, have been exploited during evolution to generate a range of observed biological shapes. PMID:21698124

A Guided-Inquiry pH Laboratory Exercise for Introductory Biological Science Laboratories

ERIC Educational Resources Information Center

Snodgrass, Meagan A.; Lux, Nicholas; Metz, Anneke M.

2011-01-01

There is a continuing need for engaging inquiry-based laboratory experiences for advanced high school and undergraduate biology courses. The authors describe a guided-inquiry exercise investigating the pH-dependence of lactase enzyme that uses an inexpensive, wide-range buffering system, lactase dietary supplement, over-the-counter glucose test…

Adaptively Selecting Biology Questions Generated from a Semantic Network

ERIC Educational Resources Information Center

Zhang, Lishan; VanLehn, Kurt

2017-01-01

The paper describes a biology tutoring system with adaptive question selection. Questions were selected for presentation to the student based on their utilities, which were estimated from the chance that the student's competence would increase if the questions were asked. Competence was represented by the probability of mastery of a set of biology…

A review of sensors, samplers and methods for marine biological observations.

NASA Astrophysics Data System (ADS)

Simmons, S. E.; Chavez, F.; Pearlman, J.; Working Group, T B S

2016-02-01

Physical scientists now have Argo floats, gliders and AUVs to supplement satellites to provide a 3-D view of the time-varying global ocean temperature and salinity structure. Biogeochemists are catching up with evolving sensors for nitrate, optical properties, oxygen and pH that can now be added to these autonomous systems. Biologists are still lagging, although some promising sensor systems based on but not limited to acoustic, chemical, genomic or imaging techniques, that can sense from microbes to whales, are on the horizon. These techniques can not only be applied in situ but also on samples returned to the laboratory using the autonomous systems. The number of samples is limiting, requiring adaptive and smart systems. Given the importance of biology to ocean health and the future earth, and the present reliance on humans and ships for observing species and abundance it is paramount that new biological sensor systems be developed. This abstract will review recent efforts to identify core biological variables for the US Integrated Ocean Observing System and address new sensors and innovations for observing these variables, particularly focused on availability and maturity of sensors. The relevance of this work in a global context will also be touched on.

A Systems' Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

PubMed Central

Kunz, Manfred; Vera, Julio; Wolkenhauer, Olaf

2013-01-01

MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts. PMID:24350286

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems.

PubMed

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-01-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial's functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field.

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems

PubMed Central

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-01-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial's functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field. PMID:29707534

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems

NASA Astrophysics Data System (ADS)

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-04-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial’s functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field.

Xenobiology: State-of-the-Art, Ethics, and Philosophy of New-to-Nature Organisms.

PubMed

Schmidt, Markus; Pei, Lei; Budisa, Nediljko

The basic chemical constitution of all living organisms in the context of carbon-based chemistry consists of a limited number of small molecules and polymers. Until the twenty-first century, biology was mainly an analytical science and has now reached a point where it merges with engineering science, paving the way for synthetic biology. One of the objectives of synthetic biology is to try to change the chemical compositions of living cells, that is, to create an artificial biological diversity, which in turn fosters a new sub-field of synthetic biology, xenobiology. In particular, the genetic code in living systems is based on highly standardized chemistry composed of the same "letters" or nucleotides as informational polymers (DNA, RNA) and the 20 amino acids which serve as basic building blocks for proteins. The universality of the genetic code enables not only vertical gene transfer within the same species but also horizontal gene transfer across biological taxa, which require a high degree of standardization and interconnectivity. Although some minor alterations of the standard genetic code are found in nature (e.g., proteins containing non-conical amino acids exist in nature, and some organisms use alternated coding systems), all structurally deep chemistry changes within living systems are generally lethal, making the creation of artificial biological system an extremely difficult challenge.In this context, one of the great challenges for bioscience is the development of a strategy for expanding the standard basic chemical repertoire of living cells. Attempts to alter the meaning of the genetic information stored in DNA as an informational polymer by changing the chemistry of the polymer (i.e., xeno-nucleic acids) or by changes in the genetic code have already yielded successful results. In the future this should enable the partial or full redirection of the biological information flow to generate "new" version(s) of the genetic code derived from the "old" biological world.In addition to the scientific challenges, the attempt to increase biochemical diversity also raises important ethical and philosophical issues. Although promotors of this branch of synthetic biology highlight the many potential applications to come (e.g., novel tools for diagnostics and fighting infection diseases), such developments could also bring risks affecting social, political, and other structures of nearly all societies.

Design of an ultraviolet fluorescence lidar for biological aerosol detection

NASA Astrophysics Data System (ADS)

Rao, Zhimin; Hua, Dengxin; He, Tingyao; Le, Jing

2016-09-01

In order to investigate the biological aerosols in the atmosphere, we have designed an ultraviolet laser induced fluorescence lidar based on the lidar measuring principle. The fluorescence lidar employs a Nd:YAG laser of 266 nm as an excited transmitter, and examines the intensity of the received light at 400 nm for biological aerosol concentration measurements. In this work, we firstly describe the designed configuration and the simulation to estimate the measure range and the system resolution of biological aerosol concentration under certain background radiation. With a relative error of less than 10%, numerical simulations show the system is able to monitor biological aerosols within detected distances of 1.8 km and of 7.3 km in the daytime and nighttime, respectively. Simulated results demonstrate the designed fluorescence lidar is capable to identify a minimum concentration of biological aerosols at 5.0×10-5 ppb in the daytime and 1.0×10-7 ppb in the nighttime at the range of 0.1 km. We believe the ultraviolet laser induced fluorescence lidar can be spread in the field of remote sensing of biological aerosols in the atmosphere.

Just working with the cellular machine: A high school game for teaching molecular biology.

PubMed

Cardoso, Fernanda Serpa; Dumpel, Renata; da Silva, Luisa B Gomes; Rodrigues, Carlos R; Santos, Dilvani O; Cabral, Lucio Mendes; Castro, Helena C

2008-03-01

Molecular biology is a difficult comprehension subject due to its high complexity, thus requiring new teaching approaches. Herein, we developed an interdisciplinary board game involving the human immune system response against a bacterial infection for teaching molecular biology at high school. Initially, we created a database with several questions and a game story that invites the students for helping the human immunological system to produce antibodies (IgG) and fight back a pathogenic bacterium second-time invasion. The game involves answering questions completing the game board in which the antibodies "are synthesized" through the molecular biology process. At the end, a problem-based learning approach is used, and a last question is raised about proteins. Biology teachers and high school students evaluated the game and considered it an easy and interesting tool for teaching the theme. An increase of about 5-30% in answering molecular biology questions revealed that the game improves learning and induced a more engaged and proactive learning profile in the high school students. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

Is the whole the sum of its parts? Agent-based modelling of wastewater treatment systems.

