Arena3D: visualizing time-driven phenotypic differences in biological systems

Directory of Open Access Journals (Sweden)

Secrier Maria

2012-03-01

Full Text Available Abstract Background Elucidating the genotype-phenotype connection is one of the big challenges of modern molecular biology. To fully understand this connection, it is necessary to consider the underlying networks and the time factor. In this context of data deluge and heterogeneous information, visualization plays an essential role in interpreting complex and dynamic topologies. Thus, software that is able to bring the network, phenotypic and temporal information together is needed. Arena3D has been previously introduced as a tool that facilitates link discovery between processes. It uses a layered display to separate different levels of information while emphasizing the connections between them. We present novel developments of the tool for the visualization and analysis of dynamic genotype-phenotype landscapes. Results Version 2.0 introduces novel features that allow handling time course data in a phenotypic context. Gene expression levels or other measures can be loaded and visualized at different time points and phenotypic comparison is facilitated through clustering and correlation display or highlighting of impacting changes through time. Similarity scoring allows the identification of global patterns in dynamic heterogeneous data. In this paper we demonstrate the utility of the tool on two distinct biological problems of different scales. First, we analyze a medium scale dataset that looks at perturbation effects of the pluripotency regulator Nanog in murine embryonic stem cells. Dynamic cluster analysis suggests alternative indirect links between Nanog and other proteins in the core stem cell network. Moreover, recurrent correlations from the epigenetic to the translational level are identified. Second, we investigate a large scale dataset consisting of genome-wide knockdown screens for human genes essential in the mitotic process. Here, a potential new role for the gene lsm14a in cytokinesis is suggested. We also show how phenotypic

From systems biology to systems biomedicine.

Science.gov (United States)

Antony, Paul M A; Balling, Rudi; Vlassis, Nikos

2012-08-01

Systems Biology is about combining theory, technology, and targeted experiments in a way that drives not only data accumulation but knowledge as well. The challenge in Systems Biomedicine is to furthermore translate mechanistic insights in biological systems to clinical application, with the central aim of improving patients' quality of life. The challenge is to find theoretically well-chosen models for the contextually correct and intelligible representation of multi-scale biological systems. In this review, we discuss the current state of Systems Biology, highlight the emergence of Systems Biomedicine, and highlight some of the topics and views that we think are important for the efficient application of Systems Theory in Biomedicine. Copyright © 2011 Elsevier Ltd. All rights reserved.

Systems Biology and Ratio-Based, Real-Time Disease Surveillance.

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Fair, J M; Rivas, A L

2015-08-01

Most infectious disease surveillance methods are not well fit for early detection. To address such limitation, here we evaluated a ratio- and Systems Biology-based method that does not require prior knowledge on the identity of an infective agent. Using a reference group of birds experimentally infected with West Nile virus (WNV) and a problem group of unknown health status (except that they were WNV-negative and displayed inflammation), both groups were followed over 22 days and tested with a system that analyses blood leucocyte ratios. To test the ability of the method to discriminate small data sets, both the reference group (n = 5) and the problem group (n = 4) were small. The questions of interest were as follows: (i) whether individuals presenting inflammation (disease-positive or D+) can be distinguished from non-inflamed (disease-negative or D-) birds, (ii) whether two or more D+ stages can be detected and (iii) whether sample size influences detection. Within the problem group, the ratio-based method distinguished the following: (i) three (one D- and two D+) data classes; (ii) two (early and late) inflammatory stages; (iii) fast versus regular or slow responders; and (iv) individuals that recovered from those that remained inflamed. Because ratios differed in larger magnitudes (up to 48 times larger) than percentages, it is suggested that data patterns are likely to be recognized when disease surveillance methods are designed to measure inflammation and utilize ratios. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Systems Biology and Health Systems Complexity in;

NARCIS (Netherlands)

Donald Combs, C.; Barham, S.R.; Sloot, P.M.A.

2016-01-01

Systems biology addresses interactions in biological systems at different scales of biological organization, from the molecular to the cellular, organ, organism, societal, and ecosystem levels. This chapter expands on the concept of systems biology, explores its implications for individual patients

Aging in a Relativistic Biological Space-Time

Directory of Open Access Journals (Sweden)

Davide Maestrini

2018-05-01

Full Text Available Here we present a theoretical and mathematical perspective on the process of aging. We extend the concepts of physical space and time to an abstract, mathematically-defined space, which we associate with a concept of “biological space-time” in which biological dynamics may be represented. We hypothesize that biological dynamics, represented as trajectories in biological space-time, may be used to model and study different rates of biological aging. As a consequence of this hypothesis, we show how dilation or contraction of time analogous to relativistic corrections of physical time resulting from accelerated or decelerated biological dynamics may be used to study precipitous or protracted aging. We show specific examples of how these principles may be used to model different rates of aging, with an emphasis on cancer in aging. We discuss how this theory may be tested or falsified, as well as novel concepts and implications of this theory that may improve our interpretation of biological aging.

Systems Biology-an interdisciplinary approach.

Science.gov (United States)

Friboulet, Alain; Thomas, Daniel

2005-06-15

System-level approaches in biology are not new but foundations of "Systems Biology" are achieved only now at the beginning of the 21st century [Kitano, H., 2001. Foundations of Systems Biology. MIT Press, Cambridge, MA]. The renewed interest for a system-level approach is linked to the progress in collecting experimental data and to the limits of the "reductionist" approach. System-level understanding of native biological and pathological systems is needed to provide potential therapeutic targets. Examples of interdisciplinary approach in Systems Biology are described in U.S., Japan and Europe. Robustness in biology, metabolic engineering and idiotypic networks are discussed in the framework of Systems Biology.

Dynamics of Nonlinear Time-Delay Systems

CERN Document Server

Lakshmanan, Muthusamy

2010-01-01

Synchronization of chaotic systems, a patently nonlinear phenomenon, has emerged as a highly active interdisciplinary research topic at the interface of physics, biology, applied mathematics and engineering sciences. In this connection, time-delay systems described by delay differential equations have developed as particularly suitable tools for modeling specific dynamical systems. Indeed, time-delay is ubiquitous in many physical systems, for example due to finite switching speeds of amplifiers in electronic circuits, finite lengths of vehicles in traffic flows, finite signal propagation times in biological networks and circuits, and quite generally whenever memory effects are relevant. This monograph presents the basics of chaotic time-delay systems and their synchronization with an emphasis on the effects of time-delay feedback which give rise to new collective dynamics. Special attention is devoted to scalar chaotic/hyperchaotic time-delay systems, and some higher order models, occurring in different bran...

Biological mechanisms, one molecule at a time

Science.gov (United States)

Tinoco, Ignacio; Gonzalez, Ruben L.

2011-01-01

The last 15 years have witnessed the development of tools that allow the observation and manipulation of single molecules. The rapidly expanding application of these technologies for investigating biological systems of ever-increasing complexity is revolutionizing our ability to probe the mechanisms of biological reactions. Here, we compare the mechanistic information available from single-molecule experiments with the information typically obtained from ensemble studies and show how these two experimental approaches interface with each other. We next present a basic overview of the toolkit for observing and manipulating biology one molecule at a time. We close by presenting a case study demonstrating the impact that single-molecule approaches have had on our understanding of one of life's most fundamental biochemical reactions: the translation of a messenger RNA into its encoded protein by the ribosome. PMID:21685361

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

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Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-08-29

Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential

Imaging systems and algorithms to analyze biological samples in real-time using mobile phone microscopy.

Science.gov (United States)

Shanmugam, Akshaya; Usmani, Mohammad; Mayberry, Addison; Perkins, David L; Holcomb, Daniel E

2018-01-01

Miniaturized imaging devices have pushed the boundaries of point-of-care imaging, but existing mobile-phone-based imaging systems do not exploit the full potential of smart phones. This work demonstrates the use of simple imaging configurations to deliver superior image quality and the ability to handle a wide range of biological samples. Results presented in this work are from analysis of fluorescent beads under fluorescence imaging, as well as helminth eggs and freshwater mussel larvae under white light imaging. To demonstrate versatility of the systems, real time analysis and post-processing results of the sample count and sample size are presented in both still images and videos of flowing samples.

Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

Science.gov (United States)

De Domenico, Manlio

2018-03-01

Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

Biological conversion system

Science.gov (United States)

Scott, C.D.

A system for bioconversion of organic material comprises a primary bioreactor column wherein a biological active agent (zymomonas mobilis) converts the organic material (sugar) to a product (alcohol), a rejuvenator column wherein the biological activity of said biological active agent is enhanced, and means for circulating said biological active agent between said primary bioreactor column and said rejuvenator column.

Tunable promoters in synthetic and systems biology

DEFF Research Database (Denmark)

Dehli, Tore; Solem, Christian; Jensen, Peter Ruhdal

2012-01-01

in synthetic biology. A number of tools exist to manipulate the steps in between gene sequence and functional protein in living cells, but out of these the most straight-forward approach is to alter the gene expression level by manipulating the promoter sequence. Some of the promoter tuning tools available......Synthetic and systems biologists need standardized, modular and orthogonal tools yielding predictable functions in vivo. In systems biology such tools are needed to quantitatively analyze the behavior of biological systems while the efficient engineering of artificial gene networks is central...... for accomplishing such altered gene expression levels are discussed here along with examples of their use, and ideas for new tools are described. The road ahead looks very promising for synthetic and systems biologists as tools to achieve just about anything in terms of tuning and timing multiple gene expression...

Integrative radiation systems biology

International Nuclear Information System (INIS)

Unger, Kristian

2014-01-01

Maximisation of the ratio of normal tissue preservation and tumour cell reduction is the main concept of radiotherapy alone or combined with chemo-, immuno- or biologically targeted therapy. The foremost parameter influencing this ratio is radiation sensitivity and its modulation towards a more efficient killing of tumour cells and a better preservation of normal tissue at the same time is the overall aim of modern therapy schemas. Nevertheless, this requires a deep understanding of the molecular mechanisms of radiation sensitivity in order to identify its key players as potential therapeutic targets. Moreover, the success of conventional approaches that tried to statistically associate altered radiation sensitivity with any molecular phenotype such as gene expression proofed to be somewhat limited since the number of clinically used targets is rather sparse. However, currently a paradigm shift is taking place from pure frequentistic association analysis to the rather holistic systems biology approach that seeks to mathematically model the system to be investigated and to allow the prediction of an altered phenotype as the function of one single or a signature of biomarkers. Integrative systems biology also considers the data from different molecular levels such as the genome, transcriptome or proteome in order to partially or fully comprehend the causal chain of molecular mechanisms. An example for the application of this concept currently carried out at the Clinical Cooperation Group “Personalized Radiotherapy in Head and Neck Cancer” of the Helmholtz-Zentrum München and the LMU Munich is described. This review article strives for providing a compact overview on the state of the art of systems biology, its actual challenges, potential applications, chances and limitations in radiation oncology research working towards improved personalised therapy concepts using this relatively new methodology

Development trend of radiation biology research-systems radiation biology

International Nuclear Information System (INIS)

Min Rui

2010-01-01

Radiation biology research has past 80 years. We have known much more about fundamentals, processes and results of biology effects induced by radiation and various factors that influence biology effects wide and deep, however many old and new scientific problems occurring in the field of radiation biology research remain to be illustrated. To explore and figure these scientific problems need systemic concept, methods and multi dimension view on the base of considerations of complexity of biology system, diversity of biology response, temporal and spatial process of biological effects during occurrence, and complex feed back network of biological regulations. (authors)

Noninvasive biological sensor system for detection of drunk driving.

Science.gov (United States)

Murata, Kohji; Fujita, Etsunori; Kojima, Shigeyuki; Maeda, Shinitirou; Ogura, Yumi; Kamei, Tsutomu; Tsuji, Toshio; Kaneko, Shigehiko; Yoshizumi, Masao; Suzuki, Nobutaka

2011-01-01

Systems capable of monitoring the biological condition of a driver and issuing warnings during instances of drowsiness have recently been studied. Moreover, many researchers have reported that biological signals, such as brain waves, pulsation waves, and heart rate, are different between people who have and have not consumed alcohol. Currently, we are developing a noninvasive system to detect individuals driving under the influence of alcohol by measuring biological signals. We used the frequency time series analysis to attempt to distinguish between normal and intoxicated states of a person as the basis of the sensing system.

Concurrent systems and time synchronization

Science.gov (United States)

Burgin, Mark; Grathoff, Annette

2018-05-01

In the majority of scientific fields, system dynamics is described assuming existence of unique time for the whole system. However, it is established theoretically, for example, in relativity theory or in the system theory of time, and validated experimentally that there are different times and time scales in a variety of real systems - physical, chemical, biological, social, etc. In spite of this, there are no wide-ranging scientific approaches to exploration of such systems. Therefore, the goal of this paper is to study systems with this property. We call them concurrent systems because processes in them can go, events can happen and actions can be performed in different time scales. The problem of time synchronization is specifically explored.

Advancing metabolic engineering through systems biology of industrial microorganisms

DEFF Research Database (Denmark)

Dai, Zongjie; Nielsen, Jens

2015-01-01

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......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...... 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....

Fostering synergy between cell biology and systems biology.

Science.gov (United States)

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Advancing metabolic engineering through systems biology of industrial microorganisms.

Science.gov (United States)

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.

Bioremediation 3.0: Engineering pollutant-removing bacteria in the times of systemic biology

DEFF Research Database (Denmark)

Dvořák, Pavel; Nikel, Pablo Ivan; Damborskýc, Jiří

2017-01-01

pollutants with no external intervention, the onset of genetic engineering in the 1980s allowed the possibility of rational design of bacteria to catabolize specific compounds, which could eventually be released into the environment as bioremediation agents. The complexity of this endeavour and the lack...... of fundamental knowledge nonetheless led to the virtual abandonment of such a recombinant DNA-based bioremediation only a decade later. In a twist of events, the last few years have witnessed the emergence of new systemic fields (including systems and synthetic biology, and metabolic engineering) that allow....... In this article, we analyze how contemporary systemic biology is helping to take the design of bioremediation agents back to the core of environmental biotechnology. We inspect a number of recent strategies for catabolic pathway construction and optimization and we bring them together by proposing an engineering...

Automated Bayesian model development for frequency detection in biological time series

Directory of Open Access Journals (Sweden)

Oldroyd Giles ED

2011-06-01

Full Text Available Abstract Background A first step in building a mathematical model of a biological system is often the analysis of the temporal behaviour of key quantities. Mathematical relationships between the time and frequency domain, such as Fourier Transforms and wavelets, are commonly used to extract information about the underlying signal from a given time series. This one-to-one mapping from time points to frequencies inherently assumes that both domains contain the complete knowledge of the system. However, for truncated, noisy time series with background trends this unique mapping breaks down and the question reduces to an inference problem of identifying the most probable frequencies. Results In this paper we build on the method of Bayesian Spectrum Analysis and demonstrate its advantages over conventional methods by applying it to a number of test cases, including two types of biological time series. Firstly, oscillations of calcium in plant root cells in response to microbial symbionts are non-stationary and noisy, posing challenges to data analysis. Secondly, circadian rhythms in gene expression measured over only two cycles highlights the problem of time series with limited length. The results show that the Bayesian frequency detection approach can provide useful results in specific areas where Fourier analysis can be uninformative or misleading. We demonstrate further benefits of the Bayesian approach for time series analysis, such as direct comparison of different hypotheses, inherent estimation of noise levels and parameter precision, and a flexible framework for modelling the data without pre-processing. Conclusions Modelling in systems biology often builds on the study of time-dependent phenomena. Fourier Transforms are a convenient tool for analysing the frequency domain of time series. However, there are well-known limitations of this method, such as the introduction of spurious frequencies when handling short and noisy time series, and

Automated Bayesian model development for frequency detection in biological time series.

Science.gov (United States)

Granqvist, Emma; Oldroyd, Giles E D; Morris, Richard J

2011-06-24

A first step in building a mathematical model of a biological system is often the analysis of the temporal behaviour of key quantities. Mathematical relationships between the time and frequency domain, such as Fourier Transforms and wavelets, are commonly used to extract information about the underlying signal from a given time series. This one-to-one mapping from time points to frequencies inherently assumes that both domains contain the complete knowledge of the system. However, for truncated, noisy time series with background trends this unique mapping breaks down and the question reduces to an inference problem of identifying the most probable frequencies. In this paper we build on the method of Bayesian Spectrum Analysis and demonstrate its advantages over conventional methods by applying it to a number of test cases, including two types of biological time series. Firstly, oscillations of calcium in plant root cells in response to microbial symbionts are non-stationary and noisy, posing challenges to data analysis. Secondly, circadian rhythms in gene expression measured over only two cycles highlights the problem of time series with limited length. The results show that the Bayesian frequency detection approach can provide useful results in specific areas where Fourier analysis can be uninformative or misleading. We demonstrate further benefits of the Bayesian approach for time series analysis, such as direct comparison of different hypotheses, inherent estimation of noise levels and parameter precision, and a flexible framework for modelling the data without pre-processing. Modelling in systems biology often builds on the study of time-dependent phenomena. Fourier Transforms are a convenient tool for analysing the frequency domain of time series. However, there are well-known limitations of this method, such as the introduction of spurious frequencies when handling short and noisy time series, and the requirement for uniformly sampled data. Biological time

Iterative Systems Biology for Medicine – time for advancing from network signature to mechanistic equations

KAUST Repository

Gomez-Cabrero, David; Tegner, Jesper

2017-01-01

The rise and growth of Systems Biology following the sequencing of the human genome has been astounding. Early on, an iterative wet-dry methodology was formulated which turned out as a successful approach in deciphering biological complexity

Memorized discrete systems and time-delay

CERN Document Server

Luo, Albert C J

2017-01-01

This book examines discrete dynamical systems with memory—nonlinear systems that exist extensively in biological organisms and financial and economic organizations, and time-delay systems that can be discretized into the memorized, discrete dynamical systems. It book further discusses stability and bifurcations of time-delay dynamical systems that can be investigated through memorized dynamical systems as well as bifurcations of memorized nonlinear dynamical systems, discretization methods of time-delay systems, and periodic motions to chaos in nonlinear time-delay systems. The book helps readers find analytical solutions of MDS, change traditional perturbation analysis in time-delay systems, detect motion complexity and singularity in MDS; and determine stability, bifurcation, and chaos in any time-delay system.

Micro-separation toward systems biology.

Science.gov (United States)

Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

2006-02-17

Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

Nutritional Systems Biology

DEFF Research Database (Denmark)

Jensen, Kasper

and network biology has the potential to increase our understanding of how small molecules affect metabolic pathways and homeostasis, how this perturbation changes at the disease state, and to what extent individual genotypes contribute to this. A fruitful strategy in approaching and exploring the field...... biology research. The paper also shows as a proof-of-concept that a systems biology approach to diet is meaningful and demonstrates some basic principles on how to work with diet systematic. The second chapter of this thesis we developed the resource NutriChem v1.0. A foodchemical database linking...... sites of diet on the disease pathway. We propose a framework for interrogating the critical targets in colon cancer process and identifying plant-based dietary interventions as important modifiers using a systems chemical biology approach. The fifth chapter of the thesis is on discovering of novel anti...