PubMed

Schuler, A J; Majed, N; Bucci, V; Hellweger, F L; Tu, Y; Gu, A Z

2011-01-01

Agent-based models (ABMS) simulate individual units within a system, such as the bacteria in a biological wastewater treatment system. This paper outlines past, current and potential future applications of ABMs to wastewater treatment. ABMs track heterogeneities within microbial populations, and this has been demonstrated to yield different predictions of bulk behaviors than the conventional, "lumped" approaches for enhanced biological phosphorus removal (EBPR) completely mixed reactors systems. Current work included the application of the ABM approach to bacterial adaptation/evolution, using the model system of individual EBPR bacteria that are allowed to evolve a kinetic parameter (maximum glycogen storage) in a competitive environment. The ABM approach was successfully implemented to a simple anaerobic-aerobic system and it was found the differing initial states converged to the same optimal solution under uncertain hydraulic residence times associated with completely mixed hydraulics. In another study, an ABM was developed and applied to simulate the heterogeneity in intracellular polymer storage compounds, including polyphosphate (PP), in functional microbial populations in enhanced biological phosphorus removal (EBPR) process. The simulation results were compared to the experimental measurements of single-cell abundance of PP in polyphosphate accumulating organisms (PAOs), performed using Raman microscopy. The model-predicted heterogeneity was generally consistent with observations, and it was used to investigate the relative contribution of external (different life histories) and internal (biological) mechanisms leading to heterogeneity. In the future, ABMs could be combined with computational fluid dynamics (CFD) models to understand incomplete mixing, more intracellular states and mechanisms can be incorporated, and additional experimental verification is needed.

Efficiency of a bagasse substrate in a biological bed system for the degradation of glyphosate, malathion and lambda-cyhalothrin under tropical climate conditions.

PubMed

de Roffignac, Laure; Cattan, Philippe; Mailloux, Julie; Herzog, David; Le Bellec, Fabrice

2008-12-01

After the rinsing of spray equipment, the rinsing water contains polluting products. One way to avoid pollution is to bring the rinsing water over a purification system, a biological bed. The system consists of an impermeable tub filled with a biomix substrate that facilitates biodegradation of pesticides. Usually, straw is one component of the biomix. The objective of this study was to assess the efficiency of an unusual substrate, bagasse, a residue of sugar cane, for the degradation of three pesticides, glyphosate, malathion and lambda-cyhalothrin. Results showed that more than 99% of malathion and glyphosate were degraded in 6 months. In the biological bed, the DT(50) value for malathion was 17 days, for glyphosate 33 days and for lambda-cyhalothrin 43 days. The degradation rate of aminomethylphosphonic acid (AMPA) residues from the degradation of glyphosate was slower than that of the other pesticides (DT(50) 69 days). Finally, the innocuousness of the biomix after 6 months of degradation was confirmed by biological tests. Although the degradation rates of the three pesticides in the present bagasse-based system were similar to those under temperate conditions, the degradation conditions were improved by comparison with those in soil under the given tropical conditions. Further benefits of this system are pesticide confinement, to avoid their dispersion in the environment by liquids or solids, and a lower overall cost. Finally, possibilities for optimising the bagasse-based system (e.g. management of the water content and nature of the biomix) are discussed.

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

Magnetic nanoparticles in different biological environments analyzed by magnetic particle spectroscopy

NASA Astrophysics Data System (ADS)

Löwa, Norbert; Seidel, Maria; Radon, Patricia; Wiekhorst, Frank

2017-04-01

Quantification of magnetic iron oxide nanoparticles (MNP) in biological systems like cells, tissue, or organs is of vital importance for development of novel biomedical applications, e.g. magnetofection, drug targeting or hyperthermia. Among others, the recently developed magnetic measurement technique magnetic particle spectroscopy (MPS) provides signals that are specific for MNP. MPS is based on the non-linear magnetic response of MNP exposed to a strong sinusoidal excitation field of up to 25 mT amplitude and 25 kHz frequency. So far, it has been proven a powerful tool for quantification of MNP in biological systems. In this study we investigated in detail the influence of typical biological media on the magnetic behavior of different MNP systems by MPS. The results reveal that amplitude and shape (ratio of harmonics) of the MPS spectra allow for perceptively monitoring changes in MNP magnetism caused by different physiological media. Additionally, the observed linear correlation between MPS amplitude and shape alterations can be used to reduce the quantification uncertainty for MNP suspended in a biological environment.

Computer retina that models the primate retina

NASA Astrophysics Data System (ADS)

Shah, Samir; Levine, Martin D.

1994-06-01

At the retinal level, the strategies utilized by biological visual systems allow them to outperform machine vision systems, serving to motivate the design of electronic or `smart' sensors based on similar principles. Design of such sensors in silicon first requires a model of retinal information processing which captures the essential features exhibited by biological retinas. In this paper, a simple retinal model is presented, which qualitatively accounts for the achromatic information processing in the primate cone system. The model exhibits many of the properties found in biological retina such as data reduction through nonuniform sampling, adaptation to a large dynamic range of illumination levels, variation of visual acuity with illumination level, and enhancement of spatio temporal contrast information. The model is validated by replicating experiments commonly performed by electrophysiologists on biological retinas and comparing the response of the computer retina to data from experiments in monkeys. In addition, the response of the model to synthetic images is shown. The experiments demonstrate that the model behaves in a manner qualitatively similar to biological retinas and thus may serve as a basis for the development of an `artificial retina.'

Fock space, symbolic algebra, and analytical solutions for small stochastic systems.

PubMed

Santos, Fernando A N; Gadêlha, Hermes; Gaffney, Eamonn A

2015-12-01

Randomness is ubiquitous in nature. From single-molecule biochemical reactions to macroscale biological systems, stochasticity permeates individual interactions and often regulates emergent properties of the system. While such systems are regularly studied from a modeling viewpoint using stochastic simulation algorithms, numerous potential analytical tools can be inherited from statistical and quantum physics, replacing randomness due to quantum fluctuations with low-copy-number stochasticity. Nevertheless, classical studies remained limited to the abstract level, demonstrating a more general applicability and equivalence between systems in physics and biology rather than exploiting the physics tools to study biological systems. Here the Fock space representation, used in quantum mechanics, is combined with the symbolic algebra of creation and annihilation operators to consider explicit solutions for the chemical master equations describing small, well-mixed, biochemical, or biological systems. This is illustrated with an exact solution for a Michaelis-Menten single enzyme interacting with limited substrate, including a consideration of very short time scales, which emphasizes when stiffness is present even for small copy numbers. Furthermore, we present a general matrix representation for Michaelis-Menten kinetics with an arbitrary number of enzymes and substrates that, following diagonalization, leads to the solution of this ubiquitous, nonlinear enzyme kinetics problem. For this, a flexible symbolic maple code is provided, demonstrating the prospective advantages of this framework compared to stochastic simulation algorithms. This further highlights the possibilities for analytically based studies of stochastic systems in biology and chemistry using tools from theoretical quantum physics.