Informing biological design by integration of systems and synthetic biology.

Science.gov (United States)

Smolke, Christina D; Silver, Pamela A

2011-03-18

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. Copyright © 2011 Elsevier Inc. All rights reserved.

Real-Time Tracking the Synthesis and Degradation of Albumin in Complex Biological Systems with a near-Infrared Fluorescent Probe.

Science.gov (United States)

Jin, Qiang; Feng, Lei; Zhang, Shui-Jun; Wang, Dan-Dan; Wang, Fang-Jun; Zhang, Yi; Cui, Jing-Nan; Guo, Wen-Zhi; Ge, Guang-Bo; Yang, Ling

2017-09-19

In this study, a novel fluorescent detection system for biological sensing of human albumin (HA) was developed on the basis of the pseudoesterase activity and substrate preference of HA. The designed near-infrared (NIR) fluorescent probe (DDAP) could be effectively hydrolyzed by HA, accompanied by significant changes in both color and fluorescence spectrum. The sensing mechanism was fully investigated by fluorescence spectroscopy, NMR, and mass spectra. DDAP exhibited excellent selectivity and sensitivity toward HA over a variety of human plasma proteins, hydrolases, and abundant biomolecules found in human body. The probe has been successfully applied to measure native HA in diluted plasma samples and the secreted HA in the hepatocyte culture supernatant. DDAP has also been used for fluorescence imaging of HA reabsorption in living renal cells, and the results show that the probe exhibits good cell permeability, low cytotoxicity and high imaging resolution. Furthermore, DDAP has been successfully used for real-time tracking the uptaking and degradation of albumin in ex vivo mouse kidney models for the first time. All these results clearly demonstrated that DDAP-based assay held great promise for real-time sensing and tracking HA in complex biological systems, which would be very useful for basic researches and clinical diagnosis of HA-associated diseases.

Excited states in biological systems

International Nuclear Information System (INIS)

Cilento, G.; Zinner, K.; Bechara, E.J.H.; Duran, N.; Baptista, R.C. de; Shimizu, Y.; Augusto, O.; Faljoni-Alario, A.; Vidigal, C.C.C.; Oliveira, O.M.M.F.; Haun, M.

1979-01-01

Some aspects of bioluminescence related to bioenergetics are discussed: 1. chemical generation of excited species, by means of two general processes: electron transference and cyclic - and linear peroxide cleavage; 2. biological systems capable of generating excited states and 3. biological functions of these states, specially the non-emissive ones (tripletes). The production and the role of non-emissive excited states in biological systems are analysed, the main purpose of the study being the search for non-emissive states. Experiences carried out in biological systems are described; results and conclusions are given. (M.A.) [pt

Interactive analysis of systems biology molecular expression data

Directory of Open Access Journals (Sweden)

Prabhakar Sunil

2008-02-01

Full Text Available Abstract Background Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations. Results Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data. Conclusion The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe in growth media (an ionomics dataset. This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology.

Systems Biology of the Fluxome

Directory of Open Access Journals (Sweden)

Miguel A. Aon

2015-07-01

Full Text Available The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms.

Multisensor Instrument for Real-Time Biological Monitoring

Science.gov (United States)

Zhang, Sean (Zhanxiang); Xu, Guoda; Qiu, Wei; Lin, Freddie

2004-01-01

The figure schematically depicts an instrumentation system, called a fiber optic-based integration system (FOBIS), that is undergoing development to enable real-time monitoring of fluid cell cultures, bioprocess flows, and the like. The FOBIS design combines a micro flow cytometer (MFC), a microphotometer (MP), and a fluorescence-spectrum- or binding-force-measuring micro-sensor (MS) in a single instrument that is capable of measuring multiple biological parameters simultaneously or sequentially. The fiber-optic-based integration system is so named because the MFC, the MP, and the MS are integrated into a single optical system that is coupled to light sources and photometric equipment via optical fibers. The optical coupling components also include a wavelength-division multiplexer and diffractive optical elements. The FOBIS includes a laserdiode- and fiber-optic-based optical trapping subsystem (optical tweezers ) with microphotometric and micro-sensing capabilities for noninvasive confinement and optical measurement of relevant parameters of a single cell or other particle. Some of the measurement techniques implemented together by the FOBIS have long been used separately to obtain basic understanding of the optical properties of individual cells and other organisms, the optical properties of populations of organisms, and the interrelationships among these properties, physiology of the organisms, and physical processes that govern the media that surround the organisms. For example, flow cytometry yields information on numerical concentrations, cross-sectional areas, and types of cells or other particles. Micro-sensing can be used to measure pH and concentrations of oxygen, carbon dioxide, glucose, metabolites, calcium, and antigens in a cell-culture fluid, thereby providing feedback that can be helpful in improving control over a bioprocess. Microphotometry (including measurements of scattering and fluorescence) can yield further information about optically

31P spin-lattice relaxation time measurements in biological systems

International Nuclear Information System (INIS)

Suzuki, Eiji; Maeda, Munehiro; Kuki, Satoru; Tsukamoto, Kenji; Kawakami, Tsuyoshi; Seo, Yoshiteru; Murakami, Masataka; Watari, Hiroshi

1989-01-01

Spin-lattice relaxation time (T 1 ) of phosphorus compounds in the perfused heart, liver, kidney and erythrocytes of rats were measured by the DESPOT (Driven-equilibrium single-pulse observation of T 1 ) method at 8.45 T. This method is a rapid and accurate technique for the measurement of T 1 values. T 1 values of phosphomonoesters (PME), 2, 3-diphosphoglycerate (DPG), inorganic phosphate (Pi), phosphodiesters (PDE), phosphocreatine (PCr) and three phosphates of ATP were ranged from 0.15±0.02 sec (β-ATP in the liver) to 8.5±1.6 sec (PDE in the kidney). T 1 value of β-ATP in the liver was 1/4-1/5 of those in the mandibular gland, heart, erythrocytes and kidney. T 1 values obtained from biological materials are useful for selecting the optimal pulse repetition times and pulse angles to maximize the signal-to-noise ratio of 13 P spectra, and for correcting distortions of signal intensities in the spectra. (author)

Logical analysis of biological systems

DEFF Research Database (Denmark)

Mardare, Radu Iulian

2005-01-01

R. Mardare, Logical analysis of biological systems. Fundamenta Informaticae, N 64:271-285, 2005.......R. Mardare, Logical analysis of biological systems. Fundamenta Informaticae, N 64:271-285, 2005....

Predictive modelling of complex agronomic and biological systems.

Science.gov (United States)

Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J

2013-09-01

Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.

Institute for Genomics and Systems Biology

Science.gov (United States)

Institute for Genomics and Systems Biology Discover. Predict. Improve. Advancing Human and , 2015 See all Research Papers Featured Video Introduction to Systems Biology Video: Introduction to Systems Biology News Jack Gilbert Heading UChicago Startup that Aims to Predict Behavior of Trillions of

Biophysics and systems biology.

Science.gov (United States)

Noble, Denis

2010-03-13

Biophysics at the systems level, as distinct from molecular biophysics, acquired its most famous paradigm in the work of Hodgkin and Huxley, who integrated their equations for the nerve impulse in 1952. Their approach has since been extended to other organs of the body, notably including the heart. The modern field of computational biology has expanded rapidly during the first decade of the twenty-first century and, through its contribution to what is now called systems biology, it is set to revise many of the fundamental principles of biology, including the relations between genotypes and phenotypes. Evolutionary theory, in particular, will require re-assessment. To succeed in this, computational and systems biology will need to develop the theoretical framework required to deal with multilevel interactions. While computational power is necessary, and is forthcoming, it is not sufficient. We will also require mathematical insight, perhaps of a nature we have not yet identified. This article is therefore also a challenge to mathematicians to develop such insights.

Optical Time-of-Flight and Absorbance Imaging of Biologic Media

Science.gov (United States)

Benaron, David A.; Stevenson, David K.

1993-03-01

Imaging the interior of living bodies with light may assist in the diagnosis and treatment of a number of clinical problems, which include the early detection of tumors and hypoxic cerebral injury. An existing picosecond time-of-flight and absorbance (TOFA) optical system has been used to image a model biologic system and a rat. Model measurements confirmed TOFA principles in systems with a high degree of photon scattering; rat images, which were constructed from the variable time delays experienced by a fixed fraction of early-arriving transmitted photons, revealed identifiable internal structure. A combination of light-based quantitative measurement and TOFA localization may have applications in continuous, noninvasive monitoring for structural imaging and spatial chemometric analysis in humans.

Systems biology in critical-care nursing.

Science.gov (United States)

Schallom, Lynn; Thimmesch, Amanda R; Pierce, Janet D

2011-01-01

Systems biology applies advances in technology and new fields of study including genomics, transcriptomics, proteomics, and metabolomics to the development of new treatments and approaches of care for the critically ill and injured patient. An understanding of systems biology enhances a nurse's ability to implement evidence-based practice and to educate patients and families on novel testing and therapies. Systems biology is an integrated and holistic view of humans in relationship with the environment. Biomarkers are used to measure the presence and severity of disease and are rapidly expanding in systems biology endeavors. A systems biology approach using predictive, preventive, and participatory involvement is being utilized in a plethora of conditions of critical illness and injury including sepsis, cancer, pulmonary disease, and traumatic injuries.

Compartmental study of biological systems

International Nuclear Information System (INIS)

Moretti, J.L.

1975-01-01

The compartmental analysis of biological system is dealt with on several chapters devoted successively to: terminology; a mathematical and symbolic account of a system at equilibrium; different compartment systems; analysis of the experimental results. For this it is pointed out that the application of compartmental systems to biological phenomena is not always without danger. Sometimes the compartmental system established in a reference subject fails to conform in the patient. The compartments can divide into two or join together, completely changing the aspect of the system so that parameters calculated with the old model become entirely false. The conclusion is that the setting up of a compartmental system to represent a biological phenomenon is a tricky undertaking and the results must be constantly criticized and questioned [fr

Philosophy of Systems and Synthetic Biology

DEFF Research Database (Denmark)

Green, Sara

2017-01-01

This entry aims to clarify how systems and synthetic biology contribute to and extend discussions within philosophy of science. Unlike fields such as developmental biology or molecular biology, systems and synthetic biology are not easily demarcated by a focus on a specific subject area or level...... of organization. Rather, they are characterized by the development and application of mathematical, computational, and synthetic modeling strategies in response to complex problems and challenges within the life sciences. Proponents of systems and synthetic biology often stress the necessity of a perspective...... that goes beyond the scope of molecular biology and genetic engineering, respectively. With the emphasis on systems and interaction networks, the approaches explicitly engage in one of the oldest philosophical discussions on the relationship between parts and wholes, or between reductionism and holism...

Biocellion: accelerating computer simulation of multicellular biological system models.

Science.gov (United States)

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.

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

Science.gov (United States)

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

Indian Academy of Sciences (India)

IAS Admin

study and understand the function of biological systems, particu- larly, the response of such .... understand the organisation and behaviour of prokaryotic sys- tems. ... relationship of the structure of a target molecule to its ability to bind a certain ...

Integrating systems biology models and biomedical ontologies.

Science.gov (United States)

Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

2011-08-11

Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

Calculating life? Duelling discourses in interdisciplinary systems biology.

Science.gov (United States)

Calvert, Jane; Fujimura, Joan H

2011-06-01

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable-a research programme that is perhaps taken to its most extreme form in systems biology's sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to 'dirty, unruly living systems'. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences. Copyright © 2010 Elsevier Ltd. All rights reserved.

Magnetic Nanotweezers for Interrogating Biological Processes in Space and Time.

Science.gov (United States)

Kim, Ji-Wook; Jeong, Hee-Kyung; Southard, Kaden M; Jun, Young-Wook; Cheon, Jinwoo

2018-04-17

The ability to sense and manipulate the state of biological systems has been extensively advanced during the past decade with the help of recent developments in physical tools. Unlike standard genetic and pharmacological perturbation techniques-knockdown, overexpression, small molecule inhibition-that provide a basic on/off switching capability, these physical tools provide the capacity to control the spatial, temporal, and mechanical properties of the biological targets. Among the various physical cues, magnetism offers distinct advantages over light or electricity. Magnetic fields freely penetrate biological tissues and are already used for clinical applications. As one of the unique features, magnetic fields can be transformed into mechanical stimuli which can serve as a cue in regulating biological processes. However, their biological applications have been limited due to a lack of high-performance magnetism-to-mechanical force transducers with advanced spatiotemporal capabilities. In this Account, we present recent developments in magnetic nanotweezers (MNTs) as a useful tool for interrogating the spatiotemporal control of cells in living tissue. MNTs are composed of force-generating magnetic nanoparticles and field generators. Through proper design and the integration of individual components, MNTs deliver controlled mechanical stimulation to targeted biomolecules at any desired space and time. We first discuss about MNT configuration with different force-stimulation modes. By modulating geometry of the magnetic field generator, MNTs exert pulling, dipole-dipole attraction, and rotational forces to the target specifically and quantitatively. We discuss the key physical parameters determining force magnitude, which include magnetic field strength, magnetic field gradient, magnetic moment of the magnetic particle, as well as distance between the field generator and the particle. MNTs also can be used over a wide range of biological time scales. By simply

Heuristic Strategies in Systems Biology

Directory of Open Access Journals (Sweden)

Fridolin Gross

2016-06-01

Full Text Available Systems biology is sometimes presented as providing a superior approach to the problem of biological complexity. Its use of ‘unbiased’ methods and formal quantitative tools might lead to the impression that the human factor is effectively eliminated. However, a closer look reveals that this impression is misguided. Systems biologists cannot simply assemble molecular information and compute biological behavior. Instead, systems biology’s main contribution is to accelerate the discovery of mechanisms by applying models as heuristic tools. These models rely on a variety of idealizing and simplifying assumptions in order to be efficient for this purpose. The strategies of systems biologists are similar to those of experimentalists in that they attempt to reduce the complexity of the discovery process. Analyzing and comparing these strategies, or ‘heuristics’, reveals the importance of the human factor in computational approaches and helps to situate systems biology within the epistemic landscape of the life sciences.

EPR spectroscopy of complex biological iron-sulfur systems.

Science.gov (United States)

Hagen, Wilfred R

2018-02-21

From the very first discovery of biological iron-sulfur clusters with EPR, the spectroscopy has been used to study not only purified proteins but also complex systems such as respiratory complexes, membrane particles and, later, whole cells. In recent times, the emphasis of iron-sulfur biochemistry has moved from characterization of individual proteins to the systems biology of iron-sulfur biosynthesis, regulation, degradation, and implications for human health. Although this move would suggest a blossoming of System-EPR as a specific, non-invasive monitor of Fe/S (dys)homeostasis in whole cells, a review of the literature reveals limited success possibly due to technical difficulties in adherence to EPR spectroscopic and biochemical standards. In an attempt to boost application of System-EPR the required boundary conditions and their practical applications are explicitly and comprehensively formulated.

Time-ordered product expansions for computational stochastic system biology

International Nuclear Information System (INIS)

Mjolsness, Eric

2013-01-01

The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie’s stochastic simulation algorithm (SSA) for chemical reaction networks; consequently, the SSA can be interpreted in terms of Feynman diagrams. It is also used here to derive other, more general simulation and parameter-learning algorithms including simulation algorithms for networks of stochastic reaction-like processes operating on parameterized objects, and also hybrid stochastic reaction/differential equation models in which systems of ordinary differential equations evolve the parameters of objects that can also undergo stochastic reactions. Thus, the time-ordered product expansion can be used systematically to derive simulation and parameter-fitting algorithms for stochastic systems. (paper)

Mammalian Synthetic Biology: Engineering Biological Systems.

Science.gov (United States)

Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A

2017-06-21

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

Applicability of Computational Systems Biology in Toxicology

DEFF Research Database (Denmark)

Kongsbak, Kristine Grønning; Hadrup, Niels; Audouze, Karine Marie Laure

2014-01-01

be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method......Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources...... and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search...

Ins and outs of systems biology vis-à-vis molecular biology: continuation or clear cut?

Science.gov (United States)

De Backer, Philippe; De Waele, Danny; Van Speybroeck, Linda

2010-03-01

The comprehension of living organisms in all their complexity poses a major challenge to the biological sciences. Recently, systems biology has been proposed as a new candidate in the development of such a comprehension. The main objective of this paper is to address what systems biology is and how it is practised. To this end, the basic tools of a systems biological approach are explored and illustrated. In addition, it is questioned whether systems biology 'revolutionizes' molecular biology and 'transcends' its assumed reductionism. The strength of this claim appears to depend on how molecular and systems biology are characterised and on how reductionism is interpreted. Doing credit to molecular biology and to methodological reductionism, it is argued that the distinction between molecular and systems biology is gradual rather than sharp. As such, the classical challenge in biology to manage, interpret and integrate biological data into functional wholes is further intensified by systems biology's use of modelling and bioinformatics, and by its scale enlargement.

Editorial overview : Systems biology for biotechnology

NARCIS (Netherlands)

Heinemann, Matthias; Pilpel, Yitzhak

About 15 years ago, systems biology was introduced as a novel approach to biological research. On the one side, its introduction was a result of the recognition that through solely the reductionist approach, we would ulti- mately not be able to understand how biological systems function as a whole.

Static Analysis for Systems Biology

DEFF Research Database (Denmark)

Nielson, Flemming; Nielson, Hanne Riis; Rosa, D. Schuch da

2004-01-01

This paper shows how static analysis techniques can help understanding biological systems. Based on a simple example we illustrate the outcome of performing three different analyses extracting information of increasing precision. We conclude by reporting on the potential impact and exploitation o...... of these techniques in systems biology....

Omics/systems biology and cancer cachexia.

Science.gov (United States)

Gallagher, Iain J; Jacobi, Carsten; Tardif, Nicolas; Rooyackers, Olav; Fearon, Kenneth

2016-06-01

Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia. Copyright © 2016. Published by Elsevier Ltd.

Inverse Problems in Systems Biology: A Critical Review.

Science.gov (United States)

Guzzi, Rodolfo; Colombo, Teresa; Paci, Paola

2018-01-01

Systems Biology may be assimilated to a symbiotic cyclic interplaying between the forward and inverse problems. Computational models need to be continuously refined through experiments and in turn they help us to make limited experimental resources more efficient. Every time one does an experiment we know that there will be some noise that can disrupt our measurements. Despite the noise certainly is a problem, the inverse problems already involve the inference of missing information, even if the data is entirely reliable. So the addition of a certain limited noise does not fundamentally change the situation but can be used to solve the so-called ill-posed problem, as defined by Hadamard. It can be seen as an extra source of information. Recent studies have shown that complex systems, among others the systems biology, are poorly constrained and ill-conditioned because it is difficult to use experimental data to fully estimate their parameters. For these reasons was born the concept of sloppy models, a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. Furthermore the concept of sloppy models contains also the concept of un-identifiability, because the models are characterized by many parameters that are poorly constrained by experimental data. Then a strategy needs to be designed to infer, analyze, and understand biological systems. The aim of this work is to provide a critical review to the inverse problems in systems biology defining a strategy to determine the minimal set of information needed to overcome the problems arising from dynamic biological models that generally may have many unknown, non-measurable parameters.

Analyzing the Biology on the System Level

OpenAIRE

Tong, Wei

2016-01-01

Although various genome projects have provided us enormous static sequence information, understanding of the sophisticated biology continues to require integrating the computational modeling, system analysis, technology development for experiments, and quantitative experiments all together to analyze the biology architecture on various levels, which is just the origin of systems biology subject. This review discusses the object, its characteristics, and research attentions in systems biology,...

Mean Transit Time and Mean Residence Time for Linear Diffusion–Convection–Reaction Transport System

Directory of Open Access Journals (Sweden)

Jacek Waniewski

2007-01-01

Full Text Available Characteristic times for transport processes in biological systems may be evaluated as mean transit times (MTTs (for transit states or mean residence times (MRT (for steady states. It is shown in a general framework of a (linear reaction–diffusion–convection equation that these two times are related. Analytical formulas are also derived to calculate moments of exit time distribution using solutions for a stationary state of the system.

Time in physics and biology

Directory of Open Access Journals (Sweden)

BRUNO GÜNTHER

2004-01-01

Full Text Available In contrast with classical physics, particularly with Sir Isaac Newton, where time is a continuous function, generally valid, eternally and evenly flowing as an absolute time dimension, in the biological sciences, time is in essence of cyclical nature (physiological periodicities, where future passes to past through an infinitely thin boundary, the present. In addition, the duration of the present (DP leads to the so-called 'granulation of time' in living beings, so that by the fusion of two successive pictures of the world, which are not entirely similar, they attain the perception of 'movement,' both in the real world as well as in the sham-movement in the mass media (TV.

Biological timing and the clock metaphor: oscillatory and hourglass mechanisms.

Science.gov (United States)

Rensing, L; Meyer-Grahle, U; Ruoff, P

2001-05-01

Living organisms have developed a multitude of timing mechanisms--"biological clocks." Their mechanisms are based on either oscillations (oscillatory clocks) or unidirectional processes (hourglass clocks). Oscillatory clocks comprise circatidal, circalunidian, circadian, circalunar, and circannual oscillations--which keep time with environmental periodicities--as well as ultradian oscillations, ovarian cycles, and oscillations in development and in the brain, which keep time with biological timescales. These clocks mainly determine time points at specific phases of their oscillations. Hourglass clocks are predominantly found in development and aging and also in the brain. They determine time intervals (duration). More complex timing systems combine oscillatory and hourglass mechanisms, such as the case for cell cycle, sleep initiation, or brain clocks, whereas others combine external and internal periodicities (photoperiodism, seasonal reproduction). A definition of a biological clock may be derived from its control of functions external to its own processes and its use in determining temporal order (sequences of events) or durations. Biological and chemical oscillators are characterized by positive and negative feedback (or feedforward) mechanisms. During evolution, living organisms made use of the many existing oscillations for signal transmission, movement, and pump mechanisms, as well as for clocks. Some clocks, such as the circadian clock, that time with environmental periodicities are usually compensated (stabilized) against temperature, whereas other clocks, such as the cell cycle, that keep time with an organismic timescale are not compensated. This difference may be related to the predominance of negative feedback in the first class of clocks and a predominance of positive feedback (autocatalytic amplification) in the second class. The present knowledge of a compensated clock (the circadian oscillator) and an uncompensated clock (the cell cycle), as well

Adapting to Biology: Maintaining Container-Closure System Compatibility with the Therapeutic Biologic Revolution.

Science.gov (United States)

Degrazio, Dominick

Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to the dimension of evolving therapeutic biologics. Important concerns associated with this changeover are becoming forefront, as challenges develop of varying complexity uncommon with the synthesis and production of traditional drugs. Therefore, alternative measures must be established that aim to preserve the efficacy and functionality of a biologic that might not be implemented for small molecules. Conserving protein stability is relative to perpetuating a net equilibrium of both intrinsic and extrinsic factors. Key to sustaining this balance is the ability of container-closure systems to maintain their compatibility with the ever-changing dynamics of therapeutic biologics. Failure to recognize and adjust the material properties of packaging components to support compatibility with therapeutic biologics can compromise patient safety, drug productivity, and biological stability. This review will examine the differences between small-molecule drugs and therapeutic biologics, lay a basic foundation for understanding the stability of therapeutic biologics, and demonstrate potential sources of container-closure systems' incompatibilities with therapeutic biologics at a mechanistic level. Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to recombinantly derived therapeutic biologics. Concerns associated with this transformation are becoming prominent, as therapeutic biologics are uncharacteristic to small-molecule drugs. Maintaining the stability of a therapeutic biologic is a combination of balancing intrinsic factors and external elements within the biologic's microenvironment. An important aspect of this balance is relegated to the overall compatibility of primary, parenteral container-closure systems with therapeutic biologics

A timeless biology.

Science.gov (United States)

Tozzi, Arturo; Peters, James F; Chafin, Clifford; De Falco, Domenico; Torday, John S

2018-05-01

Contrary to claims that physics is timeless while biology is time-dependent, we take the opposite standpoint: physical systems' dynamics are constrained by the arrow of time, while living assemblies are time-independent. Indeed, the concepts of "constraints" and "displacements" shed new light on the role of continuous time flow in life evolution, allowing us to sketch a physical gauge theory for biological systems in long timescales. In the very short timescales of biological systems' individual lives, time looks like "frozen" and "fixed", so that the second law of thermodynamics is momentarily wrecked. The global symmetries (standing for biological constrained trajectories, i.e. the energetic gradient flows dictated by the second law of thermodynamics in long timescales) are broken by local "displacements" where time is held constant, i.e., modifications occurring in living systems. Such displacements stand for brief local forces, able to temporarily "break" the cosmic increase in entropy. The force able to restore the symmetries (called "gauge field") stands for the very long timescales of biological evolution. Therefore, at the very low speeds of life evolution, time is no longer one of the four phase space coordinates of a spacetime Universe: it becomes just a gauge field superimposed to three-dimensional biological systems. We discuss the implications in biology: when assessing living beings, the underrated role of isolated "spatial" modifications needs to be emphasized, living apart the evolutionary role of time. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.

Science.gov (United States)

Nguyen, Tramy; Roehner, Nicholas; Zundel, Zach; Myers, Chris J

2016-06-17

Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.

Two faces of entropy and information in biological systems.

Science.gov (United States)

Mitrokhin, Yuriy

2014-10-21

The article attempts to overcome the well-known paradox of contradictions between the emerging biological organization and entropy production in biological systems. It is assumed that quality, speculative correlation between entropy and antientropy processes taking place both in the past and today in the metabolic and genetic cellular systems may be perfectly authorized for adequate description of the evolution of biological organization. So far as thermodynamic entropy itself cannot compensate for the high degree of organization which exists in the cell, we discuss the mode of conjunction of positive entropy events (mutations) in the genetic systems of the past generations and the formation of organized structures of current cells. We argue that only the information which is generated in the conditions of the information entropy production (mutations and other genome reorganization) in genetic systems of the past generations provides the physical conjunction of entropy and antientropy processes separated from each other in time generations. It is readily apparent from the requirements of the Second law of thermodynamics. Copyright © 2014 Elsevier Ltd. All rights reserved.

Magnetic Actuation of Biological Systems

Science.gov (United States)

Lauback, Stephanie D.

Central to the advancement of many biomedical and nanotechnology capabilities is the capacity to precisely control the motion of micro and nanostructures. These applications range from single molecule experiments to cell isolation and separation, to drug delivery and nanomachine manipulation. This dissertation focuses on actuation of biological micro- and nano-entities through the use of weak external magnetic fields, superparamagnetic beads, and ferromagnetic thin films. The magnetic platform presents an excellent method for actuation of biological systems due to its ability to directly control the motion of an array of micro and nanostructures in real-time with calibrated picoNewton forces. The energy landscape of two ferromagnetic thin film patterns (disks and zigzag wires) is experimentally explored and compared to corresponding theoretical models to quantify the applied forces and trajectories of superparamagnetic beads due to the magnetic traps. A magnetic method to directly actuate DNA nanomachines in real-time with nanometer resolution and sub-second response times using micromagnetic control was implemented through the use of stiff DNA micro-levers which bridged the large length scale mismatch between the micro-actuator and the nanomachine. Compared to current alternative methods which are limited in the actuation speeds and the number of reconfiguration states of DNA constructs, this magnetic approach enables fast actuation (˜ milliseconds) and reconfigurable conformations achieved through a continuous range of finely tuned steps. The system was initially tested through actuation of the stiff arm tethered to the surface, and two prototype DNA nanomachines (rotor and hinge) were successfully actuated using the stiff mechanical lever. These results open new possibilities in the development of functional robotic systems at the molecular scale. In exploiting the use of DNA stiff levers, a new technique was also developed to investigate the emergence of the

Ten questions about systems biology

DEFF Research Database (Denmark)

Joyner, Michael J; Pedersen, Bente K

2011-01-01

to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as 'systems biology' by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many......In this paper we raise 'ten questions' broadly related to 'omics', the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist...

Ten questions about systems biology

DEFF Research Database (Denmark)

Joyner, Michael J; Pedersen, Bente K

2011-01-01

In this paper we raise 'ten questions' broadly related to 'omics', the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist...... to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as 'systems biology' by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many...

Genomes, Phylogeny, and Evolutionary Systems Biology

Energy Technology Data Exchange (ETDEWEB)

Medina, Monica

2005-03-25

With the completion of the human genome and the growing number of diverse genomes being sequenced, a new age of evolutionary research is currently taking shape. The myriad of technological breakthroughs in biology that are leading to the unification of broad scientific fields such as molecular biology, biochemistry, physics, mathematics and computer science are now known as systems biology. Here I present an overview, with an emphasis on eukaryotes, of how the postgenomics era is adopting comparative approaches that go beyond comparisons among model organisms to shape the nascent field of evolutionary systems biology.

Aspergilli: Systems biology and industrial applications

DEFF Research Database (Denmark)

Knuf, Christoph; Nielsen, Jens

2012-01-01

possible to implement systems biology tools to advance metabolic engineering. These tools include genome-wide transcription analysis and genome-scale metabolic models. Herein, we review achievements in the field and highlight the impact of Aspergillus systems biology on industrial biotechnology....

Biomimicry, Biofabrication, and Biohybrid Systems: The Emergence and Evolution of Biological Design.

Science.gov (United States)

Raman, Ritu; Bashir, Rashid

2017-10-01

The discipline of biological design has a relatively short history, but has undergone very rapid expansion and development over that time. This Progress Report outlines the evolution of this field from biomimicry to biofabrication to biohybrid systems' design, showcasing how each subfield incorporates bioinspired dynamic adaptation into engineered systems. Ethical implications of biological design are discussed, with an emphasis on establishing responsible practices for engineering non-natural or hypernatural functional behaviors in biohybrid systems. This report concludes with recommendations for implementing biological design into educational curricula, ensuring effective and responsible practices for the next generation of engineers and scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model checking biological systems described using ambient calculus

DEFF Research Database (Denmark)

Mardare, Radu Iulian; Priami, Corrado; Qualia, Paola

2005-01-01

Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005.......Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005....

Systems Biology, Systems Medicine, Systems Pharmacology: The What and The Why.

Science.gov (United States)

Stéphanou, Angélique; Fanchon, Eric; Innominato, Pasquale F; Ballesta, Annabelle

2018-05-09

Systems biology is today such a widespread discipline that it becomes difficult to propose a clear definition of what it really is. For some, it remains restricted to the genomic field. For many, it designates the integrated approach or the corpus of computational methods employed to handle the vast amount of biological or medical data and investigate the complexity of the living. Although defining systems biology might be difficult, on the other hand its purpose is clear: systems biology, with its emerging subfields systems medicine and systems pharmacology, clearly aims at making sense of complex observations/experimental and clinical datasets to improve our understanding of diseases and their treatments without putting aside the context in which they appear and develop. In this short review, we aim to specifically focus on these new subfields with the new theoretical tools and approaches that were developed in the context of cancer. Systems pharmacology and medicine now give hope for major improvements in cancer therapy, making personalized medicine closer to reality. As we will see, the current challenge is to be able to improve the clinical practice according to the paradigm shift of systems sciences.

Complexity, Analysis and Control of Singular Biological Systems

CERN Document Server

Zhang, Qingling; Zhang, Xue

2012-01-01

Complexity, Analysis and Control of Singular Biological Systems follows the control of real-world biological systems at both ecological and phyisological levels concentrating on the application of now-extensively-investigated singular system theory. Much effort has recently been dedicated to the modelling and analysis of developing bioeconomic systems and the text establishes singular examples of these, showing how proper control can help to maintain sustainable economic development of biological resources. The book begins from the essentials of singular systems theory and bifurcations before tackling  the use of various forms of control in singular biological systems using examples including predator-prey relationships and viral vaccination and quarantine control. Researchers and graduate students studying the control of complex biological systems are shown how a variety of methods can be brought to bear and practitioners working with the economics of biological systems and their control will also find the ...

Systems biology of fungal infection

Directory of Open Access Journals (Sweden)

Fabian eHorn

2012-04-01

Full Text Available Elucidation of pathogenicity mechanisms of the most important human pathogenic fungi, Aspergillus fumigatus and Candida albicans, has gained great interest in the light of the steadily increasing number of cases of invasive fungal infections.A key feature of these infections is the interaction of the different fungal morphotypes with epithelial and immune effector cells in the human host. Because of the high level of complexity, it is necessary to describe and understand invasive fungal infection by taking a systems biological approach, i.e., by a comprehensive quantitative analysis of the non-linear and selective interactions of a large number of functionally diverse, and frequently multifunctional, sets of elements, e.g., genes, proteins, metabolites, which produce coherent and emergent behaviours in time and space. The recent advances in systems biology will now make it possible to uncover the structure and dynamics of molecular and cellular cause-effect relationships within these pathogenic interactions.We review current efforts to integrate omics and image-based data of host-pathogen interactions into network and spatio-temporal models. The modelling will help to elucidate pathogenicity mechanisms and to identify diagnostic biomarkers and potential drug targets for therapy and could thus pave the way for novel intervention strategies based on novel antifungal drugs and cell therapy.

Biological Systems Thinking for Control Engineering Design

Directory of Open Access Journals (Sweden)

D. J. Murray-Smith

2004-01-01

Full Text Available Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control. 

Network Analyses in Systems Biology: New Strategies for Dealing with Biological Complexity

DEFF Research Database (Denmark)

Green, Sara; Serban, Maria; Scholl, Raphael

2018-01-01

of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological...... strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from the investigation of organizational properties...

A system for success: BMC Systems Biology, a new open access journal.

Science.gov (United States)

Hodgkinson, Matt J; Webb, Penelope A

2007-09-04

BMC Systems Biology is the first open access journal spanning the growing field of systems biology from molecules up to ecosystems. The journal has launched as more and more institutes are founded that are similarly dedicated to this new approach. BMC Systems Biology builds on the ongoing success of the BMC series, providing a venue for all sound research in the systems-level analysis of biology.

Hierarchical structure of biological systems: a bioengineering approach.

Science.gov (United States)

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.

Biological Therapy in Systemic Lupus Erythematosus

Directory of Open Access Journals (Sweden)

Mariana Postal

2012-01-01

Full Text Available Systemic lupus erythematosus (SLE is a prototypic inflammatory autoimmune disorder characterized by multisystem involvement and fluctuating disease activity. Symptoms range from rather mild manifestations such as rash or arthritis to life-threatening end-organ manifestations. Despite new and improved therapy having positively impacted the prognosis of SLE, a subgroup of patients do not respond to conventional therapy. Moreover, the risk of fatal outcomes and the damaging side effects of immunosuppressive therapies in SLE call for an improvement in the current therapeutic management. New therapeutic approaches are focused on B-cell targets, T-cell downregulation and costimulatory blockade, cytokine inhibition, and the modulation of complement. Several biological agents have been developed, but this encouraging news is associated with several disappointments in trials and provide a timely moment to reflect on biologic therapy in SLE.

An engineering design approach to systems biology.

Science.gov (United States)

Janes, Kevin A; Chandran, Preethi L; Ford, Roseanne M; Lazzara, Matthew J; Papin, Jason A; Peirce, Shayn M; Saucerman, Jeffrey J; Lauffenburger, Douglas A

2017-07-17

Measuring and modeling the integrated behavior of biomolecular-cellular networks is central to systems biology. Over several decades, systems biology has been shaped by quantitative biologists, physicists, mathematicians, and engineers in different ways. However, the basic and applied versions of systems biology are not typically distinguished, which blurs the separate aspirations of the field and its potential for real-world impact. Here, we articulate an engineering approach to systems biology, which applies educational philosophy, engineering design, and predictive models to solve contemporary problems in an age of biomedical Big Data. A concerted effort to train systems bioengineers will provide a versatile workforce capable of tackling the diverse challenges faced by the biotechnological and pharmaceutical sectors in a modern, information-dense economy.

The Feasibility of Systems Thinking in Biology Education

Science.gov (United States)

Boersma, Kerst; Waarlo, Arend Jan; Klaassen, Kees

2011-01-01

Systems thinking in biology education is an up and coming research topic, as yet with contrasting feasibility claims. In biology education systems thinking can be understood as thinking backward and forward between concrete biological objects and processes and systems models representing systems theoretical characteristics. Some studies claim that…

Answering biological questions: Querying a systems biology database for nutrigenomics

NARCIS (Netherlands)

Evelo, C.T.; Bochove, K. van; Saito, J.T.

2011-01-01

The requirement of systems biology for connecting different levels of biological research leads directly to a need for integrating vast amounts of diverse information in general and of omics data in particular. The nutritional phenotype database addresses this challenge for nutrigenomics. A

Time-slicing subsystem of the biology small-angle x-ray scattering station at the National Synchrotron Light Source

International Nuclear Information System (INIS)

Stubblefield, F.W.