Stochastic simulation in systems biology

PubMed Central

Székely, Tamás; Burrage, Kevin

2014-01-01

Natural systems are, almost by definition, heterogeneous: this can be either a boon or an obstacle to be overcome, depending on the situation. Traditionally, when constructing mathematical models of these systems, heterogeneity has typically been ignored, despite its critical role. However, in recent years, stochastic computational methods have become commonplace in science. They are able to appropriately account for heterogeneity; indeed, they are based around the premise that systems inherently contain at least one source of heterogeneity (namely, intrinsic heterogeneity). In this mini-review, we give a brief introduction to theoretical modelling and simulation in systems biology and discuss the three different sources of heterogeneity in natural systems. Our main topic is an overview of stochastic simulation methods in systems biology. There are many different types of stochastic methods. We focus on one group that has become especially popular in systems biology, biochemistry, chemistry and physics. These discrete-state stochastic methods do not follow individuals over time; rather they track only total populations. They also assume that the volume of interest is spatially homogeneous. We give an overview of these methods, with a discussion of the advantages and disadvantages of each, and suggest when each is more appropriate to use. We also include references to software implementations of them, so that beginners can quickly start using stochastic methods for practical problems of interest. PMID:25505503

Results of the Alternative Water Processor Test, A Novel Technology for Exploration Wastewater Remediation

NASA Technical Reports Server (NTRS)

Vega, Leticia; Meyer, Caitlin

2016-01-01

Biologically-based water recovery systems are a regenerative, low energy alternative to physiochemical processes to reclaim water from wastewater. This paper summarizes the results of the Alternative Water Processor (AWP) test conducted over one year. The AWP recovered 90% of water from four crewmembers using (4) membrane aerated bioreactors (MABRs) to remove carbon and nitrogen from an exploration mission wastewater, including urine, hygiene, laundry and humidity condensate. Downstream, a coupled forward and reverse osmosis system removed large organics and inorganic salts from the biological system effluent. The system exceeded the overall objectives of the test by recovering 90% of the influent wastewater processed and a 29% reduction of consumables from the current state of the art water recovery system on the International Space Station (ISS). However the biological system fell short of its test goals, failing to remove 75% and 90% of the influent ammonium and organic carbon, respectively. Despite not meeting its test goals, the BWP demonstrated the feasibility of an attached-growth biological system for simultaneous nitrification and denitrification, an innovative, volume and consumable-saving design that doesn't require toxic pretreatment. This paper will explain the reasons for this and will discuss steps to optimize each subsystem to increase effluent quality from the MABRs and the FOST to advance the system.

Results of the Alternative Water Processor Test, A Novel Technology for Exploration Wastewater Remediation

NASA Technical Reports Server (NTRS)

Vega, Leticia; Meyer, Caitlin

2015-01-01

Biologically-based water recovery systems are a regenerative, low energy alternative to physiochemical processes to reclaim water from wastewater. This paper summarizes the results of the Alternative Water Processor (AWP) test conducted over one year. The AWP recovered 90% of water from four crewmembers using (4) membrane aerated bioreactors (MABRs) to remove carbon and nitrogen from an exploration mission wastewater, including urine, hygiene, laundry and humidity condensate. Downstream, a coupled forward and reverse osmosis system removed large organics and inorganic salts from the biological system effluent. The system exceeded the overall objectives of the test by recovering 90% of the influent wastewater processed and a 29% reduction of consumables from the current state of the art water recovery system on the International Space Station (ISS). However the biological system fell short of its test goals, failing to remove 75% and 90% of the influent ammonium and organic carbon, respectively. Despite not meeting its test goals, the BWP demonstrated the feasibility of an attachedgrowth biological system for simultaneous nitrification and denitrification, an innovative, volume and consumable-saving design that doesn't require toxic pretreatment. This paper will explain the reasons for this and will discuss steps to optimize each subsystem to increase effluent quality from the MABRs and the FOST to advance the system.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly.

PubMed

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-28

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.

Gravitational Biology Facility on Space Station: Meeting the needs of space biology

NASA Technical Reports Server (NTRS)

Allen, Katherine; Wade, Charles

1992-01-01

The Gravitational Biology Facility (GBF) is a set of generic laboratory equipment needed to conduct research on Space Station Freedom (SSF), focusing on Space Biology Program science (Cell and Developmental Biology and Plant Biology). The GBF will be functional from the earliest utilization flights through the permanent manned phase. Gravitational biology research will also make use of other Life Sciences equipment on the space station as well as existing equipment developed for the space shuttle. The facility equipment will be developed based on requirements derived from experiments proposed by the scientific community to address critical questions in the Space Biology Program. This requires that the facility have the ability to house a wide variety of species, various methods of observation, and numerous methods of sample collection, preservation, and storage. The selection of the equipment will be done by the members of a scientific working group (5 members representing cell biology, 6 developmental biology, and 6 plant biology) who also provide requirements to design engineers to ensure that the equipment will meet scientific needs. All equipment will undergo extensive ground based experimental validation studies by various investigators addressing a variety of experimental questions. Equipment will be designed to be adaptable to other space platforms. The theme of the Gravitational Biology Facility effort is to provide optimal and reliable equipment to answer the critical questions in Space Biology as to the effects of gravity on living systems.

Agent Based Modeling Applications for Geosciences

NASA Astrophysics Data System (ADS)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in a thermodynamic framework as a set of reactions that roll-up the integrated effect that diverse biological communities exert on a geological system. This approach may work well to predict the effect of certain biological communities in specific environments in which experimental data is available. However, it does not further our knowledge of how the geobiological system actually functions on a micro scale. Agent-based techniques may provide a framework to explore the fundamental interactions required to explain the system-wide behavior. This presentation will present a survey of several promising applications of agent-based modeling approaches to problems in the geosciences and describe specific contributions to some of the inherent challenges facing this approach.

Payao: a community platform for SBML pathway model curation

PubMed Central

Matsuoka, Yukiko; Ghosh, Samik; Kikuchi, Norihiro; Kitano, Hiroaki

2010-01-01

Summary: Payao is a community-based, collaborative web service platform for gene-regulatory and biochemical pathway model curation. The system combines Web 2.0 technologies and online model visualization functions to enable a collaborative community to annotate and curate biological models. Payao reads the models in Systems Biology Markup Language format, displays them with CellDesigner, a process diagram editor, which complies with the Systems Biology Graphical Notation, and provides an interface for model enrichment (adding tags and comments to the models) for the access-controlled community members. Availability and implementation: Freely available for model curation service at http://www.payaologue.org. Web site implemented in Seaser Framework 2.0 with S2Flex2, MySQL 5.0 and Tomcat 5.5, with all major browsers supported. Contact: kitano@sbi.jp PMID:20371497

Advances in Omics and Bioinformatics Tools for Systems Analyses of Plant Functions

PubMed Central

Mochida, Keiichi; Shinozaki, Kazuo

2011-01-01

Omics and bioinformatics are essential to understanding the molecular systems that underlie various plant functions. Recent game-changing sequencing technologies have revitalized sequencing approaches in genomics and have produced opportunities for various emerging analytical applications. Driven by technological advances, several new omics layers such as the interactome, epigenome and hormonome have emerged. Furthermore, in several plant species, the development of omics resources has progressed to address particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we provide this review of the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances. PMID:22156726

Genomics, "Discovery Science," Systems Biology, and Causal Explanation: What Really Works?