1985-11-01

The time-slicing subsystem of the Biology Small-Angle X-ray Scattering divides the time period during which the data for small-angle x-ray diffraction patterns from biological samples is collected into time slices (or frames). The subsystem, being part of a multiprocessor experiment control and data acquisition system, has its own dedicated processor; it also has special-purpose front-end electronics sufficient to generate the gating and other control signals required to produce a sequence of as many as 256 time slices, measured with a basic time unit of 1 μsec. The electronics also synchronizes with execution of the time slice sequence the application of stimuli to the biological sample, the measurement of voltages generated by the sample, and the application of auxiliary device trigger pulses and routes detector data and auxiliary scaler data into appropriate time-slice-indexed buffers in a large external data memory array. The structure of the entire experiment control and data acquisition system is briefly reviewed. Details of the structure and operation of the time slice subsystem are presented. 7 refs., 5 figs

Systems biology and biomarker discovery

Energy Technology Data Exchange (ETDEWEB)

Rodland, Karin D.

2010-12-01

Medical practitioners have always relied on surrogate markers of inaccessible biological processes to make their diagnosis, whether it was the pallor of shock, the flush of inflammation, or the jaundice of liver failure. Obviously, the current implementation of biomarkers for disease is far more sophisticated, relying on highly reproducible, quantitative measurements of molecules that are often mechanistically associated with the disease in question, as in glycated hemoglobin for the diagnosis of diabetes [1] or the presence of cardiac troponins in the blood for confirmation of myocardial infarcts [2]. In cancer, where the initial symptoms are often subtle and the consequences of delayed diagnosis often drastic for disease management, the impetus to discover readily accessible, reliable, and accurate biomarkers for early detection is compelling. Yet despite years of intense activity, the stable of clinically validated, cost-effective biomarkers for early detection of cancer is pathetically small and still dominated by a handful of markers (CA-125, CEA, PSA) first discovered decades ago. It is time, one could argue, for a fresh approach to the discovery and validation of disease biomarkers, one that takes full advantage of the revolution in genomic technologies and in the development of computational tools for the analysis of large complex datasets. This issue of Disease Markers is dedicated to one such new approach, loosely termed the 'Systems Biology of Biomarkers'. What sets the Systems Biology approach apart from other, more traditional approaches, is both the types of data used, and the tools used for data analysis - and both reflect the revolution in high throughput analytical methods and high throughput computing that has characterized the start of the twenty first century.

Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems

Science.gov (United States)

2011-01-01

Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete. PMID:21689427

[Habitability and biological life support systems for man].

Science.gov (United States)

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.

Collaborative Systems Biology Projects for the Military Medical Community.

Science.gov (United States)

Zalatoris, Jeffrey J; Scheerer, Julia B; Lebeda, Frank J

2017-09-01

This pilot study was conducted to examine, for the first time, the ongoing systems biology research and development projects within the laboratories and centers of the U.S. Army Medical Research and Materiel Command (USAMRMC). The analysis has provided an understanding of the breadth of systems biology activities, resources, and collaborations across all USAMRMC subordinate laboratories. The Systems Biology Collaboration Center at USAMRMC issued a survey regarding systems biology research projects to the eight U.S.-based USAMRMC laboratories and centers in August 2016. This survey included a data call worksheet to gather self-identified project and programmatic information. The general topics focused on the investigators and their projects, on the project's research areas, on omics and other large data types being collected and stored, on the analytical or computational tools being used, and on identifying intramural (i.e., USAMRMC) and extramural collaborations. Among seven of the eight laboratories, 62 unique systems biology studies were funded and active during the final quarter of fiscal year 2016. Of 29 preselected medical Research Task Areas, 20 were associated with these studies, some of which were applicable to two or more Research Task Areas. Overall, studies were categorized among six general types of objectives: biological mechanisms of disease, risk of/susceptibility to injury or disease, innate mechanisms of healing, diagnostic and prognostic biomarkers, and host/patient responses to vaccines, and therapeutic strategies including host responses to therapies. We identified eight types of omics studies and four types of study subjects. Studies were categorized on a scale of increasing complexity from single study subject/single omics technology studies (23/62) to studies integrating results across two study subject types and two or more omics technologies (13/62). Investigators at seven USAMRMC laboratories had collaborations with systems biology experts

Ion beam induced fluorescence imaging in biological systems

International Nuclear Information System (INIS)

Bettiol, Andrew A.; Mi, Zhaohong; Vanga, Sudheer Kumar; Chen, Ce-belle; Tao, Ye; Watt, Frank

2015-01-01

Imaging fluorescence generated by MeV ions in biological systems such as cells and tissue sections requires a high resolution beam (<100 nm), a sensitive detection system and a fluorescent probe that has a high quantum efficiency and low bleaching rate. For cutting edge applications in bioimaging, the fluorescence imaging technique needs to break the optical diffraction limit allowing for sub-cellular structure to be visualized, leading to a better understanding of cellular function. In a nuclear microprobe this resolution requirement can be readily achieved utilizing low beam current techniques such as Scanning Transmission Ion Microscopy (STIM). In recent times, we have been able to extend this capability to fluorescence imaging through the development of a new high efficiency fluorescence detection system, and through the use of new novel fluorescent probes that are resistant to ion beam damage (bleaching). In this paper we demonstrate ion beam induced fluorescence imaging in several biological samples, highlighting the advantages and challenges associated with using this technique

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

International Nuclear Information System (INIS)

Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

Energy Technology Data Exchange (ETDEWEB)

Lewis, Daniel D. [Integrative Genetics and Genomics, University of California Davis, Davis, CA (United States); Department of Biomedical Engineering, University of California Davis, Davis, CA (United States); Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng, E-mail: cmtan@ucdavis.edu [Department of Biomedical Engineering, University of California Davis, Davis, CA (United States)

2014-12-09

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

Science.gov (United States)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

Bioremediation 3.0: Engineering pollutant-removing bacteria in the times of systemic biology.

Science.gov (United States)

Dvořák, Pavel; Nikel, Pablo I; Damborský, Jiří; de Lorenzo, Víctor

2017-11-15

Elimination or mitigation of the toxic effects of chemical waste released to the environment by industrial and urban activities relies largely on the catalytic activities of microorganisms-specifically bacteria. Given their capacity to evolve rapidly, they have the biochemical power to tackle a large number of molecules mobilized from their geological repositories through human action (e.g., hydrocarbons, heavy metals) or generated through chemical synthesis (e.g., xenobiotic compounds). Whereas naturally occurring microbes already have considerable ability to remove many environmental pollutants with no external intervention, the onset of genetic engineering in the 1980s allowed the possibility of rational design of bacteria to catabolize specific compounds, which could eventually be released into the environment as bioremediation agents. The complexity of this endeavour and the lack of fundamental knowledge nonetheless led to the virtual abandonment of such a recombinant DNA-based bioremediation only a decade later. In a twist of events, the last few years have witnessed the emergence of new systemic fields (including systems and synthetic biology, and metabolic engineering) that allow revisiting the same environmental pollution challenges through fresh and far more powerful approaches. The focus on contaminated sites and chemicals has been broadened by the phenomenal problems of anthropogenic emissions of greenhouse gases and the accumulation of plastic waste on a global scale. In this article, we analyze how contemporary systemic biology is helping to take the design of bioremediation agents back to the core of environmental biotechnology. We inspect a number of recent strategies for catabolic pathway construction and optimization and we bring them together by proposing an engineering workflow. Copyright © 2017 Elsevier Inc. All rights reserved.

Effect of sludge retention time on continuous-flow system with enhanced biological phosphorus removal granules at different COD loading.

Science.gov (United States)

Li, Dong; Lv, Yufeng; Zeng, Huiping; Zhang, Jie

2016-11-01

The effect of sludge retention time (SRT) on the continuous-flow system with enhanced biological phosphorus removal (EBPR) granules at different COD loading was investigated during the operation of more than 220days. And the results showed that when the system operated at long SRT (30days) and low COD loading (200mg·L(-1)), it could maintain excellent performance. However, long SRT and high COD loading (300mg·L(-1)) deteriorated the settling ability of granules and the performance of system and resulted in the overgrowth of filamentous bacteria. Meanwhile, the transformation of poly-β-hydroxyalkanoates (PHAs) and glycogen in metabolism process was inhibited. Moreover, the results of pyrosequencing indicated that filamentous bacteria had a competitive advantage over polyphosphate-accumulating organisms (PAOs) at high COD loading and long SRT. The PAOs specious of Candidatus_Accumlibater and system performance increased obviously when the SRT was reduced to 20days at high COD loading. Copyright © 2016 Elsevier Ltd. All rights reserved.

Industrial systems biology and its impact on synthetic biology of yeast cell factories

DEFF Research Database (Denmark)

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-01-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools......, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex...... regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal...

Metabolomics: Definitions and Significance in Systems Biology.

Science.gov (United States)

Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

2017-01-01

Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

Applications of membrane computing in systems and synthetic biology

CERN Document Server

Gheorghe, Marian; Pérez-Jiménez, Mario

2014-01-01

Membrane Computing was introduced as a computational paradigm in Natural Computing. The models introduced, called Membrane (or P) Systems, provide a coherent platform to describe and study living cells as computational systems. Membrane Systems have been investigated for their computational aspects and employed to model problems in other fields, like: Computer Science, Linguistics, Biology, Economy, Computer Graphics, Robotics, etc. Their inherent parallelism, heterogeneity and intrinsic versatility allow them to model a broad range of processes and phenomena, being also an efficient means to solve and analyze problems in a novel way. Membrane Computing has been used to model biological systems, becoming with time a thorough modeling paradigm comparable, in its modeling and predicting capabilities, to more established models in this area. This book is the result of the need to collect, in an organic way, different facets of this paradigm. The chapters of this book, together with the web pages accompanying th...

Next-generation mammalian genetics toward organism-level systems biology.

Science.gov (United States)

Susaki, Etsuo A; Ukai, Hideki; Ueda, Hiroki R

2017-01-01

Organism-level systems biology in mammals aims to identify, analyze, control, and design molecular and cellular networks executing various biological functions in mammals. In particular, system-level identification and analysis of molecular and cellular networks can be accelerated by next-generation mammalian genetics. Mammalian genetics without crossing, where all production and phenotyping studies of genome-edited animals are completed within a single generation drastically reduce the time, space, and effort of conducting the systems research. Next-generation mammalian genetics is based on recent technological advancements in genome editing and developmental engineering. The process begins with introduction of double-strand breaks into genomic DNA by using site-specific endonucleases, which results in highly efficient genome editing in mammalian zygotes or embryonic stem cells. By using nuclease-mediated genome editing in zygotes, or ~100% embryonic stem cell-derived mouse technology, whole-body knock-out and knock-in mice can be produced within a single generation. These emerging technologies allow us to produce multiple knock-out or knock-in strains in high-throughput manner. In this review, we discuss the basic concepts and related technologies as well as current challenges and future opportunities for next-generation mammalian genetics in organism-level systems biology.

Systems Biology of Industrial Microorganisms

Science.gov (United States)

Papini, Marta; Salazar, Margarita; Nielsen, Jens

The field of industrial biotechnology is expanding rapidly as the chemical industry is looking towards more sustainable production of chemicals that can be used as fuels or building blocks for production of solvents and materials. In connection with the development of sustainable bioprocesses, it is a major challenge to design and develop efficient cell factories that can ensure cost efficient conversion of the raw material into the chemical of interest. This is achieved through metabolic engineering, where the metabolism of the cell factory is engineered such that there is an efficient conversion of sugars, the typical raw materials in the fermentation industry, into the desired product. However, engineering of cellular metabolism is often challenging due to the complex regulation that has evolved in connection with adaptation of the different microorganisms to their ecological niches. In order to map these regulatory structures and further de-regulate them, as well as identify ingenious metabolic engineering strategies that full-fill mass balance constraints, tools from systems biology can be applied. This involves both high-throughput analysis tools like transcriptome, proteome and metabolome analysis, as well as the use of mathematical modeling to simulate the phenotypes resulting from the different metabolic engineering strategies. It is in fact expected that systems biology may substantially improve the process of cell factory development, and we therefore propose the term Industrial Systems Biology for how systems biology will enhance the development of industrial biotechnology for sustainable chemical production.

Study of the effects of radon in three biological systems

International Nuclear Information System (INIS)

Tavera, L.; Balcazar, M.; Lopez, A.; Brena, M.; Rosa, M.E. De la; Villalobos P, R.

2002-01-01

The radon and its decay products are responsible of the 3/4 parts of the exposure of the persons to the environmental radiation. The discovery at the end of XIX Century of the illnesses, mainly of cancer, which appeared in the presence of radon, lead to an accelerated growing of the radon studies: monitoring, dosimetry, effects on the persons, etc. Several epidemiological studies of radon in miners and population in general have been realized; advancing in the knowledge about the concentration-lung cancer risk relationship, but with discrepancies in the results depending on the concentration levels. Therefor, studies which consuming time, efforts and money go on doing. The research of the radon effects in biological systems different to human, allows to realize studies in less time, in controlled conditions and generally at lower cost, generating information about the alpha radiation effects in the cellular field. Therefor it was decided to study the response of three biological systems exposed to radon: an unicellular bacteria Escherichia Coli which was exposed directly to alpha particles from an electrodeposited source for determining the sensitivity limit of the chose technique. A plant, Tradescantia, for studying the cytogenetic effect of the system exposed to controlled concentrations of radon. An insect, Drosophila Melanogaster, for studying the genetic effects and the accumulated effects in several generations exposed to radon. In this work the experimental settlements are presented for the expositions of the systems and the biological results commenting the importance of these. (Author)

Time delay systems theory, numerics, applications, and experiments

CERN Document Server

Ersal, Tulga; Orosz, Gábor

2017-01-01

This volume collects contributions related to selected presentations from the 12th IFAC Workshop on Time Delay Systems, Ann Arbor, June 28-30, 2015. The included papers present novel techniques and new results of delayed dynamical systems. The topical spectrum covers control theory, numerical analysis, engineering and biological applications as well as experiments and case studies. The target audience primarily comprises research experts in the field of time delay systems, but the book may also be beneficial for graduate students alike. .

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Systems Biology for Organotypic Cell Cultures

Energy Technology Data Exchange (ETDEWEB)

Grego, Sonia [RTI International, Research Triangle Park, NC (United States); Dougherty, Edward R. [Texas A & M Univ., College Station, TX (United States); Alexander, Francis J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Auerbach, Scott S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Berridge, Brian R. [GlaxoSmithKline, Research Triangle Park, NC (United States); Bittner, Michael L. [Translational Genomics Research Inst., Phoenix, AZ (United States); Casey, Warren [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Cooley, Philip C. [RTI International, Research Triangle Park, NC (United States); Dash, Ajit [HemoShear Therapeutics, Charlottesville, VA (United States); Ferguson, Stephen S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Fennell, Timothy R. [RTI International, Research Triangle Park, NC (United States); Hawkins, Brian T. [RTI International, Research Triangle Park, NC (United States); Hickey, Anthony J. [RTI International, Research Triangle Park, NC (United States); Kleensang, Andre [Johns Hopkins Univ., Baltimore, MD (United States). Center for Alternatives to Animal Testing; Liebman, Michael N. [IPQ Analytics, Kennett Square, PA (United States); Martin, Florian [Phillip Morris International, Neuchatel (Switzerland); Maull, Elizabeth A. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Paragas, Jason [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Qiao, Guilin [Defense Threat Reduction Agency, Ft. Belvoir, VA (United States); Ramaiahgari, Sreenivasa [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Sumner, Susan J. [RTI International, Research Triangle Park, NC (United States); Yoon, Miyoung [The Hamner Inst. for Health Sciences, Research Triangle Park, NC (United States); ScitoVation, Research Triangle Park, NC (United States)

2016-08-04

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. This consensus report summarizes the discussions held.

Impact of Thermodynamic Principles in Systems Biology

NARCIS (Netherlands)

Heijnen, J.J.

2010-01-01

It is shown that properties of biological systems which are relevant for systems biology motivated mathematical modelling are strongly shaped by general thermodynamic principles such as osmotic limit, Gibbs energy dissipation, near equilibria and thermodynamic driving force. Each of these aspects

Time lags in biological models

CERN Document Server

MacDonald, Norman

1978-01-01

In many biological models it is necessary to allow the rates of change of the variables to depend on the past history, rather than only the current values, of the variables. The models may require discrete lags, with the use of delay-differential equations, or distributed lags, with the use of integro-differential equations. In these lecture notes I discuss the reasons for including lags, especially distributed lags, in biological models. These reasons may be inherent in the system studied, or may be the result of simplifying assumptions made in the model used. I examine some of the techniques available for studying the solution of the equations. A large proportion of the material presented relates to a special method that can be applied to a particular class of distributed lags. This method uses an extended set of ordinary differential equations. I examine the local stability of equilibrium points, and the existence and frequency of periodic solutions. I discuss the qualitative effects of lags, and how these...

Role of time in symbiotic systems

Energy Technology Data Exchange (ETDEWEB)

Agrawala, A.K. [Univ. of Maryland, College Park, MD (United States)

1996-12-31

All systems have a dynamics which reflects the changes in the system in time and, therefore, have to maintain a notion of time, either explicitly or implicitly. Traditionally, the notion of time in constructed systems has been implicitly specified at design time through rigid structures such as sampled data systems which operate with a fixed time tick, feedback systems which are designed reflecting a fixed time scale for the dynamics of the system as well as the controller responses, etc. In biological systems, the sense of time is a key element but it is not rigidly structured, even though all such systems have a clear notion of time. We define the notion of time in systems in terms of temporal locality, time scale and time horizon. Temporal locality gives the notion of the accuracy with which the system knows about the current time. Time scale reflects the scale indicating the smallest and the largest granularity considered. It also reflects the reaction time. The time horizon indicates the time beyond which the system considers to be distant future and may not take it into account in its actions. Note that the temporal locality, time scale and the time horizon may be different for different types of actions of a system, thereby permitting the system to use multiple notions of time concurrently. In multi agent systems each subsystem may have its own notion of time but when intentions take place a coordination is necessary. Such coordination requires that the notions of time for different agents of the system be consistent. Clearly, the consistency requirement in this case does not mean exactly identical but implies that different agents can coordinate their actions which must take place in time. When the actions only require a determinate ordering the required coordination is much less severe than the case requiring actions to take place at the same time.

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

KAUST Repository

Klingbeil, G.

2011-02-25

Motivation: 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. Results: 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 Author 2011. Published by Oxford University Press. All rights reserved.

Systems Biology of Metabolism: Annual Review of Biochemistry

DEFF Research Database (Denmark)

Nielsen, Jens

2017-01-01

Metabolism is highly complex and involves thousands of different connected reactions; it is therefore necessary to use mathematical models for holistic studies. The use of mathematical models in biology is referred to as systems biology. In this review, the principles of systems biology are descr...

Toxicity of silver nanoparticles in biological systems: Does the complexity of biological systems matter?

Science.gov (United States)

Vazquez-Muñoz, Roberto; Borrego, Belen; Juárez-Moreno, Karla; García-García, Maritza; Mota Morales, Josué D; Bogdanchikova, Nina; Huerta-Saquero, Alejandro

2017-07-05

Currently, nanomaterials are more frequently in our daily life, specifically in biomedicine, electronics, food, textiles and catalysis just to name a few. Although nanomaterials provide many benefits, recently their toxicity profiles have begun to be explored. In this work, the toxic effects of silver nanoparticles (35nm-average diameter and Polyvinyl-Pyrrolidone-coated) on biological systems of different levels of complexity was assessed in a comprehensive and comparatively way, through a variety of viability and toxicological assays. The studied organisms included viruses, bacteria, microalgae, fungi, animal and human cells (including cancer cell lines). It was found that biological systems of different taxonomical groups are inhibited at concentrations of silver nanoparticles within the same order of magnitude. Thus, the toxicity of nanomaterials on biological/living systems, constrained by their complexity, e.g. taxonomic groups, resulted contrary to the expected. The fact that cells and virus are inhibited with a concentration of silver nanoparticles within the same order of magnitude could be explained considering that silver nanoparticles affects very primitive cellular mechanisms by interacting with fundamental structures for cells and virus alike. Copyright © 2017 Elsevier B.V. All rights reserved.

The Systems Biology Research Tool: evolvable open-source software

Directory of Open Access Journals (Sweden)

Wright Jeremiah

2008-06-01

Full Text Available Abstract Background Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. Results We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. Conclusion The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability, to facilitate cooperation among researchers, and to expedite progress in the field of systems biology.

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

Science.gov (United States)

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among

Plant Systems Biology at the Single-Cell Level.

Science.gov (United States)

Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

2017-11-01

Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

On the interplay between mathematics and biology: hallmarks toward a new systems biology.

Science.gov (United States)

Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M; Alghamdi, Mohammed Ali

2015-03-01

This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach. Copyright © 2014 Elsevier B.V. All rights reserved.

Systems Biology — the Broader Perspective

Directory of Open Access Journals (Sweden)

Jonathan Bard

2013-06-01

Full Text Available Systems biology has two general aims: a narrow one, which is to discover how complex networks of proteins work, and a broader one, which is to integrate the molecular and network data with the generation and function of organism phenotypes. Doing all this involves complex methodologies, but underpinning the subject are more general conceptual problems about upwards and downwards causality, complexity and information storage, and their solutions provide the constraints within which these methodologies can be used. This essay considers these general aspects and the particular role of protein networks; their functional outputs are often the processes driving phenotypic change and physiological function—networks are, in a sense, the units of systems biology much as proteins are for molecular biology. It goes on to argue that the natural language for systems-biological descriptions of biological phenomena is the mathematical graph (a set of connected facts of the general form [process] (e.g., [activates] . Such graphs not only integrate events at different levels but emphasize the distributed nature of control as well as displaying a great deal of data. The implications and successes of these ideas for physiology, pharmacology, development and evolution are briefly considered. The paper concludes with some challenges for the future.

Biological repair with time-dependent irradiation

International Nuclear Information System (INIS)

Broyles, A.A.; Shapiro, C.S.

1985-01-01

Recent experiments have provided new data that explore the effectiveness of biological repair in assessing damage due to exposures from ionizing radiation. These data are mainly from experiments conducted at constant dose rates, to study the effectiveness per unit dose of different dose rates. Here, we develop new formulae to estimate the effectiveness of an arbitrary time-dependent dose rate exposure

Systems Biology and Stem Cell Pluripotency

DEFF Research Database (Denmark)

Mashayekhi, Kaveh; Hall, Vanessa Jane; Freude, Kristine

2016-01-01

Recent breakthroughs in stem cell biology have accelerated research in the area of regenerative medicine. Over the past years, it has become possible to derive patient-specific stem cells which can be used to generate different cell populations for potential cell therapy. Systems biological...... modeling of stem cell pluripotency and differentiation have largely been based on prior knowledge of signaling pathways, gene regulatory networks, and epigenetic factors. However, there is a great need to extend the complexity of the modeling and to integrate different types of data, which would further...... improve systems biology and its uses in the field. In this chapter, we first give a general background on stem cell biology and regenerative medicine. Stem cell potency is introduced together with the hierarchy of stem cells ranging from pluripotent embryonic stem cells (ESCs) and induced pluripotent stem...

Industrial systems biology and its impact on synthetic biology of yeast cell factories.

Science.gov (United States)

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-06-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Optoelectronic system and apparatus for connection to biological systems

Science.gov (United States)

Okandan, Murat; Nielson, Gregory N.

2018-03-06

The present invention relates to a biological probe structure, as well as apparatuses, systems, and methods employing this structure. In particular embodiments, the structure includes a hermetically sealed unit configured to receive and transmit one or more optical signals. Furthermore, the structure can be implanted subcutaneously and interrogated externally. In this manner, a minimally invasive method can be employed to detect, treat, and/or assess the biological target. Additional methods and systems are also provided.

A review of imaging techniques for systems biology

Directory of Open Access Journals (Sweden)

Po Ming J

2008-08-01

Full Text Available Abstract This paper presents a review of imaging techniques and of their utility in system biology. During the last decade systems biology has matured into a distinct field and imaging has been increasingly used to enable the interplay of experimental and theoretical biology. In this review, we describe and compare the roles of microscopy, ultrasound, CT (Computed Tomography, MRI (Magnetic Resonance Imaging, PET (Positron Emission Tomography, and molecular probes such as quantum dots and nanoshells in systems biology. As a unified application area among these different imaging techniques, examples in cancer targeting are highlighted.

Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

Science.gov (United States)

Saks, Valdur; Monge, Claire; Guzun, Rita

2009-01-01

We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed. PMID:19399243

Multiway modeling and analysis in stem cell systems biology

Directory of Open Access Journals (Sweden)

Vandenberg Scott L

2008-07-01

Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

Macroscopic Quantum-Type Potentials in Theoretical Systems Biology

Directory of Open Access Journals (Sweden)

Laurent Nottale

2013-12-01

Full Text Available We review in this paper the use of the theory of scale relativity and fractal space-time as a tool particularly well adapted to the possible development of a future genuine systems theoretical biology. We emphasize in particular the concept of quantum-type potentials, since, in many situations, the effect of the fractality of space—or of the underlying medium—can be reduced to the addition of such a potential energy to the classical equations of motion. Various equivalent representations—geodesic, quantum-like, fluid mechanical, stochastic—of these equations are given, as well as several forms of generalized quantum potentials. Examples of their possible intervention in high critical temperature superconductivity and in turbulence are also described, since some biological processes may be similar in some aspects to these physical phenomena. These potential extra energy contributions could have emerged in biology from the very fractal nature of the medium, or from an evolutive advantage, since they involve spontaneous properties of self-organization, morphogenesis, structuration and multi-scale integration. Finally, some examples of applications of the theory to actual biological-like processes and functions are also provided.

A system for success: BMC Systems Biology, a new open access journal

OpenAIRE

Webb Penelope A; Hodgkinson Matt J

2007-01-01

Abstract BMC Systems Biology is the first open access journal spanning the growing field of systems biology from molecules up to ecosystems. The journal has launched as more and more institutes are founded that are similarly dedicated to this new approach. BMC Systems Biology builds on the ongoing success of the BMC series, providing a venue for all sound research in the systems-level analysis of biology.

Systems biology of neutrophil differentiation and immune response

DEFF Research Database (Denmark)

Theilgaard-Mönch, Kim; Porse, Bo T; Borregaard, Niels

2005-01-01

Systems biology has emerged as a new scientific field, which aims at investigating biological processes at the genomic and proteomic levels. Recent studies have unravelled aspects of neutrophil differentiation and immune responses at the systems level using high-throughput technologies. These stu......Systems biology has emerged as a new scientific field, which aims at investigating biological processes at the genomic and proteomic levels. Recent studies have unravelled aspects of neutrophil differentiation and immune responses at the systems level using high-throughput technologies....... These studies have identified a plethora of novel effector proteins stored in the granules of neutrophils. In addition, these studies provide evidence that neutrophil differentiation and immune response are governed by a highly coordinated transcriptional programme that regulates cellular fate and function...

Biological Potential in Serpentinizing Systems

Science.gov (United States)

Hoehler, Tori M.

2016-01-01

Generation of the microbial substrate hydrogen during serpentinization, the aqueous alteration of ultramafic rocks, has focused interest on the potential of serpentinizing systems to support biological communities or even the origin of life. However the process also generates considerable alkalinity, a challenge to life, and both pH and hydrogen concentrations vary widely across natural systems as a result of different host rock and fluid composition and differing physical and hydrogeologic conditions. Biological potential is expected to vary in concert. We examined the impact of such variability on the bioenergetics of an example metabolism, methanogenesis, using a cell-scale reactive transport model to compare rates of metabolic energy generation as a function of physicochemical environment. Potential rates vary over more than 5 orders of magnitude, including bioenergetically non-viable conditions, across the range of naturally occurring conditions. In parallel, we assayed rates of hydrogen metabolism in wells associated with the actively serpentinizing Coast Range Ophiolite, which includes conditions more alkaline and considerably less reducing than is typical of serpentinizing systems. Hydrogen metabolism is observed at pH approaching 12 but, consistent with the model predictions, biological methanogenesis is not observed.

On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

Science.gov (United States)

Gomez-Ramirez, Jaime; Sanz, Ricardo

2013-09-01

One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.

Systems biology approach to bioremediation

Energy Technology Data Exchange (ETDEWEB)

Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

2012-06-01

Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potential for making bioremediation breakthroughs and illuminating the ‘black box’.

Growing trend of CE at the omics level: the frontier of systems biology.

Science.gov (United States)

Oh, Eulsik; Hasan, Md Nabiul; Jamshed, Muhammad; Park, Soo Hyun; Hong, Hye-Min; Song, Eun Joo; Yoo, Young Sook

2010-01-01

In a novel attempt to comprehend the complexity of life, systems biology has recently emerged as a state-of-the-art approach for biological research in contrast to the reductionist approaches that have been used in molecular cell biology since the 1950s. Because a massive amount of information is required in many systems biology studies of life processes, we have increasingly come to depend on techniques that provide high-throughput omics data. CE and CE coupled to MS have served as powerful analytical tools for providing qualitative and quantitative omics data. Recent systems biology studies have focused strongly on the diagnosis and treatment of diseases. The increasing number of clinical research papers on drug discovery and disease therapies reflects this growing interest among scientists. Since such clinical research reflects one of the ultimate purposes of bioscience, these trends will be sustained for a long time. Thus, this review mainly focuses on the application of CE and CE-MS in diagnosis as well as on the latest CE methods developed. Furthermore, we outline the new challenges that arose in 2008 and later in elucidating the system-level functions of the bioconstituents of living organisms.

BetaWB - A language for modular representation of biological systems

DEFF Research Database (Denmark)

Ihekwaba, Adoha; Larcher, Roberto; Mardare, Radu Iulian

2007-01-01

A. Ihekwaba, R. Larcher, R. Mardare, C. Priami. BetaWB - A language for modular representation of biological systems. In Proc. of International Conference on Systems Biology (ICSB), 2007......A. Ihekwaba, R. Larcher, R. Mardare, C. Priami. BetaWB - A language for modular representation of biological systems. In Proc. of International Conference on Systems Biology (ICSB), 2007...

Teleology and its constitutive role for biology as the science of organized systems in nature.

Science.gov (United States)

Toepfer, Georg

2012-03-01

'Nothing in biology makes sense, except in the light of teleology'. This could be the first sentence in a textbook about the methodology of biology. The fundamental concepts in biology, e.g. 'organism' and 'ecosystem', are only intelligible given a teleological framework. Since early modern times, teleology has often been considered methodologically unscientific. With the acceptance of evolutionary theory, one popular strategy for accommodating teleological reasoning was to explain it by reference to selection in the past: functions were reconstructed as 'selected effects'. But the theory of evolution obviously presupposes the existence of organisms as organized and regulated, i.e. functional systems. Therefore, evolutionary theory cannot provide the foundation for teleology. The underlying reason for the central methodological role of teleology in biology is not its potential to offer particular forms of (evolutionary) explanations for the presence of parts, but rather an ontological one: organisms and other basic biological entities do not exist as physical bodies do, as amounts of matter with a definite form. Rather, they are dynamic systems in stable equilibrium; despite changes of their matter and form (in metabolism and metamorphosis) they maintain their identity. What remains constant in these kinds of systems is their 'organization', i.e. the causal pattern of interdependence of parts with certain effects of each part being relevant for the working of the system. Teleological analysis consists in the identification of these system-relevant effects and at the same time of the system as a whole. Therefore, the identity of biological systems cannot be specified without teleological reasoning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Yeast systems biology to unravel the network of life

DEFF Research Database (Denmark)

Mustacchi, Roberta; Hohmann, S; Nielsen, Jens

2006-01-01

Systems biology focuses on obtaining a quantitative description of complete biological systems, even complete cellular function. In this way, it will be possible to perform computer-guided design of novel drugs, advanced therapies for treatment of complex diseases, and to perform in silico design....... Furthermore, it serves as an industrial workhorse for production of a wide range of chemicals and pharmaceuticals. Systems biology involves the combination of novel experimental techniques from different disciplines as well as functional genomics, bioinformatics and mathematical modelling, and hence no single...... laboratory has access to all the necessary competences. For this reason the Yeast Systems Biology Network (YSBN) has been established. YSBN will coordinate research efforts, in yeast systems biology and, through the recently obtained EU funding for a Coordination Action, it will be possible to set...

3S - Systematic, systemic, and systems biology and toxicology.

Science.gov (United States)

Smirnova, Lena; Kleinstreuer, Nicole; Corvi, Raffaella; Levchenko, Andre; Fitzpatrick, Suzanne C; Hartung, Thomas

2018-01-01

A biological system is more than the sum of its parts - it accomplishes many functions via synergy. Deconstructing the system down to the molecular mechanism level necessitates the complement of reconstructing functions on all levels, i.e., in our conceptualization of biology and its perturbations, our experimental models and computer modelling. Toxicology contains the somewhat arbitrary subclass "systemic toxicities"; however, there is no relevant toxic insult or general disease that is not systemic. At least inflammation and repair are involved that require coordinated signaling mechanisms across the organism. However, the more body components involved, the greater the challenge to reca-pitulate such toxicities using non-animal models. Here, the shortcomings of current systemic testing and the development of alternative approaches are summarized. We argue that we need a systematic approach to integrating existing knowledge as exemplified by systematic reviews and other evidence-based approaches. Such knowledge can guide us in modelling these systems using bioengineering and virtual computer models, i.e., via systems biology or systems toxicology approaches. Experimental multi-organ-on-chip and microphysiological systems (MPS) provide a more physiological view of the organism, facilitating more comprehensive coverage of systemic toxicities, i.e., the perturbation on organism level, without using substitute organisms (animals). The next challenge is to establish disease models, i.e., micropathophysiological systems (MPPS), to expand their utility to encompass biomedicine. Combining computational and experimental systems approaches and the chal-lenges of validating them are discussed. The suggested 3S approach promises to leverage 21st century technology and systematic thinking to achieve a paradigm change in studying systemic effects.

Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm.

Science.gov (United States)

Tchagang, Alain B; Phan, Sieu; Famili, Fazel; Shearer, Heather; Fobert, Pierre; Huang, Yi; Zou, Jitao; Huang, Daiqing; Cutler, Adrian; Liu, Ziying; Pan, Youlian

2012-04-04

Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space. We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (Plasmodium chabaudi), systemic acquired resistance in Arabidopsis thaliana, similarities and differences between inner and outer cotyledon in Brassica napus during seed development, and to Brassica napus whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples. Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data.

A dedicated database system for handling multi-level data in systems biology.

Science.gov (United States)

Pornputtapong, Natapol; Wanichthanarak, Kwanjeera; Nilsson, Avlant; Nookaew, Intawat; Nielsen, Jens

2014-01-01

Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging. To overcome this, we designed and developed a dedicated database system that can serve and solve the vital issues in data management and hereby facilitate data integration, modeling and analysis in systems biology within a sole database. In addition, a yeast data repository was implemented as an integrated database environment which is operated by the database system. Two applications were implemented to demonstrate extensibility and utilization of the system. Both illustrate how the user can access the database via the web query function and implemented scripts. These scripts are specific for two sample cases: 1) Detecting the pheromone pathway in protein interaction networks; and 2) Finding metabolic reactions regulated by Snf1 kinase. In this study we present the design of database system which offers an extensible environment to efficiently capture the majority of biological entities and relations encountered in systems biology. Critical functions and control processes were designed and implemented to ensure consistent, efficient, secure and reliable transactions. The two sample cases on the yeast integrated data clearly demonstrate the value of a sole database environment for systems biology research.

Strategies for structuring interdisciplinary education in Systems Biology

DEFF Research Database (Denmark)

Cvijovic, Marija; Höfer, Thomas; Aćimović, Jure

2016-01-01

function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material...... and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active...... performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii...

Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

Directory of Open Access Journals (Sweden)

Valdur Saks

2009-03-01

Full Text Available We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed.

Time-evolution of the entropy of fluctuations in some biological systems as investigated by NMR

International Nuclear Information System (INIS)

Lenk, R.

1979-01-01

A simple expression for the entropy of fluctuations has been developed, using the tunnelling-effect model. This gives the possibility to estimate the changes and evolution of entropy in non-crystalline and biological samples by NMR investigations. On the other hand, the oscillatory character of the time-evolution of some properties, experimentally found in the investigated samples of plants, is interpreted in terms of the generalized master equation with an exponential memory function. (Auth.)

Redefining plant systems biology: from cell to ecosystem

NARCIS (Netherlands)

Keurentjes, J.J.B.; Angenent, G.C.; Dicke, M.; Martins Dos Santos, V.A.P.; Molenaar, J.; Van der Putten, W.H.; de Ruiter, P.C.; Struik, P.C.; Thomma, B.P.H.J.

2011-01-01

Molecular biologists typically restrict systems biology to cellular levels. By contrast, ecologists define biological systems as communities of interacting individuals at different trophic levels that process energy, nutrient and information flows. Modern plant breeding needs to increase

Electromagnetic fields in biological systems

National Research Council Canada - National Science Library

Lin, James C

2012-01-01

"Focusing on exposure, induced fields, and absorbed energy, this volume covers the interaction of electromagnetic fields and waves with biological systems, spanning static fields to terahertz waves...