PubMed

Davidson, Eric H

2015-01-01

Diverse and non-coherent sets of epistemological principles currently inform research in the general area of functional genomics. Here, from the personal point of view of a scientist with over half a century of immersion in hypothesis driven scientific discovery, I compare and deconstruct the ideological bases of prominent recent alternatives, such as "discovery science," some productions of the ENCODE project, and aspects of large data set systems biology. The outputs of these types of scientific enterprise qualitatively reflect their radical definitions of scientific knowledge, and of its logical requirements. Their properties emerge in high relief when contrasted (as an example) to a recent, system-wide, predictive analysis of a developmental regulatory apparatus that was instead based directly on hypothesis-driven experimental tests of mechanism.

Synthetic biology and its alternatives. Descartes, Kant and the idea of engineering biological machines.

PubMed

Kogge, Werner; Richter, Michael

2013-06-01

The engineering-based approach of synthetic biology is characterized by an assumption that 'engineering by design' enables the construction of 'living machines'. These 'machines', as biological machines, are expected to display certain properties of life, such as adapting to changing environments and acting in a situated way. This paper proposes that a tension exists between the expectations placed on biological artefacts and the notion of producing such systems by means of engineering; this tension makes it seem implausible that biological systems, especially those with properties characteristic of living beings, can in fact be produced using the specific methods of engineering. We do not claim that engineering techniques have nothing to contribute to the biotechnological construction of biological artefacts. However, drawing on Descartes's and Kant's thinking on the relationship between the organism and the machine, we show that it is considerably more plausible to assume that distinctively biological artefacts emerge within a paradigm different from the paradigm of the Cartesian machine that underlies the engineering approach. We close by calling for increased attention to be paid to approaches within molecular biology and chemistry that rest on conceptions different from those of synthetic biology's engineering paradigm. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of socioscientific issues-based instruction on argumentation ability and biology concepts of upper secondary school students

NASA Astrophysics Data System (ADS)

Faelt, Surasak; Samiphak, Sara; Pattaradilokrat, Sittiporn

2018-01-01

Argumentation skill is an essential skill needed in students, and one of the competencies in scientific literacy. Through arguing on socioscientific issues, students may gain deeper conceptual understanding. The purpose of this research is to examine the efficacy of a socioscientific issues-based instruction compared with an inquirybased instruction. This is to determine which one is better in promoting 10th grade students' argumentation ability and biology concepts of digestive system and cellular respiration. The forty 10th grade students included in this study were from two mathematics-science program classes in a medium-sized secondary school located in a suburb of Buriram province, Thailand. The research utilizes a quasi-experimental design; pre-test post-test control group design. We developed and implemented 4 lesson plans for both socioscientific issues-based instruction and inquiry-based instruction. Ten weeks were used to collect the data. A paper-based questionnaire and informal interviews were designed to test students' argumentation ability, and the two-tier multiple-choice test was designed to test their biology concepts. This research explore qualitatively and quantitatively students' argumentation abilities and biology concepts, using arithmetic mean, mean of percentage, standard deviation and t-test. Results show that there is no significant difference between the two group regarding mean scores of the argumentation ability. However, there is significant difference between the two groups regarding mean scores of the biology concepts. This suggests that socioscientific issues-based instruction could be used to improve students' biology concepts.

Molecular biomimetics: GEPI-based biological routes to technology.

PubMed

Tamerler, Candan; Khatayevich, Dmitriy; Gungormus, Mustafa; Kacar, Turgay; Oren, E Emre; Hnilova, Marketa; Sarikaya, Mehmet

2010-01-01

In nature, the viability of biological systems is sustained via specific interactions among the tens of thousands of proteins, the major building blocks of organisms from the simplest single-celled to the most complex multicellular species. Biomolecule-material interaction is accomplished with molecular specificity and efficiency leading to the formation of controlled structures and functions at all scales of dimensional hierarchy. Through evolution, Mother Nature developed molecular recognition by successive cycles of mutation and selection. Molecular specificity of probe-target interactions, e.g., ligand-receptor, antigen-antibody, is always based on specific peptide molecular recognition. Using biology as a guide, we can now understand, engineer, and control peptide-material interactions and exploit them as a new design tool for novel materials and systems. We adapted the protocols of combinatorially designed peptide libraries, via both cell surface or phage display methods; using these we select short peptides with specificity to a variety of practical materials. These genetically engineered peptides for inorganics (GEPI) are then studied experimentally to establish their binding kinetics and surface stability. The bound peptide structure and conformations are interrogated both experimentally and via modeling, and self-assembly characteristics are tested via atomic force microscopy. We further engineer the peptide binding and assembly characteristics using a computational biomimetics approach where bioinformatics based peptide-sequence similarity analysis is developed to design higher generation function-specific peptides. The molecular biomimetic approach opens up new avenues for the design and utilization of multifunctional molecular systems in a wide-range of applications from tissue engineering, disease diagnostics, and therapeutics to various areas of nanotechnology where integration is required among inorganic, organic and biological materials. Here, we describe lessons from biology with examples of protein-mediated functional biological materials, explain how novel peptides can be designed with specific affinity to inorganic solids using evolutionary engineering approaches, give examples of their potential utilizations in technology and medicine, and, finally, provide a summary of challenges and future prospects. (c) 2010 Wiley Periodicals, Inc.

Electrochemical reverse engineering: A systems-level tool to probe the redox-based molecular communication of biology.

PubMed

Li, Jinyang; Liu, Yi; Kim, Eunkyoung; March, John C; Bentley, William E; Payne, Gregory F

2017-04-01

The intestine is the site of digestion and forms a critical interface between the host and the outside world. This interface is composed of host epithelium and a complex microbiota which is "connected" through an extensive web of chemical and biological interactions that determine the balance between health and disease for the host. This biology and the associated chemical dialogues occur within a context of a steep oxygen gradient that provides the driving force for a variety of reduction and oxidation (redox) reactions. While some redox couples (e.g., catecholics) can spontaneously exchange electrons, many others are kinetically "insulated" (e.g., biothiols) allowing the biology to set and control their redox states far from equilibrium. It is well known that within cells, such non-equilibrated redox couples are poised to transfer electrons to perform reactions essential to immune defense (e.g., transfer from NADH to O 2 for reactive oxygen species, ROS, generation) and protection from such oxidative stresses (e.g., glutathione-based reduction of ROS). More recently, it has been recognized that some of these redox-active species (e.g., H 2 O 2 ) cross membranes and diffuse into the extracellular environment including lumen to transmit redox information that is received by atomically-specific receptors (e.g., cysteine-based sulfur switches) that regulate biological functions. Thus, redox has emerged as an important modality in the chemical signaling that occurs in the intestine and there have been emerging efforts to develop the experimental tools needed to probe this modality. We suggest that electrochemistry provides a unique tool to experimentally probe redox interactions at a systems level. Importantly, electrochemistry offers the potential to enlist the extensive theories established in signal processing in an effort to "reverse engineer" the molecular communication occurring in this complex biological system. Here, we review our efforts to develop this electrochemical tool for in vitro redox-probing. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of Ion Irradiation on Seedlings Growth Monitored by Ultraweak Delayed Luminescence