Systems biology solutions for biochemical production challenges

DEFF Research Database (Denmark)

Hansen, Anne Sofie Lærke; Lennen, Rebecca M; Sonnenschein, Nikolaus

2017-01-01

There is an urgent need to significantly accelerate the development of microbial cell factories to produce fuels and chemicals from renewable feedstocks in order to facilitate the transition to a biobased society. Methods commonly used within the field of systems biology including omics...... characterization, genome-scale metabolic modeling, and adaptive laboratory evolution can be readily deployed in metabolic engineering projects. However, high performance strains usually carry tens of genetic modifications and need to operate in challenging environmental conditions. This additional complexity...... compared to basic science research requires pushing systems biology strategies to their limits and often spurs innovative developments that benefit fields outside metabolic engineering. Here we survey recent advanced applications of systems biology methods in engineering microbial production strains...

Synthetic Biology: Engineering Living Systems from Biophysical Principles.

Science.gov (United States)

Bartley, Bryan A; Kim, Kyung; Medley, J Kyle; Sauro, Herbert M

2017-03-28

Synthetic biology was founded as a biophysical discipline that sought explanations for the origins of life from chemical and physical first principles. Modern synthetic biology has been reinvented as an engineering discipline to design new organisms as well as to better understand fundamental biological mechanisms. However, success is still largely limited to the laboratory and transformative applications of synthetic biology are still in their infancy. Here, we review six principles of living systems and how they compare and contrast with engineered systems. We cite specific examples from the synthetic biology literature that illustrate these principles and speculate on their implications for further study. To fully realize the promise of synthetic biology, we must be aware of life's unique properties. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Casual Games and Casual Learning About Human Biological Systems

Science.gov (United States)

Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia

2016-02-01

Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human biological systems. Two hundred and forty-two children were given pretests at a Museum and posttests at home after playing either a treatment or control game. Also, 41 children were interviewed to explore deeper meanings behind the test results. Results show modest improvement in scientific attitudes, ability to identify human biological systems and in the children's ability to describe how those systems work together in real-world scenarios. Interviews reveal that children drew upon their prior school learning as they played the game. Also, on the surface they perceived the game as mainly entertainment but were easily able to discern learning outcomes when prompted. Implications for the design of casual games and how they can be used to enhance transfer of knowledge from the classroom to everyday life are discussed.

Integrating external biological knowledge in the construction of regulatory networks from time-series expression data

Directory of Open Access Journals (Sweden)

Lo Kenneth

2012-08-01

Full Text Available Abstract Background Inference about regulatory networks from high-throughput genomics data is of great interest in systems biology. We present a Bayesian approach to infer gene regulatory networks from time series expression data by integrating various types of biological knowledge. Results We formulate network construction as a series of variable selection problems and use linear regression to model the data. Our method summarizes additional data sources with an informative prior probability distribution over candidate regression models. We extend the Bayesian model averaging (BMA variable selection method to select regulators in the regression framework. We summarize the external biological knowledge by an informative prior probability distribution over the candidate regression models. Conclusions We demonstrate our method on simulated data and a set of time-series microarray experiments measuring the effect of a drug perturbation on gene expression levels, and show that it outperforms leading regression-based methods in the literature.

The aims of systems biology: between molecules and organisms.

Science.gov (United States)

Noble, D

2011-05-01

The systems approach to biology has a long history. Its recent rapid resurgence at the turn of the century reflects the problems encountered in interpreting the sequencing of the genome and the failure of that immense achievement to provide rapid and direct solutions to major multi-factorial diseases. This paper argues that systems biology is necessarily multilevel and that there is no privileged level of causality in biological systems. It is an approach rather than a separate discipline. Functionality arises from biological networks that interact with the genome, the environment and the phenotype. This view of biology is very different from the gene-centred views of neo-Darwinism and molecular biology. In neuroscience, the systems approach leads naturally to 2 important conclusions: first, that the idea of 'programs' in the brain is confusing, and second, that the self is better interpreted as a process than as an object. © Georg Thieme Verlag KG Stuttgart · New York.

Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

Science.gov (United States)

Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A

2012-07-02

Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

Directory of Open Access Journals (Sweden)

Daniel eLewis

2014-12-01

Full Text Available As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo systems, with only a few examples of prominent work done on predicting the dynamics of cell-free systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Systems Biology: Impressions from a Newcomer Graduate Student in 2016

Science.gov (United States)

Simpson, Melanie Rae

2016-01-01

As a newcomer, the philosophical basis of systems biology seems intuitive and appealing, the underlying philosophy being that the whole of a living system cannot be completely understood by the study of its individual parts. Yet answers to the questions "What is systems biology?" and "What constitutes a systems biology approach in…

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

Science.gov (United States)

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.

Mathematical methods in systems biology.

Science.gov (United States)

Kashdan, Eugene; Duncan, Dominique; Parnell, Andrew; Schattler, Heinz

2016-12-01

The editors of this Special Issue of Mathematical Biosciences and Engineering were the organizers for the Third International Workshop "Mathematical Methods in System Biology" that took place on June 15-18, 2015 at the University College Dublin in Ireland. As stated in the workshop goals, we managed to attract a good mix of mathematicians and statisticians working on biological and medical applications with biologists and clinicians interested in presenting their challenging problems and looking to find mathematical and statistical tools for their solutions.

Nanoscale technology in biological systems

CERN Document Server

Greco, Ralph S; Smith, R Lane

2004-01-01

Reviewing recent accomplishments in the field of nanobiology Nanoscale Technology in Biological Systems introduces the application of nanoscale matrices to human biology. It focuses on the applications of nanotechnology fabrication to biomedical devices and discusses new physical methods for cell isolation and manipulation and intracellular communication at the molecular level. It also explores the application of nanobiology to cardiovascular diseases, oncology, transplantation, and a range of related disciplines. This book build a strong background in nanotechnology and nanobiology ideal for

Modeling of biological intelligence for SCM system optimization.

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available 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

Science.gov (United States)

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

Systems biology at work

NARCIS (Netherlands)

Martins Dos Santos, V.A.P.; Damborsky, J.

2010-01-01

In his editorial overview for the 2008 Special Issue on this topic, the late Jaroslav Stark pointedly noted that systems biology is no longer a niche pursuit, but a recognized discipline in its own right “noisily” coming of age [1]. Whilst general underlying principles and basic techniques are now

BETAview: a digital {beta}-imaging system for dynamic studies of biological phenomena

Energy Technology Data Exchange (ETDEWEB)

Bertolucci, E.; Conti, M.; Mettivier, G.; Montesi, M.C. E-mail: montesi@na.infn.it; Russo, P

2002-02-01

We present a digital autoradiography (DAR) system, named BETAview, based on semiconductor pixel detectors and a single particle counting chip, for quantitative analysis of {beta}-emitting radioactive tracers in biological samples. The system is able to perform a real time monitoring of time-dependent biological phenomena. BETAview could be equipped either with GaAs or with Si semiconductor pixellated detectors. In this paper, we describe the results obtained with an assembly based on a Si detector, 300 {mu}m thick, segmented into 64x64 170 {mu}m size square pixels. The detector is bump-bonded to the low threshold, single particle counting chip named Medipix1, developed by a CERN-based European collaboration. The sensitive area is about 1 cm{sup 2}. Studies of background noise and detection efficiency have been performed. Moreover, time-resolved cellular uptake studies with radiolabelled molecules have been monitored. Specifically, we have followed in vivo and in real time, the [{sup 14}C]L-leucine amino acid uptake by eggs of Octopus vulgaris confirming the preliminary results of a previous paper. This opens the field of biomolecular kynetic studies with this new class of semiconductor DAR systems, whose evolution (using the Medipix2 chip, 256x256 pixels, 55 {mu}m pixel size) is soon to come.

BETAview: a digital β-imaging system for dynamic studies of biological phenomena

International Nuclear Information System (INIS)

Bertolucci, E.; Conti, M.; Mettivier, G.; Montesi, M.C.; Russo, P.

2002-01-01

We present a digital autoradiography (DAR) system, named BETAview, based on semiconductor pixel detectors and a single particle counting chip, for quantitative analysis of β-emitting radioactive tracers in biological samples. The system is able to perform a real time monitoring of time-dependent biological phenomena. BETAview could be equipped either with GaAs or with Si semiconductor pixellated detectors. In this paper, we describe the results obtained with an assembly based on a Si detector, 300 μm thick, segmented into 64x64 170 μm size square pixels. The detector is bump-bonded to the low threshold, single particle counting chip named Medipix1, developed by a CERN-based European collaboration. The sensitive area is about 1 cm 2 . Studies of background noise and detection efficiency have been performed. Moreover, time-resolved cellular uptake studies with radiolabelled molecules have been monitored. Specifically, we have followed in vivo and in real time, the [ 14 C]L-leucine amino acid uptake by eggs of Octopus vulgaris confirming the preliminary results of a previous paper. This opens the field of biomolecular kynetic studies with this new class of semiconductor DAR systems, whose evolution (using the Medipix2 chip, 256x256 pixels, 55 μm pixel size) is soon to come

Advances in Structural Biology and the Application to Biological Filament Systems.

Science.gov (United States)

Popp, David; Koh, Fujiet; Scipion, Clement P M; Ghoshdastider, Umesh; Narita, Akihiro; Holmes, Kenneth C; Robinson, Robert C

2018-04-01

Structural biology has experienced several transformative technological advances in recent years. These include: development of extremely bright X-ray sources (microfocus synchrotron beamlines and free electron lasers) and the use of electrons to extend protein crystallography to ever decreasing crystal sizes; and an increase in the resolution attainable by cryo-electron microscopy. Here we discuss the use of these techniques in general terms and highlight their application for biological filament systems, an area that is severely underrepresented in atomic resolution structures. We assemble a model of a capped tropomyosin-actin minifilament to demonstrate the utility of combining structures determined by different techniques. Finally, we survey the methods that attempt to transform high resolution structural biology into more physiological environments, such as the cell. Together these techniques promise a compelling decade for structural biology and, more importantly, they will provide exciting discoveries in understanding the designs and purposes of biological machines. © 2018 The Authors. BioEssays Published by WILEY Periodicals, Inc.

Systems biology for molecular life sciences and its impact in biomedicine.

Science.gov (United States)

Medina, Miguel Ángel

2013-03-01

Modern systems biology is already contributing to a radical transformation of molecular life sciences and biomedicine, and it is expected to have a real impact in the clinical setting in the next years. In this review, the emergence of systems biology is contextualized with a historic overview, and its present state is depicted. The present and expected future contribution of systems biology to the development of molecular medicine is underscored. Concerning the present situation, this review includes a reflection on the "inflation" of biological data and the urgent need for tools and procedures to make hidden information emerge. Descriptions of the impact of networks and models and the available resources and tools for applying them in systems biology approaches to molecular medicine are provided as well. The actual current impact of systems biology in molecular medicine is illustrated, reviewing two cases, namely, those of systems pharmacology and cancer systems biology. Finally, some of the expected contributions of systems biology to the immediate future of molecular medicine are commented.

Plant Systems Biology (editorial)

Science.gov (United States)

In June 2003, Plant Physiology published an Arabidopsis special issue devoted to plant systems biology. The intention of Natasha Raikhel and Gloria Coruzzi, the two editors of this first-of-its-kind issue, was ‘‘to help nucleate this new effort within the plant community’’ as they considered that ‘‘...

Center of cancer systems biology second annual workshop--tumor metronomics: timing and dose level dynamics.

Science.gov (United States)

Hahnfeldt, Philip; Hlatky, Lynn; Klement, Giannoula Lakka

2013-05-15

Metronomic chemotherapy, the delivery of doses in a low, regular manner so as to avoid toxic side effects, was introduced over 12 years ago in the face of substantial clinical and preclinical evidence supporting its tumor-suppressive capability. It constituted a marked departure from the classic maximum-tolerated dose (MTD) strategy, which, given its goal of rapid eradication, uses dosing sufficiently intense to require rest periods between cycles to limit toxicity. Even so, upfront tumor eradication is frequently not achieved with MTD, whereupon a de facto goal of longer-term tumor control is often pursued. As metronomic dosing has shown tumor control capability, even for cancers that have become resistant to the same drug delivered under MTD, the question arises whether it may be a preferable alternative dosing approach from the outset. To date, however, our knowledge of the coupled dynamics underlying metronomic dosing is neither sufficiently well developed nor widely enough disseminated to establish its actual potential. Meeting organizers thus felt the time was right, armed with new quantitative approaches, to call a workshop on "Tumor Metronomics: Timing and Dose Level Dynamics" to explore prospects for gaining a deeper, systems-level appreciation of the metronomics concept. The workshop proved to be a forum in which experts from the clinical, biologic, mathematical, and computational realms could work together to clarify the principles and underpinnings of metronomics. Among other things, the need for significant shifts in thinking regarding endpoints to be used as clinical standards of therapeutic progress was recognized. ©2013 AACR.

A graphical method for reducing and relating models in systems biology.

Science.gov (United States)

Gay, Steven; Soliman, Sylvain; Fages, François

2010-09-15

In Systems Biology, an increasing collection of models of various biological processes is currently developed and made available in publicly accessible repositories, such as biomodels.net for instance, through common exchange formats such as SBML. To date, however, there is no general method to relate different models to each other by abstraction or reduction relationships, and this task is left to the modeler for re-using and coupling models. In mathematical biology, model reduction techniques have been studied for a long time, mainly in the case where a model exhibits different time scales, or different spatial phases, which can be analyzed separately. These techniques are however far too restrictive to be applied on a large scale in systems biology, and do not take into account abstractions other than time or phase decompositions. Our purpose here is to propose a general computational method for relating models together, by considering primarily the structure of the interactions and abstracting from their dynamics in a first step. We present a graph-theoretic formalism with node merge and delete operations, in which model reductions can be studied as graph matching problems. From this setting, we derive an algorithm for deciding whether there exists a reduction from one model to another, and evaluate it on the computation of the reduction relations between all SBML models of the biomodels.net repository. In particular, in the case of the numerous models of MAPK signalling, and of the circadian clock, biologically meaningful mappings between models of each class are automatically inferred from the structure of the interactions. We conclude on the generality of our graphical method, on its limits with respect to the representation of the structure of the interactions in SBML, and on some perspectives for dealing with the dynamics. The algorithms described in this article are implemented in the open-source software modeling platform BIOCHAM available at http

Systems biology solutions for biochemical production challenges.

Science.gov (United States)

Hansen, Anne Sofie Lærke; Lennen, Rebecca M; Sonnenschein, Nikolaus; Herrgård, Markus J

2017-06-01

There is an urgent need to significantly accelerate the development of microbial cell factories to produce fuels and chemicals from renewable feedstocks in order to facilitate the transition to a biobased society. Methods commonly used within the field of systems biology including omics characterization, genome-scale metabolic modeling, and adaptive laboratory evolution can be readily deployed in metabolic engineering projects. However, high performance strains usually carry tens of genetic modifications and need to operate in challenging environmental conditions. This additional complexity compared to basic science research requires pushing systems biology strategies to their limits and often spurs innovative developments that benefit fields outside metabolic engineering. Here we survey recent advanced applications of systems biology methods in engineering microbial production strains for biofuels and -chemicals. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

GPSR: A Resource for Genomics Proteomics and Systems Biology

Indian Academy of Sciences (India)

GPSR: A Resource for Genomics Proteomics and Systems Biology · Simple Calculation Programs for Biology Immunological Methods · Simple Calculation Programs for Biology Methods in Molecular Biology · Simple Calculation Programs for Biology Other Methods · PowerPoint Presentation · Slide 6 · Slide 7 · Prediction of ...

Dietary antioxidant synergy in chemical and biological systems.

Science.gov (United States)

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.

Systems Biology for Mapping Genotype-Phenotype Relations in Yeast

KAUST Repository

Nielsen, Jens

2016-01-25

The yeast Saccharomyces cerevisiae is widely used for production of fuels, chemicals, pharmaceuticals and materials. Through metabolic engineering of this yeast a number of novel new industrial processes have been developed over the last 10 years. Besides its wide industrial use, S. cerevisiae serves as an eukaryal model organism, and many systems biology tools have therefore been developed for this organism. Among these genome-scale metabolic models have shown to be most successful as they easy integrate with omics data and at the same time have been shown to have excellent predictive power. Despite our extensive knowledge of yeast metabolism and its regulation we are still facing challenges when we want to engineer complex traits, such as improved tolerance to toxic metabolites like butanol and elevated temperatures or when we want to engineer the highly complex protein secretory pathway. In this presentation it will be demonstrated how we can combine directed evolution with systems biology analysis to identify novel targets for rational design-build-test of yeast strains that have improved phenotypic properties. In this lecture an overview of systems biology of yeast will be presented together with examples of how genome-scale metabolic modeling can be used for prediction of cellular growth at different conditions. Examples will also be given on how adaptive laboratory evolution can be used for identifying targets for improving tolerance towards butanol, increased temperature and low pH and for improving secretion of heterologous proteins.

It's the System, Stupid: How Systems Biology Is Transforming.

Science.gov (United States)

2010-01-01

So far, little is known about systems biology and its potential for changing how we diagnose and treat disease. That will change soon, say the systems experts, who advise payers to begin learning now about how it could make healthcare efficient.

Seasonal allergic rhinitis and systems biology-oriented biomarker discovery

NARCIS (Netherlands)

Baars, E.W.; Nierop, A.F.M.; Savelkoul, H.F.J.

2015-01-01

There is an increasing interest in science and medicine in the systems approach. Instead of the reductionist approach that focuses on the physical and chemical properties of the individual components, systems biology aims to describe, understand, and explain from the complex biological systems

Systems biology technologies enable personalized traditional Chinese medicine: a systematic review.

Science.gov (United States)

Wang, Xijun; Zhang, Aihua; Sun, Hui; Wang, Ping

2012-01-01

Traditional Chinese medicine (TCM), an alternative medicine, focuses on the treatment of human disease via the integrity of the close relationship between body and syndrome analysis. It remains a form of primary care in most Asian countries and its characteristics showcase the great advantages of personalized medicine. Although this approach to disease diagnosis, prognosis and treatment has served the medical establishment well for thousands of years, it has serious shortcomings in the era of modern medicine that stem from its reliance on reductionist principles of experimentation and analysis. In this way, systems biology offers the potential to personalize medicine, facilitating the provision of the right care to the right patient at the right time. We expect that systems biology will have a major impact on future personalized therapeutic approaches which herald the future of medicine. Here we summarize current trends and critically review the potential limitations and future prospects of such treatments. Some characteristic examples are presented to highlight the application of this groundbreaking platform to personalized TCM as well as some of the necessary milestones for moving systems biology of a state-of-the-art nature into mainstream health care.

Tracing organizing principles: Learning from the history of systems biology

DEFF Research Database (Denmark)

Green, Sara; Wolkenhauer, Olaf

2014-01-01

on this historical background in order to increase the understanding of the motivation behind the search for general principles and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational......With the emergence of systems biology, the identification of organizing principles is being highlighted as a key research aim. Researchers attempt to “reverse engineer” the functional organization of biological systems using methodologies from mathematics, engineering and computer science while...... taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-twentieth century. The aim of this paper is to draw...

An online model composition tool for system biology models.

Science.gov (United States)

Coskun, Sarp A; Cicek, A Ercument; Lai, Nicola; Dash, Ranjan K; Ozsoyoglu, Z Meral; Ozsoyoglu, Gultekin

2013-09-05

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. 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. 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.

SEEK: a systems biology data and model management platform.

Science.gov (United States)

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

Genome Scale Modeling in Systems Biology: Algorithms and Resources

Science.gov (United States)

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

Systems Biology Knowledgebase for a New Era in Biology A Genomics:GTL Report from the May 2008 Workshop

Energy Technology Data Exchange (ETDEWEB)

Gregurick, S.; Fredrickson, J. K.; Stevens, R.

2009-03-01

Biology has entered a systems-science era with the goal to establish a predictive understanding of the mechanisms of cellular function and the interactions of biological systems with their environment and with each other. Vast amounts of data on the composition, physiology, and function of complex biological systems and their natural environments are emerging from new analytical technologies. Effectively exploiting these data requires developing a new generation of capabilities for analyzing and managing the information. By revealing the core principles and processes conserved in collective genomes across all biology and by enabling insights into the interplay between an organism's genotype and its environment, systems biology will allow scientific breakthroughs in our ability to project behaviors of natural systems and to manipulate and engineer managed systems. These breakthroughs will benefit Department of Energy (DOE) missions in energy security, climate protection, and environmental remediation.

Scaffolded biology.

Science.gov (United States)

Minelli, Alessandro

2016-09-01

Descriptions and interpretations of the natural world are dominated by dichotomies such as organism vs. environment, nature vs. nurture, genetic vs. epigenetic, but in the last couple of decades strong dissatisfaction with those partitions has been repeatedly voiced and a number of alternative perspectives have been suggested, from perspectives such as Dawkins' extended phenotype, Turner's extended organism, Oyama's Developmental Systems Theory and Odling-Smee's niche construction theory. Last in time is the description of biological phenomena in terms of hybrids between an organism (scaffolded system) and a living or non-living scaffold, forming unit systems to study processes such as reproduction and development. As scaffold, eventually, we can define any resource used by the biological system, especially in development and reproduction, without incorporating it as happens in the case of resources fueling metabolism. Addressing biological systems as functionally scaffolded systems may help pointing to functional relationships that can impart temporal marking to the developmental process and thus explain its irreversibility; revisiting the boundary between development and metabolism and also regeneration phenomena, by suggesting a conceptual framework within which to investigate phenomena of regular hypermorphic regeneration such as characteristic of deer antlers; fixing a periodization of development in terms of the times at which a scaffolding relationship begins or is terminated; and promoting plant galls to legitimate study objects of developmental biology.

Hydrogen production from biomass by biological systems

International Nuclear Information System (INIS)

Sharifan, H.R.; Qader, S.

2009-01-01

Hydrogen gas is seen as a future energy carrier, not involved in 'greenhouse' gas and its released energy in combustion can be converted to electric power. Biological system with low energy can produce hydrogen compared to electrochemical hydrogen production via solar battery-based water splitting which requires the use of solar batteries with high energy requirements. The biological hydrogen production occurs in microalgae and cyanobacteria by photosynthesis. They consume biochemical energy to produce molecular hydrogen. Hydrogen in some algae is an anaerobic production in the absence of light. In cyanobacteria the hydrogen production simultaneously happens with nitrogen fixation, and also catalyzed by nitrogenase as a side reaction. Hydrogen production by photosynthetic bacteria is mediated by nitrogenase activity, although hydrogenases may be active for both hydrogen production and hydrogen uptake under some conditions. Genetic studies on photosynthetic microorganisms have markedly increased in recent times, relatively few genetic engineering studies have focused on altering the characteristics of these microorganisms, particularly with respect to enhancing the hydrogen-producing capabilities of photosynthetic bacteria and cyanobacteria. (author)

Exploring Synthetic and Systems Biology at the University of Edinburgh.

Science.gov (United States)

Fletcher, Liz; Rosser, Susan; Elfick, Alistair

2016-06-15

The Centre for Synthetic and Systems Biology ('SynthSys') was originally established in 2007 as the Centre for Integrative Systems Biology, funded by the Biotechnology and Biological Sciences Research Council (BBSRC) and the Engineering and Physical Sciences Research Council (EPSRC). Today, SynthSys embraces an extensive multidisciplinary community of more than 200 researchers from across the University with a common interest in synthetic and systems biology. Our research is broad and deep, addressing a diversity of scientific questions, with wide ranging impact. We bring together the power of synthetic biology and systems approaches to focus on three core thematic areas: industrial biotechnology, agriculture and the environment, and medicine and healthcare. In October 2015, we opened a newly refurbished building as a physical hub for our new U.K. Centre for Mammalian Synthetic Biology funded by the BBSRC/EPSRC/MRC as part of the U.K. Research Councils' Synthetic Biology for Growth programme. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

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

Science.gov (United States)

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).

Physics and biology

International Nuclear Information System (INIS)

Frauenfelder, H.

1988-01-01

The author points out that the coupling between physics and biology is becoming closer as time goes on. He tries to show that physical studies on biological systems not only yield insight into biology but also provide results of interest to physics. Biological systems are extremly complex system. Ideally one would like to understand the behavior of such systems in terms of the behavior of its constituent atoms. Since in small organisms this may be 10 20 atoms, it is clear these are not simple many-body systems. He reviews the basic elements of cells and then considers the broader questions of structure, complexity, and function, which must be looked at on levels from the cell to the organism. Despite the vast amount of observational material already in existence, biophysics and biological physics are only at a beginning. We can expect that physics will continue to interact strongly with biology. Actually, the connection also includes chemistry and mathematics. New tools that become available in physics will continue to be applied to biological problems. We can expect that the flow of information will not be one way; biological systems will provide new information on many old and new parts of physics, from reaction theory and transport phenomena to complexity, cooperativity, and nonlinear processes

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

Science.gov (United States)

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

SEEK: a systems biology data and model management platform.

NARCIS (Netherlands)

Wolstencroft, K.J.; Owen, S.; Krebs, O.; Nguyen, Q.; Stanford, N.J.; Golebiewski, M.; Weidemann, A.; Bittkowski, M.; An, L.; Shockley, D.; Snoep, J.L.; Mueller, W.; Goble, C.

2015-01-01

Background: 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

A high-resolution mini-microscope system for wireless real-time monitoring.

Science.gov (United States)

Wang, Zongjie; Boddeda, Akash; Parker, Benjamin; Samanipour, Roya; Ghosh, Sanjoy; Menard, Frederic; Kim, Keekyoung

2017-09-04

Compact, cost-effective and high-performance microscope that enables the real-time imaging of cells and lab-on-a-chip devices is highly demanded for cell biology and biomedical engineering. This paper aims to present the design and application of an inexpensive wireless mini-microscope with resolution up to 2592 × 1944 pixels and speed up to 90 fps. The mini-microscope system was built on a commercial embedded system (Raspberry Pi). We modified a camera module and adopted an inverse dual lens system to obtain the clear field of view and appropriate magnification for tens of micrometer objects. The system was capable of capturing time-lapse images and transferring image data wirelessly. The entire system can be operated wirelessly and cordlessly in a conventional cell culturing incubator. The developed mini-microscope was used to monitor the attachment and proliferation of NIH-3T3 and HEK 293 cells inside an incubator for 50 hours. In addition, the mini-microscope was used to monitor a droplet generation process in a microfluidic device. The high-quality images captured by the mini-microscope enabled us an automated analysis of experimental parameters. The successful applications prove the great potential of the developed mini-microscope for monitoring various biological samples and microfluidic devices. This paper presents the design of a high resolution mini-microscope system that enables the wireless real-time imaging of cells inside the incubator. This system has been verified to be a useful tool to obtain high-quality images and videos for the automated quantitative analysis of biological samples and lab-on-a-chip devices in the long term.

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Tunable promoters in systems biology

DEFF Research Database (Denmark)

Mijakovic, Ivan; Petranovic, Dina; Jensen, Peter Ruhdal

2005-01-01

The construction of synthetic promoter libraries has represented a major breakthrough in systems biology, enabling the subtle tuning of enzyme activities. A number of tools are now available that allow the modulation of gene expression and the detection of changes in expression patterns. But, how...

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

Science.gov (United States)

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.

Complex biological and bio-inspired systems

Energy Technology Data Exchange (ETDEWEB)

Ecke, Robert E [Los Alamos National Laboratory

2009-01-01

The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to

A study for the biological CO2 fixation and utilization system

International Nuclear Information System (INIS)

Otsuki, T.

2001-01-01

Increased CO 2 in the atmosphere is such a serious problem for mankind that many research and development approaches are implemented to reduce CO 2 emissions. One is a biological CO 2 fixation using the photosynthetic function of microalgae like Chlorella and Synechocystis sp. The target of the project is to achieve a CO 2 fixation rate of 50 g CO 2 /m 2 ·d, which is 10 times as large as that of the temperate forest. The purpose of this study is to clarify the possibilities of the biological CO 2 fixation system in view of the CO 2 balance, energy balance, and payback period. The amount of CO 2 fixation of the system should be larger than the emission of CO 2 by operating. Furthermore, the energy consumption of the system should also be less than the biochemical energy (enthalpy) of glucose, which is made by photosynthesis. After CO 2 fixation was completed by the microalgae, the biomass must be utilized practically for many markets and the initial investment in the system construction could be regained

Heavy-ion microbeam system at JAEA-Takasaki for microbeam biology

International Nuclear Information System (INIS)

Funayama, Tomoo; Wada, Seiichi; Yokota, Yuichiro

2008-01-01

Research concerning cellular responses to low dose irradiation, radiation-induced bystander effects, and the biological track structure of charged particles has recently received particular attention in the field of radiation biology. Target irradiation employing a microbeam represents a useful means of advancing this research by obviating some of the disadvantages associated with the conventional irradiation strategies. The heavy-ion microbeam system at Japan Atomic Energy Agency (JAEA)-Takasaki, which was planned in 1987 and started in the early 1990's, can provide target irradiation of heavy charged particles to biological material at atmospheric pressure using a minimum beam size 5 μm in diameter. A variety of biological material has been irradiated using this microbeam system including cultured mammalian and higher plant cells, isolated fibers of mouse skeletal muscle, silkworm (Bombyx mori) embryos and larvae, Arabidopsis thaliana roots, and the nematode Caenorhabditis elegans. The system can be applied to the investigation of mechanisms within biological organisms not only in the context of radiation biology, but also in the fields of general biology such as physiology, developmental biology and neurobiology, and should help to establish and contribute to the field of 'microbeam biology'. (author)

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

Science.gov (United States)

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 Graphical Notation: Entity Relationship language Level 1 Version 2

Directory of Open Access Journals (Sweden)

Sorokin Anatoly

2015-06-01

Full Text Available The Systems Biological Graphical Notation (SBGN is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD, Entity Relationship (ER and Activity Flow (AF, allow for the representation of different aspects of biological and biochemical systems at different levels of detail.

Impact of systems biology on metabolic engineering of Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Nielsen, Jens; Jewett, Michael Christopher

2008-01-01

in the industrial application of this yeast. Developments in genomics and high-throughput systems biology tools are enhancing one's ability to rapidly characterize cellular behaviour, which is valuable in the field of metabolic engineering where strain characterization is often the bottleneck in strain development...... programmes. Here, the impact of systems biology on metabolic engineering is reviewed and perspectives on the role of systems biology in the design of cell factories are given....

Efficient Bayesian estimates for discrimination among topologically different systems biology models.

Science.gov (United States)

Hagen, David R; Tidor, Bruce

2015-02-01

A major effort in systems biology is the development of mathematical models that describe complex biological systems at multiple scales and levels of abstraction. Determining the topology-the set of interactions-of a biological system from observations of the system's behavior is an important and difficult problem. Here we present and demonstrate new methodology for efficiently computing the probability distribution over a set of topologies based on consistency with existing measurements. Key features of the new approach include derivation in a Bayesian framework, incorporation of prior probability distributions of topologies and parameters, and use of an analytically integrable linearization based on the Fisher information matrix that is responsible for large gains in efficiency. The new method was demonstrated on a collection of four biological topologies representing a kinase and phosphatase that operate in opposition to each other with either processive or distributive kinetics, giving 8-12 parameters for each topology. The linearization produced an approximate result very rapidly (CPU minutes) that was highly accurate on its own, as compared to a Monte Carlo method guaranteed to converge to the correct answer but at greater cost (CPU weeks). The Monte Carlo method developed and applied here used the linearization method as a starting point and importance sampling to approach the Bayesian answer in acceptable time. Other inexpensive methods to estimate probabilities produced poor approximations for this system, with likelihood estimation showing its well-known bias toward topologies with more parameters and the Akaike and Schwarz Information Criteria showing a strong bias toward topologies with fewer parameters. These results suggest that this linear approximation may be an effective compromise, providing an answer whose accuracy is near the true Bayesian answer, but at a cost near the common heuristics.

EURASIP journal on bioinformatics & systems biology

National Research Council Canada - National Science Library

2006-01-01

"The overall aim of "EURASIP Journal on Bioinformatics and Systems Biology" is to publish research results related to signal processing and bioinformatics theories and techniques relevant to a wide...

Agent-Based Modeling in Molecular Systems Biology.

Science.gov (United States)

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-06-08

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.

Marine biological data and information management system

Digital Repository Service at National Institute of Oceanography (India)

Sarupria, J.S.

Indian National Oceanographic Data Centre (INODC) is engaged in developing a marine biological data and information management system (BIODIMS). This system will contain the information on zooplankton in the water column, zoobenthic biomass...

Complex Time-Delay Systems Theory and Applications

CERN Document Server

Atay, Fatihcan M

2010-01-01

Time delays in dynamical systems arise as an inevitable consequence of finite speeds of information transmission. Realistic models increasingly demand the inclusion of delays in order to properly understand, analyze, design, and control real-life systems. The goal of this book is to present the state-of-the-art in research on time-delay dynamics in the framework of complex systems and networks. While the mathematical theory of delay equations is quite mature, its application to the particular problems of complex systems and complexity is a newly emerging field, and the present volume aims to play a pioneering role in this perspective. The chapters in this volume are authored by renowned experts and cover both theory and applications in a wide range of fields, with examples extending from neuroscience and biology to laser physics and vehicle traffic. Furthermore, all chapters include sufficient introductory material and extensive bibliographies, making the book a self-contained reference for both students and ...

Carbon nanomaterials in biological systems

Energy Technology Data Exchange (ETDEWEB)

Pu Chun Ke [Laboratory of Single-Molecule Biophysics and Polymer Physics, Department of Physics and Astronomy, Clemson University, Clemson, SC 29634 (United States); Qiao Rui [Department of Mechanical Engineering, Clemson University, Clemson, SC 29634 (United States)

2007-09-19

This paper intends to reflect, from the biophysical viewpoint, our current understanding on interfacing nanomaterials, such as carbon nanotubes and fullerenes, with biological systems. Strategies for improving the solubility, and therefore, the bioavailability of nanomaterials in aqueous solutions are summarized. In particular, the underlining mechanisms of attaching biomacromolecules (DNA, RNA, proteins) and lysophospholipids onto carbon nanotubes and gallic acids onto fullerenes are analyzed. The diffusion and the cellular delivery of RNA-coated carbon nanotubes are characterized using fluorescence microscopy. The translocation of fullerenes across cell membranes is simulated using molecular dynamics to offer new insight into the complex issue of nanotoxicity. To assess the fate of nanomaterials in the environment, the biomodification of lipid-coated carbon nanotubes by the aquatic organism Daphnia magna is discussed. The aim of this paper is to illuminate the need for adopting multidisciplinary approaches in the field study of nanomaterials in biological systems and in the environment. (topical review)

Carbon nanomaterials in biological systems

International Nuclear Information System (INIS)

Pu Chun Ke; Qiao Rui

2007-01-01

This paper intends to reflect, from the biophysical viewpoint, our current understanding on interfacing nanomaterials, such as carbon nanotubes and fullerenes, with biological systems. Strategies for improving the solubility, and therefore, the bioavailability of nanomaterials in aqueous solutions are summarized. In particular, the underlining mechanisms of attaching biomacromolecules (DNA, RNA, proteins) and lysophospholipids onto carbon nanotubes and gallic acids onto fullerenes are analyzed. The diffusion and the cellular delivery of RNA-coated carbon nanotubes are characterized using fluorescence microscopy. The translocation of fullerenes across cell membranes is simulated using molecular dynamics to offer new insight into the complex issue of nanotoxicity. To assess the fate of nanomaterials in the environment, the biomodification of lipid-coated carbon nanotubes by the aquatic organism Daphnia magna is discussed. The aim of this paper is to illuminate the need for adopting multidisciplinary approaches in the field study of nanomaterials in biological systems and in the environment. (topical review)

Quantitative computational models of molecular self-assembly in systems biology.

Science.gov (United States)

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Drawing inspiration from biological optical systems

Science.gov (United States)

Wolpert, H. D.

2009-08-01

Bio-Mimicking/Bio-Inspiration: How can we not be inspired by Nature? Life has evolved on earth over the last 3.5 to 4 billion years. Materials formed during this time were not toxic; they were created at low temperatures and low pressures unlike many of the materials developed today. The natural materials formed are self-assembled, multifunctional, nonlinear, complex, adaptive, self-repairing and biodegradable. The designs that failed are fossils. Those that survived are the success stories. Natural materials are mostly formed from organics, inorganic crystals and amorphous phases. The materials make economic sense by optimizing the design of the structures or systems to meet multiple needs. We constantly "see" many similar strategies in approaches, between man and nature, but we seldom look at the details of natures approaches. The power of image processing, in many of natures creatures, is a detail that is often overlooked. Seldon does the engineer interact with the biologist and learn what nature has to teach us. The variety and complexity of biological materials and the optical systems formed should inspire us.

Vibrational resonances in biological systems at microwave frequencies.

Science.gov (United States)

Adair, Robert K

2002-03-01

Many biological systems can be expected to exhibit resonance behavior involving the mechanical vibration of system elements. The natural frequencies of such resonances will, generally, be in the microwave frequency range. Some of these systems will be coupled to the electromagnetic field by the charge distributions they carry, thus admitting the possibility that microwave exposures may generate physiological effects in man and other species. However, such microwave excitable resonances are expected to be strongly damped by interaction with their aqueous biological environment. Although those dissipation mechanisms have been studied, the limitations on energy transfers that follow from the limited coupling of these resonances to the electromagnetic field have not generally been considered. We show that this coupling must generally be very small and thus the absorbed energy is so strongly limited that such resonances cannot affect biology significantly even if the systems are much less strongly damped than expected from basic dissipation models.