PubMed Central

Abe, Tomoko; Cirrone, Giuseppe A. P.; Cuttone, Giacomo; Gulino, Marisa; Musumeci, Francesco; Romano, Francesco; Ryuto, Hiromichi; Scordino, Agata

2016-01-01

The optical technique based on the measurement of delayed luminescence emitted from the biological samples has demonstrated its ability to provide valid and predictive information on the functional status of various biological systems. We want to extend this technique to study the effect of ionizing radiation on biological systems. In particular we are interested in the action of ion beams, used for therapeutic purposes or to increase the biological diversity. In general, the assessment of the damage that radiation produces both in the target objects and in the surrounding tissues, requires considerable time because is based on biochemical analysis or on the examination of the evolution of the irradiated systems. The delayed luminescence technique could help to simplify this investigation. We have so started our studies performing irradiations of some relatively simple vegetable models. In this paper we report results obtained from mung bean (Vigna radiata) seeds submitted to a 12C ion beam at the energy of 62 MeV/nucleon. The dry seeds were irradiated at doses from 50 to 7000 Gy. The photoinduced delayed luminescence of each seed before and after ion irradiation was measured. The growth of seedlings after irradiation was compared with that of untreated seeds. A growth reduction on increasing the dose was registered. The results show strong correlations between the ion irradiation dose, seeds growth and delayed luminescence intensity. In particular, the delayed luminescence intensity is correlated by a logistic function to the seedlings elongation and, after performing a suitable measurement campaign based on blind tests, it could become a tool able to predict the growth of seeds after ion irradiation. Moreover these results demonstrate that measurements of delayed luminescence could be used as a fast and non-invasive technique to check the effects of ion beams on relatively simple biological systems. PMID:27936220

PANDORA: keyword-based analysis of protein sets by integration of annotation sources.

PubMed

Kaplan, Noam; Vaaknin, Avishay; Linial, Michal

2003-10-01

Recent advances in high-throughput methods and the application of computational tools for automatic classification of proteins have made it possible to carry out large-scale proteomic analyses. Biological analysis and interpretation of sets of proteins is a time-consuming undertaking carried out manually by experts. We have developed PANDORA (Protein ANnotation Diagram ORiented Analysis), a web-based tool that provides an automatic representation of the biological knowledge associated with any set of proteins. PANDORA uses a unique approach of keyword-based graphical analysis that focuses on detecting subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA currently supports SwissProt keywords, NCBI Taxonomy, InterPro entries and the hierarchical classification terms from ENZYME, SCOP and GO databases. The integrated study of several annotation sources simultaneously allows a representation of biological relations of structure, function, cellular location, taxonomy, domains and motifs. PANDORA is also integrated into the ProtoNet system, thus allowing testing thousands of automatically generated clusters. We illustrate how PANDORA enhances the biological understanding of large, non-uniform sets of proteins originating from experimental and computational sources, without the need for prior biological knowledge on individual proteins.

Enzyme-regulated the changes of pH values for assembling a colorimetric and multistage interconnection logic network with multiple readouts.

PubMed

Huang, Yanyan; Ran, Xiang; Lin, Youhui; Ren, Jinsong; Qu, Xiaogang

2015-04-22

Based on enzymatic reactions-triggered changes of pH values and biocomputing, a novel and multistage interconnection biological network with multiple easy-detectable signal outputs has been developed. Compared with traditional chemical computing, the enzyme-based biological system could overcome the interference between reactions or the incompatibility of individual computing gates and offer a unique opportunity to assemble multicomponent/multifunctional logic circuitries. Our system included four enzyme inputs: β-galactosidase (β-gal), glucose oxidase (GOx), esterase (Est) and urease (Ur). With the assistance of two signal transducers (gold nanoparticles and acid-base indicators) or pH meter, the outputs of the biological network could be conveniently read by the naked eyes. In contrast to current methods, the approach present here could realize cost-effective, label-free and colorimetric logic operations without complicated instrument. By designing a series of Boolean logic operations, we could logically make judgment of the compositions of the samples on the basis of visual output signals. Our work offered a promising paradigm for future biological computing technology and might be highly useful in future intelligent diagnostics, prodrug activation, smart drug delivery, process control, and electronic applications. Copyright © 2015 Elsevier B.V. All rights reserved.

ShinyKGode: an interactive application for ODE parameter inference using gradient matching.

PubMed

Wandy, Joe; Niu, Mu; Giurghita, Diana; Daly, Rónán; Rogers, Simon; Husmeier, Dirk

2018-07-01

Mathematical modelling based on ordinary differential equations (ODEs) is widely used to describe the dynamics of biological systems, particularly in systems and pathway biology. Often the kinetic parameters of these ODE systems are unknown and have to be inferred from the data. Approximate parameter inference methods based on gradient matching (which do not require performing computationally expensive numerical integration of the ODEs) have been getting popular in recent years, but many implementations are difficult to run without expert knowledge. Here, we introduce ShinyKGode, an interactive web application to perform fast parameter inference on ODEs using gradient matching. ShinyKGode can be used to infer ODE parameters on simulated and observed data using gradient matching. Users can easily load their own models in Systems Biology Markup Language format, and a set of pre-defined ODE benchmark models are provided in the application. Inferred parameters are visualized alongside diagnostic plots to assess convergence. The R package for ShinyKGode can be installed through the Comprehensive R Archive Network (CRAN). Installation instructions, as well as tutorial videos and source code are available at https://joewandy.github.io/shinyKGode. Supplementary data are available at Bioinformatics online.

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Lipidomics: a global approach to lipid analysis in biological systems.

PubMed

Watson, Andrew D

2006-10-01

Lipids are water-insoluble molecules that have a wide variety of functions within cells, including: 1) maintenance of electrochemical gradients; 2) subcellular partitioning; 3) first- and second-messenger cell signaling; 4) energy storage; and 5) protein trafficking and membrane anchoring. The physiological importance of lipids is illustrated by the numerous diseases to which lipid abnormalities contribute, including atherosclerosis, diabetes, obesity, and Alzheimer's disease. Lipidomics, a branch of metabolomics, is a systems-based study of all lipids, the molecules with which they interact, and their function within the cell. Recent advances in soft-ionization mass spectrometry, combined with established separation techniques, have allowed the rapid and sensitive detection of a variety of lipid species with minimal sample preparation. A "lipid profile" from a crude lipid extract is a mass spectrum of the composition and abundance of the lipids it contains, which can be used to monitor changes over time and in response to particular stimuli. Lipidomics, integrated with genomics, proteomics, and metabolomics, will contribute toward understanding how lipids function in a biological system and will provide a powerful tool for elucidating the mechanism of lipid-based disease, for biomarker screening, and for monitoring pharmacologic therapy.

Endobiogeny: a global approach to systems biology (part 2 of 2).

PubMed

Lapraz, Jean-Claude; Hedayat, Kamyar M; Pauly, Patrice

2013-03-01

ENDOBIOGENY AND THE BIOLOGY OF FUNCTIONS ARE BASED ON FOUR SCIENTIFIC CONCEPTS THAT ARE KNOWN AND GENERALLY ACCEPTED: (1) human physiology is complex and multifactorial and exhibits the properties of a system; (2) the endocrine system manages metabolism, which is the basis of the continuity of life; (3) the metabolic activity managed by the endocrine system results in the output of biomarkers that reflect the functional achievement of specific aspects of metabolism; and (4) when biomarkers are related to each other in ratios, it contextualizes one type of function relative to another to which is it linked anatomically, sequentially, chronologically, biochemically, etc.

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

A global parallel model based design of experiments method to minimize model output uncertainty.

PubMed

Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E

2012-03-01

Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.

The -omics Era- Toward a Systems-Level Understanding of Streptomyces

PubMed Central

Zhou, Zhan; Gu, Jianying; Du, Yi-Ling; Li, Yong-Quan; Wang, Yufeng

2011-01-01

Streptomyces is a group of soil bacteria of medicinal, economic, ecological, and industrial importance. It is renowned for its complex biology in gene regulation, antibiotic production, morphological differentiation, and stress response. In this review, we provide an overview of the recent advances in Streptomyces biology inspired by -omics based high throughput technologies. In this post-genomic era, vast amounts of data have been integrated to provide significant new insights into the fundamental mechanisms of system control and regulation dynamics of Streptomyces. PMID:22379394

Rigid Biological Systems as Models for Synthetic Composites

NASA Astrophysics Data System (ADS)

Mayer, George

2005-11-01

Advances that have been made in understanding the mechanisms underlying the mechanical behavior of a number of biological materials (namely mollusk shells and sponge spicules) are discussed here. Attempts at biomimicry of the structure of a nacreous layer of a mollusk shell have shown reasonable success. However, they have revealed additional issues that must be addressed if new synthetic composite materials that are based on natural systems are to be constructed. Some of the important advantages and limitations of copying from nature are also described here.

Data Integration and Mining for Synthetic Biology Design.

PubMed

Mısırlı, Göksel; Hallinan, Jennifer; Pocock, Matthew; Lord, Phillip; McLaughlin, James Alastair; Sauro, Herbert; Wipat, Anil

2016-10-21

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

Conceptual biology, hypothesis discovery, and text mining: Swanson's legacy.

PubMed

Bekhuis, Tanja

2006-04-03

Innovative biomedical librarians and information specialists who want to expand their roles as expert searchers need to know about profound changes in biology and parallel trends in text mining. In recent years, conceptual biology has emerged as a complement to empirical biology. This is partly in response to the availability of massive digital resources such as the network of databases for molecular biologists at the National Center for Biotechnology Information. Developments in text mining and hypothesis discovery systems based on the early work of Swanson, a mathematician and information scientist, are coincident with the emergence of conceptual biology. Very little has been written to introduce biomedical digital librarians to these new trends. In this paper, background for data and text mining, as well as for knowledge discovery in databases (KDD) and in text (KDT) is presented, then a brief review of Swanson's ideas, followed by a discussion of recent approaches to hypothesis discovery and testing. 'Testing' in the context of text mining involves partially automated methods for finding evidence in the literature to support hypothetical relationships. Concluding remarks follow regarding (a) the limits of current strategies for evaluation of hypothesis discovery systems and (b) the role of literature-based discovery in concert with empirical research. Report of an informatics-driven literature review for biomarkers of systemic lupus erythematosus is mentioned. Swanson's vision of the hidden value in the literature of science and, by extension, in biomedical digital databases, is still remarkably generative for information scientists, biologists, and physicians.

Spray-Dried Nanoparticle-in-Microparticle Delivery Systems (NiMDS) for Gene Delivery, Comprising Polyethylenimine (PEI)-Based Nanoparticles in a Poly(Vinyl Alcohol) Matrix.

PubMed

Schulze, Jan; Kuhn, Stephanie; Hendrikx, Stephan; Schulz-Siegmund, Michaela; Polte, Tobias; Aigner, Achim

2018-03-01

Nucleic acid-based therapies rely on efficient formulations for nucleic acid protection and delivery. As nonviral strategies, polymeric and lipid-based nanoparticles have been introduced; however, biological efficacy and biocompatibility as well as poor storage properties due to colloidal instability and their unavailability as ready-to-use systems are still major issues. Polyethylenimine is the most widely explored and promising candidate for gene delivery. Polyethylenimine-based polyplexes and their combination with liposomes, lipopolyplexes, are efficient for DNA or siRNA delivery in vitro and in vivo. In this study, a highly potent spray-dried nanoparticle-in-microparticle delivery system is presented for the encapsulation of polyethylenimine-based polyplexes and lipopolyplexes into poly(vinyl alcohol) microparticles, without requiring additional stabilizing agents. This easy-to-handle gene delivery device allows prolonged nanoparticle storage and protection at ambient temperature. Biological analyses reveal further advantages regarding profoundly reduced cytotoxicity and enhanced transfection efficacies of polyethylenimine-based nanoparticles from the nanoparticle-in-microparticle delivery system over their freshly prepared counterparts, as determined in various cell lines. Importantly, this nanoparticle-in-microparticle delivery system is demonstrated as ready-to-use dry powder to be an efficient device for the inhalative delivery of polyethylenimine-based lipopolyplexes in vivo, as shown by transgene expression in mice after only one administration. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

Rapid Start-up and Loading of an Attached Growth, Simultaneous Nitrification/Denitrification Membrane Aerated Bioreactor

NASA Technical Reports Server (NTRS)

Meyer, Caitlin E.; Pensinger, Stuart; Pickering, Karen D.; Barta, Daniel; Shull, Sarah A.; Vega, Letticia M.; Christenson, Dylan; Jackson, W. Andrew

2015-01-01

Membrane aerated bioreactors (MABR) are attached-growth biological systems used for simultaneous nitrification and denitrification to reclaim water from waste. This design is an innovative approach to common terrestrial wastewater treatments for nitrogen and carbon removal and implementing a biologically-based water treatment system for long-duration human exploration is an attractive, low energy alternative to physiochemical processes. Two obstacles to implementing such a system are (1) the "start-up" duration from inoculation to steady-state operations and (2) the amount of surface area needed for the biological activity to occur. The Advanced Water Recovery Systems (AWRS) team at JSC explored these two issues through two tests; a rapid inoculation study and a wastewater loading study. Results from these tests demonstrate that the duration from inoculation to steady state can be reduced to under two weeks, and that despite low ammonium removal rates, the MABRs are oversized.

Cross-generational influences on childhood anxiety disorders: pathways and mechanisms

PubMed Central

Leckman, James F.; Silverman, Wendy K.; Feldman, Ruth

2016-01-01

Anxiety disorders are common across the lifespan, cause severe distress and impairment, and usually have their onset in childhood. Substantial clinical and epidemiological research has demonstrated the existence of links between anxiety and its disorders in children and parents. Research on the pathways and mechanisms underlying these links has pointed to both behavioral and biological systems. This review synthesizes and summarizes several major aspects of this research. Behavioral systems include vicarious learning, social referencing, and modeling of parental anxiety; overly protective or critical parenting styles; and aspects of parental responses to child anxiety including family accommodation of the child’s symptoms. Biological systems include aspects of the prenatal environment affected by maternal anxiety, development and functioning of the oxytocinergic system, and genetic and epigenetic transmission. Implications for the prevention and treatment of child anxiety disorders are discussed, including the potential to enhance child anxiety treatment outcomes through biologically informed parent-based interventions. PMID:27145763

Cross-generational influences on childhood anxiety disorders: pathways and mechanisms.

PubMed

Lebowitz, Eli R; Leckman, James F; Silverman, Wendy K; Feldman, Ruth

2016-09-01

Anxiety disorders are common across the lifespan, cause severe distress and impairment, and usually have their onset in childhood. Substantial clinical and epidemiological research has demonstrated the existence of links between anxiety and its disorders in children and parents. Research on the pathways and mechanisms underlying these links has pointed to both behavioral and biological systems. This review synthesizes and summarizes several major aspects of this research. Behavioral systems include vicarious learning, social referencing, and modeling of parental anxiety; overly protective or critical parenting styles; and aspects of parental responses to child anxiety including family accommodation of the child's symptoms. Biological systems include aspects of the prenatal environment affected by maternal anxiety, development and functioning of the oxytocinergic system, and genetic and epigenetic transmission. Implications for the prevention and treatment of child anxiety disorders are discussed, including the potential to enhance child anxiety treatment outcomes through biologically informed parent-based interventions.

Relations between intuitive biological thinking and biological misconceptions in biology majors and nonmajors.

PubMed

Coley, John D; Tanner, Kimberly

2015-03-02

Research and theory development in cognitive psychology and science education research remain largely isolated. Biology education researchers have documented persistent scientifically inaccurate ideas, often termed misconceptions, among biology students across biological domains. In parallel, cognitive and developmental psychologists have described intuitive conceptual systems--teleological, essentialist, and anthropocentric thinking--that humans use to reason about biology. We hypothesize that seemingly unrelated biological misconceptions may have common origins in these intuitive ways of knowing, termed cognitive construals. We presented 137 undergraduate biology majors and nonmajors with six biological misconceptions. They indicated their agreement with each statement, and explained their rationale for their response. Results indicate frequent agreement with misconceptions, and frequent use of construal-based reasoning among both biology majors and nonmajors in their written explanations. Moreover, results also show associations between specific construals and the misconceptions hypothesized to arise from those construals. Strikingly, such associations were stronger among biology majors than nonmajors. These results demonstrate important linkages between intuitive ways of thinking and misconceptions in discipline-based reasoning, and raise questions about the origins, persistence, and generality of relations between intuitive reasoning and biological misconceptions. © 2015 J. D. Coley and K. Tanner. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Therapeutic target discovery using Boolean network attractors: improvements of kali

PubMed Central

Guziolowski, Carito

2018-01-01

In a previous article, an algorithm for identifying therapeutic targets in Boolean networks modelling pathological mechanisms was introduced. In the present article, the improvements made on this algorithm, named kali, are described. These improvements are (i) the possibility to work on asynchronous Boolean networks, (ii) a finer assessment of therapeutic targets and (iii) the possibility to use multivalued logic. kali assumes that the attractors of a dynamical system, such as a Boolean network, are associated with the phenotypes of the modelled biological system. Given a logic-based model of pathological mechanisms, kali searches for therapeutic targets able to reduce the reachability of the attractors associated with pathological phenotypes, thus reducing their likeliness. kali is illustrated on an example network and used on a biological case study. The case study is a published logic-based model of bladder tumorigenesis from which kali returns consistent results. However, like any computational tool, kali can predict but cannot replace human expertise: it is a supporting tool for coping with the complexity of biological systems in the field of drug discovery. PMID:29515890

LTI system order reduction approach based on asymptotical equivalence and the Co-operation of biology-related algorithms

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.; Akhmedova, Sh A.

2017-02-01

A novel order reduction method for linear time invariant systems is described. The method is based on reducing the initial problem to an optimization one, using the proposed model representation, and solving the problem with an efficient optimization algorithm. The proposed method of determining the model allows all the parameters of the model with lower order to be identified and by definition, provides the model with the required steady-state. As a powerful optimization tool, the meta-heuristic Co-Operation of Biology-Related Algorithms was used. Experimental results proved that the proposed approach outperforms other approaches and that the reduced order model achieves a high level of accuracy.

A biosensor system using nickel ferrite nanoparticles

NASA Astrophysics Data System (ADS)

Singh, Prachi; Rathore, Deepshikha

2016-05-01

NiFe2O4 ferrite nanoparticles were synthesized by chemical co-precipitation method and the structural characteristics were investigated using X-ray diffraction technique, where single cubic phase formation of nanoparticles was confirmed. The average particle size of NiFe2O4 was found to be 4.9 nm. Nanoscale magnetic materials are an important source of labels for biosensing due to their strong magnetic properties which are not found in biological systems. This property of the material was exploited and the fabrication of the NiFe2O4 nanoparticle based biosensor was done in the form of a capacitor system, with NiFe2O4 as the dielectric material. The biosensor system was tested towards different biological materials with the help of electrochemical workstation and the same was analysed through Cole-Cole plot of NiFe2O4. The performance of the sensor was determined based on its sensitivity, response time and recovery time.

Multiphoton microscopy system with a compact fiber-based femtosecond-pulse laser and handheld probe

PubMed Central

Liu, Gangjun; Kieu, Khanh; Wise, Frank W.; Chen, Zhongping

2012-01-01

We report on the development of a compact multiphoton microscopy (MPM) system that integrates a compact and robust fiber laser with a miniature probe. The all normal dispersion fiber femtosecond laser has a central wavelength of 1.06 μm, pulse width of 125 fs and average power of more than 1 W. A double cladding photonic crystal fiber was used to deliver the excitation beam and to collect the two-photon signal. The hand-held probe included galvanometer-based mirror scanners, relay lenses and a focusing lens. The packaged probe had a diameter of 16 mm. Second harmonic generation (SHG) images and two-photon excited fluorescence (TPEF) images of biological tissues were demonstrated using the system. MPM images of different biological tissues acquired by the compact system which integrates an FBFP laser, an DCPCF and a miniature handheld probe. PMID:20635426

Interdisciplinary research and education at the biology-engineering-computer science interface: a perspective.

PubMed

Tadmor, Brigitta; Tidor, Bruce

2005-09-01

Progress in the life sciences, including genome sequencing and high-throughput experimentation, offers an opportunity for understanding biology and medicine from a systems perspective. This 'new view', which complements the more traditional component-based approach, involves the integration of biological research with approaches from engineering disciplines and computer science. The result is more than a new set of technologies. Rather, it promises a fundamental reconceptualization of the life sciences based on the development of quantitative and predictive models to describe crucial processes. To achieve this change, learning communities are being formed at the interface of the life sciences, engineering and computer science. Through these communities, research and education will be integrated across disciplines and the challenges associated with multidisciplinary team-based science will be addressed.

Biosensors and Bio-Bar Code Assays Based on Biofunctionalized Magnetic Microbeads

PubMed Central

Jaffrezic-Renault, Nicole; Martelet, Claude; Chevolot, Yann; Cloarec, Jean-Pierre

2007-01-01

This review paper reports the applications of magnetic microbeads in biosensors and bio-bar code assays. Affinity biosensors are presented through different types of transducing systems: electrochemical, piezo electric or magnetic ones, applied to immunodetection and genodetection. Enzymatic biosensors are based on biofunctionalization through magnetic microbeads of a transducer, more often amperometric, potentiometric or conductimetric. The bio-bar code assays relie on a sandwich structure based on specific biological interaction of a magnetic microbead and a nanoparticle with a defined biological molecule. The magnetic particle allows the separation of the reacted target molecules from unreacted ones. The nanoparticles aim at the amplification and the detection of the target molecule. The bio-bar code assays allow the detection at very low concentration of biological molecules, similar to PCR sensitivity.

Network Approach to Disease Diagnosis

NASA Astrophysics Data System (ADS)

Sharma, Amitabh; Bashan, Amir; Barabasi, Alber-Laszlo

2014-03-01

Human diseases could be viewed as perturbations of the underlying biological system. A thorough understanding of the topological and dynamical properties of the biological system is crucial to explain the mechanisms of many complex diseases. Recently network-based approaches have provided a framework for integrating multi-dimensional biological data that results in a better understanding of the pathophysiological state of complex diseases. Here we provide a network-based framework to improve the diagnosis of complex diseases. This framework is based on the integration of transcriptomics and the interactome. We analyze the overlap between the differentially expressed (DE) genes and disease genes (DGs) based on their locations in the molecular interaction network (''interactome''). Disease genes and their protein products tend to be much more highly connected than random, hence defining a disease sub-graph (called disease module) in the interactome. DE genes, even though different from the known set of DGs, may be significantly associated with the disease when considering their closeness to the disease module in the interactome. This new network approach holds the promise to improve the diagnosis of patients who cannot be diagnosed using conventional tools. Support was provided by HL066289 and HL105339 grants from the U.S. National Institutes of Health.

Engineering Ultimate Self-Protection in Autonomic Agents for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

NASA's Exploration Initiative (EI) will push space exploration missions to the limit. Future missions will be required to be self-managing as well as self-directed, in order to meet the challenges of human and robotic space exploration. We discuss security and self protection in autonomic agent based-systems, and propose the ultimate self-protection mechanism for such systems-self-destruction. Like other metaphors in Autonomic Computing, this is inspired by biological systems, and is the analog of biological apoptosis. Finally, we discus the role it might play in future NASA space exploration missions.

An origin of life on Mars.

PubMed

McKay, Christopher P

2010-04-01

Evidence of past liquid water on the surface of Mars suggests that this world once had habitable conditions and leads to the question of life. If there was life on Mars, it would be interesting to determine if it represented a separate origin from life on Earth. To determine the biochemistry and genetics of life on Mars requires that we have access to an organism or the biological remains of one-possibly preserved in ancient permafrost. A way to determine if organic material found on Mars represents the remains of an alien biological system could be based on the observation that biological systems select certain organic molecules over others that are chemically similar (e.g., chirality in amino acids).

An Origin of Life on Mars

PubMed Central

McKay, Christopher P.

2010-01-01

Evidence of past liquid water on the surface of Mars suggests that this world once had habitable conditions and leads to the question of life. If there was life on Mars, it would be interesting to determine if it represented a separate origin from life on Earth. To determine the biochemistry and genetics of life on Mars requires that we have access to an organism or the biological remains of one—possibly preserved in ancient permafrost. A way to determine if organic material found on Mars represents the remains of an alien biological system could be based on the observation that biological systems select certain organic molecules over others that are chemically similar (e.g., chirality in amino acids). PMID:20452949

Priorities and developments of sensors, samplers and methods for key marine biological observations.

NASA Astrophysics Data System (ADS)

Simmons, Samantha; Chavez, Francisco; Pearlman, Jay

2016-04-01

Over the last two decades or more, physical oceanography has seen a significant growth in in-situ sensors and platforms including fixed point and cable observatories, Argo floats, gliders and AUVs to supplement satellites for creating a 3-D view of the time-varying global ocean temperature and salinity structures. There are important developments recently for biogeochemists for monitoring nitrate, chemical contaminants, oxygen and pH that can now be added to these autonomous systems. Biologists are still lagging. Given the importance of biology to ocean health and the future earth, and the present reliance on humans and ships for observing species and abundance, it is paramount that new biological sensor systems be developed. Some promising sensor systems based on, but not limited to acoustic, chemical, genomic or imaging techniques, can sense from microbes to whales, are on the horizon. These techniques can be applied in situ with either real time or recorded data and can be captured and returned to the laboratory using the autonomous systems. The number of samples is limiting, requiring adaptive and smart systems. Two steps are envisioned to meeting the challenges. The first is to identify the priority biological variables to focus observation requirements and planning. The second is to address new sensors that can fill the gaps in current capabilities for biological observations. This abstract will review recent efforts to identify core biological variables for the US Integrated Ocean Observing System and address new sensors and innovations for observing these variables, particularly focused on availability and maturity of sensors.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

PubMed

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

Evaluating the feasibility of biological waste processing for long term space missions.

PubMed

Garland, J L; Alazraki, M P; Atkinson, C F; Finger, B W

1998-01-01

Recycling waste products during orbital (e.g., International Space Station) and planetary missions (e.g., lunar base, Mars transit mission, Martian base) will reduce storage and resupply costs. Wastes streams on the space station will include human hygiene water, urine, faeces, and trash. Longer term missions will contain human waste and inedible plant material from plant growth systems used for atmospheric regeneration, food production, and water recycling. The feasibility of biological and physical-chemical waste recycling is being investigated as part of National Aeronautics and Space Administration's (NASA) Advanced Life Support (ALS) Program. In-vessel composting has lower manpower requirements, lower water and volume requirements, and greater potential for sanitization of human waste compared to alternative bioreactor designs such as continuously stirred tank reactors (CSTR). Residual solids from the process (i.e. compost) could be used a biological air filter, a plant nutrient source, and a carbon sink. Potential in-vessel composting designs for both near- and long-term space missions are presented and discussed with respect to the unique aspects of space-based systems.