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

Energy Technology Data Exchange (ETDEWEB)

Aderem, Alan; Adkins, Joshua N.; Ansong, Charles; Galagan, James; Kaiser, Shari; Korth, Marcus J.; Law, G. L.; McDermott, Jason E.; Proll, Sean; Rosenberger, Carrie; Schoolnik, Gary; Katze, Michael G.

2011-02-01

The 20th century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and water borne illnesses are frequent, multi-drug resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the 21st century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program we think that the time is at hand to redefine the pathogen-host research paradigm.

Dielectric relaxation in biological systems physical principles, methods, and applications

CERN Document Server

Feldman, Yuri

2015-01-01

This title covers the theoretical basis and practical aspects of the study of dielectric properties of biological systems, such as water, electrolyte and polyelectrolytes, solutions of biological macromolecules, cells suspensions and cellular systems.

Systems-biology dissection of eukaryotic cell growth

Directory of Open Access Journals (Sweden)

Andrews Justen

2010-05-01

Full Text Available Abstract A recent article in BMC Biology illustrates the use of a systems-biology approach to integrate data across the transcriptome, proteome and metabolome of budding yeast in order to dissect the relationship between nutrient conditions and cell growth. See research article http://jbiol.com/content/6/2/4 and http://www.biomedcentral.com/1741-7007/8/68

It’s the System, Stupid: How Systems Biology Is Transforming

Science.gov (United States)

2010-01-01

So far, little is known about systems biology and its potential for changing how we diagnose and treat disease. That will change soon, say the systems experts, who advise payers to begin learning now about how it could make healthcare efficient. PMID:22478806

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

Science.gov (United States)

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.

A dedicated database system for handling multi-level data in systems biology

OpenAIRE

Pornputtapong, Natapol; Wanichthanarak, Kwanjeera; Nilsson, Avlant; Nookaew, Intawat; Nielsen, Jens

2014-01-01

Background Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging...

Single molecule tools for enzymology, structural biology, systems biology and nanotechnology: an update

Science.gov (United States)

Widom, Julia R.; Dhakal, Soma; Heinicke, Laurie A.; Walter, Nils G.

2015-01-01

Toxicology is the highly interdisciplinary field studying the adverse effects of chemicals on living organisms. It requires sensitive tools to detect such effects. After their initial implementation during the 1990s, single-molecule fluorescence detection tools were quickly recognized for their potential to contribute greatly to many different areas of scientific inquiry. In the intervening time, technical advances in the field have generated ever-improving spatial and temporal resolution, and have enabled the application of single-molecule fluorescence to increasingly complex systems, such as live cells. In this review, we give an overview of the optical components necessary to implement the most common versions of single-molecule fluorescence detection. We then discuss current applications to enzymology and structural studies, systems biology, and nanotechnology, presenting the technical considerations that are unique to each area of study, along with noteworthy recent results. We also highlight future directions that have the potential to revolutionize these areas of study by further exploiting the capabilities of single-molecule fluorescence microscopy. PMID:25212907

Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2.

Science.gov (United States)

Sorokin, Anatoly; Le Novère, Nicolas; Luna, Augustin; Czauderna, Tobias; Demir, Emek; Haw, Robin; Mi, Huaiyu; Moodie, Stuart; Schreiber, Falk; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Systems Biology of Saccharomyces cerevisiae Physiology and its DNA Damage Response

DEFF Research Database (Denmark)

Fazio, Alessandro

The yeast Saccharomyces cerevisiae is a model organism in biology, being widely used in fundamental research, the first eukaryotic organism to be fully sequenced and the platform for the development of many genomics techniques. Therefore, it is not surprising that S. cerevisiae has also been widely...... used in the field of systems biology during the last decade. This thesis investigates S. cerevisiae growth physiology and DNA damage response by using a systems biology approach. Elucidation of the relationship between growth rate and gene expression is important to understand the mechanisms regulating...... set of growth dependent genes by using a multi-factorial experimental design. Moreover, new insights into the metabolic response and transcriptional regulation of these genes have been provided by using systems biology tools (Chapter 3). One of the prerequisite of systems biology should...

Biological optimization systems for enhancing photosynthetic efficiency and methods of use

Science.gov (United States)

Hunt, Ryan W.; Chinnasamy, Senthil; Das, Keshav C.; de Mattos, Erico Rolim

2012-11-06

Biological optimization systems for enhancing photosynthetic efficiency and methods of use. Specifically, methods for enhancing photosynthetic efficiency including applying pulsed light to a photosynthetic organism, using a chlorophyll fluorescence feedback control system to determine one or more photosynthetic efficiency parameters, and adjusting one or more of the photosynthetic efficiency parameters to drive the photosynthesis by the delivery of an amount of light to optimize light absorption of the photosynthetic organism while providing enough dark time between light pulses to prevent oversaturation of the chlorophyll reaction centers are disclosed.

A Biological Perspective on the Meaning of Time

Science.gov (United States)

Rothschild, Lynn J.

2014-01-01

We have become impatient waiting for a web page to load, but the first member of our species evolved about 150,000 years ago - a geological instant as brief and as transitory as a text message. The shortest generation time of a bacterium is a sprint at under ten minutes, whereas a 200-year old whale, turtle or tree is not unknown. Life is a phenomenon that integrates processes ranging from the near instantaneous reactions of photosynthesis to the more stately pace of evolution. Here I will elucidate these processes with radically different time scales that go to creating and maintaining the diversity of life on earth, the clocks that nature uses to time them, and how modern biology is being used to alter the natural time scales.

PathSys: integrating molecular interaction graphs for systems biology

Directory of Open Access Journals (Sweden)

Raval Alpan

2006-02-01

Full Text Available Abstract Background The goal of information integration in systems biology is to combine information from a number of databases and data sets, which are obtained from both high and low throughput experiments, under one data management scheme such that the cumulative information provides greater biological insight than is possible with individual information sources considered separately. Results Here we present PathSys, a graph-based system for creating a combined database of networks of interaction for generating integrated view of biological mechanisms. We used PathSys to integrate over 14 curated and publicly contributed data sources for the budding yeast (S. cerevisiae and Gene Ontology. A number of exploratory questions were formulated as a combination of relational and graph-based queries to the integrated database. Thus, PathSys is a general-purpose, scalable, graph-data warehouse of biological information, complete with a graph manipulation and a query language, a storage mechanism and a generic data-importing mechanism through schema-mapping. Conclusion Results from several test studies demonstrate the effectiveness of the approach in retrieving biologically interesting relations between genes and proteins, the networks connecting them, and of the utility of PathSys as a scalable graph-based warehouse for interaction-network integration and a hypothesis generator system. The PathSys's client software, named BiologicalNetworks, developed for navigation and analyses of molecular networks, is available as a Java Web Start application at http://brak.sdsc.edu/pub/BiologicalNetworks.

Echinococcus as a model system: biology and epidemiology.

Science.gov (United States)

Thompson, R C A; Jenkins, D J

2014-10-15

The introduction of Echinococcus to Australia over 200 years ago and its establishment in sheep rearing areas of the country inflicted a serious medical and economic burden on the country. This resulted in an investment in both basic and applied research aimed at learning more about the biology and life cycle of Echinococcus. This research served to illustrate the uniqueness of the parasite in terms of developmental biology and ecology, and the value of Echinococcus as a model system in a broad range of research, from fundamental biology to theoretical control systems. These studies formed the foundation for an international, diverse and ongoing research effort on the hydatid organisms encompassing stem cell biology, gene regulation, strain variation, wildlife diseases and models of transmission dynamics. We describe the development, nature and diversity of this research, and how it was initiated in Australia but subsequently has stimulated much international and collaborative research on Echinococcus. Copyright © 2014 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Thermostability of biological systems: fundamentals, challenges, and quantification.

Science.gov (United States)

He, Xiaoming

2011-01-01

This review examines the fundamentals and challenges in engineering/understanding the thermostability of biological systems over a wide temperature range (from the cryogenic to hyperthermic regimen). Applications of the bio-thermostability engineering to either destroy unwanted or stabilize useful biologicals for the treatment of diseases in modern medicine are first introduced. Studies on the biological responses to cryogenic and hyperthermic temperatures for the various applications are reviewed to understand the mechanism of thermal (both cryo and hyperthermic) injury and its quantification at the molecular, cellular and tissue/organ levels. Methods for quantifying the thermophysical processes of the various applications are then summarized accounting for the effect of blood perfusion, metabolism, water transport across cell plasma membrane, and phase transition (both equilibrium and non-equilibrium such as ice formation and glass transition) of water. The review concludes with a summary of the status quo and future perspectives in engineering the thermostability of biological systems.

A data integration approach for cell cycle analysis oriented to model simulation in systems biology

Directory of Open Access Journals (Sweden)

Mosca Ettore

2007-08-01

Full Text Available Abstract Background The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. Description In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. Conclusion This integrated system is freely available in order to support systems biology research on the cell cycle and

Carbon-13 NMR spectroscopy of biological systems

CERN Document Server

Beckmann, Nicolau

1995-01-01

This book is intended to provide an in-depth understanding of 13C NMR as a tool in biological research. 13C NMR has provided unique information concerning complex biological systems, from proteins and nucleic acids to animals and humans. The subjects addressed include multidimensional heteronuclear techniques for structural studies of molecules in the liquid and solid states, the investigation of interactions in model membranes, the elucidation of metabolic pathwaysin vitro and in vivo on animals, and noninvasive metabolic studies performed on humans. The book is a unique mix of NMR methods and biological applications which makes it a convenient reference for those interested in research in this interdisciplinary area of physics, chemistry, biology, and medicine.Key Features* An interdisciplinary text with emphasis on both 13C NMR methodology and the relevant biological and biomedical issues* State-of-the-art 13C NMR techniques are described; Whenever possible, their advantages over other approaches are empha...

An Augmented γ-Spray System to Visualize Biological Effects for Human Body

Science.gov (United States)

Manabe, Seiya; Tenzou, Hideki; Kasuga, Takaaki; Iwakura, Yukiko; Johnston, Robert

2017-09-01

The purpose of this study was to develop a new educational system with an easy-to-use interface in order to support comprehension of the biological effects of radiation on the human body within a short period of time. A paint spray-gun was used as a gamma rays source mock-up for the system. The application screen shows the figure of a human body for radiation deposition using the γ-Sprayer, a virtual radiation source, as well as equivalent dosage and a panel for setting the irradiation conditions. While the learner stands in front of the PC monitor, the virtual radiation source is used to deposit radiation on the graphic of the human body that is displayed. Tissue damage is calculated using an interpolation method from the data calculated by the PHITS simulation code in advance while the learner is pulling the trigger with respect to the irradiation time, incident position, and distance from the screen. It was confirmed that the damage was well represented by the interpolation method. The augmented ?-Spray system was assessed by questionnaire. Pre-post questionnaire was taken for our 41 students in National Institute of Technology, Kagawa College. It was also confirmed that the system has a capability of teaching the basic radiation protection concept, quantitative feeling of the radiation dose, and the biological effects

Fiber laser-microscope system for femtosecond photodisruption of biological samples.

Science.gov (United States)

Yavaş, Seydi; Erdogan, Mutlu; Gürel, Kutan; Ilday, F Ömer; Eldeniz, Y Burak; Tazebay, Uygar H

2012-03-01

We report on the development of a ultrafast fiber laser-microscope system for femtosecond photodisruption of biological targets. A mode-locked Yb-fiber laser oscillator generates few-nJ pulses at 32.7 MHz repetition rate, amplified up to ∼125 nJ at 1030 nm. Following dechirping in a grating compressor, ∼240 fs-long pulses are delivered to the sample through a diffraction-limited microscope, which allows real-time imaging and control. The laser can generate arbitrary pulse patterns, formed by two acousto-optic modulators (AOM) controlled by a custom-developed field-programmable gate array (FPGA) controller. This capability opens the route to fine optimization of the ablation processes and management of thermal effects. Sample position, exposure time and imaging are all computerized. The capability of the system to perform femtosecond photodisruption is demonstrated through experiments on tissue and individual cells.

Multilayer microfluidic systems with indium-tin-oxide microelectrodes for studying biological cells

International Nuclear Information System (INIS)

Wu, Hsiang-Chiu; Chen, Hsin; Lyau, Jia-Bo; Lin, Min-Hsuan; Chuang, Yung-Jen

2017-01-01

Contemporary semiconductor and micromachining technologies have been exploited to develop lab-on-a-chip microsystems, which enable parallel and efficient experiments in molecular and cellular biology. In these microlab systems, microfluidics play an important role for automatic transportation or immobilization of cells and bio-molecules, as well as for separation or mixing of different chemical reagents. However, seldom microlab systems allow both morphology and electrophysiology of biological cells to be studied in situ . This kind of study is important, for example, for understanding how neuronal networks grow in response to environmental stimuli. To fulfill this application need, this paper investigates the possibility of fabricating multi-layer photoresists as microfluidic systems directly above a glass substrate with indium-tin-oxide (ITO) electrodes. The microfluidic channels are designed to guide and trap biological cells on top of ITO electrodes, through which the electrical activities of cells can be recorded or elicited. As both the microfluidic system and ITO electrodes are transparent, the cellular morphology is observable easily during electrophysiological studies. Two fabrication processes are proposed and compared. One defines the structure and curing depth of each photoresist layer simply by controlling the exposure time in lithography, while the other further utilizes a sacrificial layer to defines the structure of the bottom layer. The fabricated microfluidic system is proved bio-compatible and able to trap blood cells or neurons. Therefore, the proposed microsystem will be useful for studying cultured cells efficiently in applications such as drug-screening. (paper)

Anion binding in biological systems

Energy Technology Data Exchange (ETDEWEB)

Feiters, Martin C [Department of Organic Chemistry, Institute for Molecules and Materials, Faculty of Science, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen (Netherlands); Meyer-Klaucke, Wolfram [EMBL Hamburg Outstation at DESY, Notkestrasse 85, D-22607 Hamburg (Germany); Kostenko, Alexander V; Soldatov, Alexander V [Faculty of Physics, Southern Federal University, Sorge 5, Rostov-na-Donu, 344090 (Russian Federation); Leblanc, Catherine; Michel, Gurvan; Potin, Philippe [Centre National de la Recherche Scientifique and Universite Pierre et Marie Curie Paris-VI, Station Biologique de Roscoff, Place Georges Teissier, BP 74, F-29682 Roscoff cedex, Bretagne (France); Kuepper, Frithjof C [Scottish Association for Marine Science, Dunstaffnage Marine Laboratory, Oban, Argyll PA37 1QA, Scotland (United Kingdom); Hollenstein, Kaspar; Locher, Kaspar P [Institute of Molecular Biology and Biophysics, ETH Zuerich, Schafmattstrasse 20, Zuerich, 8093 (Switzerland); Bevers, Loes E; Hagedoorn, Peter-Leon; Hagen, Wilfred R, E-mail: m.feiters@science.ru.n [Department of Biotechnology, Delft University of Technology, Julianalaan 67, 2628 BC Delft (Netherlands)

2009-11-15

We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L{sub 3} (2p{sub 3/2}) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

Anion binding in biological systems

International Nuclear Information System (INIS)

Feiters, Martin C; Meyer-Klaucke, Wolfram; Kostenko, Alexander V; Soldatov, Alexander V; Leblanc, Catherine; Michel, Gurvan; Potin, Philippe; Kuepper, Frithjof C; Hollenstein, Kaspar; Locher, Kaspar P; Bevers, Loes E; Hagedoorn, Peter-Leon; Hagen, Wilfred R

2009-01-01

We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L 3 (2p 3/2 ) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

Anion binding in biological systems

Science.gov (United States)

Feiters, Martin C.; Meyer-Klaucke, Wolfram; Kostenko, Alexander V.; Soldatov, Alexander V.; Leblanc, Catherine; Michel, Gurvan; Potin, Philippe; Küpper, Frithjof C.; Hollenstein, Kaspar; Locher, Kaspar P.; Bevers, Loes E.; Hagedoorn, Peter-Leon; Hagen, Wilfred R.

2009-11-01

We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L3 (2p3/2) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2

Directory of Open Access Journals (Sweden)

Mi Huaiyu

2015-06-01

Full Text Available The Systems Biological Graphical Notation (SBGN is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD, Entity Relationship (ER and Activity Flow (AF, allow for the representation of different aspects of biological and biochemical systems at different levels of detail.

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

Science.gov (United States)

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.

The effect of cosmic rays on biological systems - an investigation during GLE events

Science.gov (United States)

Belisheva, N. K.; Lammer, H.; Biernat, H. K.; Vashenuyk, E. V.

2012-01-01

In this study, first direct and circumstantial evidences of the effects of cosmic rays (CR) on biological systems are presented. A direct evidence of biological effects of CR is demonstrated in experiments with three cellular lines growing in culture during three events of Ground Level Enhancement (GLEs) in the neutron count rate detected by ground-based neutron monitor in October 1989. Various phenomena associated with DNA lesion on the cellular level demonstrate coherent dynamics of radiation effects in all cellular lines coincident with the time of arrival of high-energy solar particles to the near-Earth space and with the main peak in GLE. These results were obtained in the course of six separate experiments, with partial overlapping of the time of previous and subsequent experiments, which started and finished in the quiet period of solar activity (SA). A significant difference between the values of multinuclear cells in all cellular lines in the quiet period and during GLE events indicates that the cause of radiation effects in the cell cultures is an exposure of cells to the secondary solar CR near the Earth's surface. The circumstantial evidence was obtained by statistical analysis of cases of congenital malformations (CM) at two sites in the Murmansk region. The number of cases of all classes of CM reveals a significant correlation with the number of GLE events. The number of cases of CM with pronounced chromosomal abnormalities clearly correlates with the GLE events that occurred a year before the birth of a child. We have found a significant correlation between modulations of the water properties and daily background variations of CR intensity. We believe that the effects of CR on biological systems can be also mediated by fluctuations in water properties, considered as one of possible mechanisms controlling the effects of CRs on biological systems.

Applications of dynamical systems in biology and medicine

CERN Document Server

Radunskaya, Ami

2015-01-01

This volume highlights problems from a range of biological and medical applications that can be interpreted as questions about system behavior or control.  Topics include drug resistance in cancer and malaria, biological fluid dynamics, auto-regulation in the kidney, anti-coagulation therapy, evolutionary diversification and photo-transduction.  Mathematical techniques used to describe and investigate these biological and medical problems include ordinary, partial and stochastic differentiation equations, hybrid discrete-continuous approaches, as well as 2 and 3D numerical simulation. .

Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort

Science.gov (United States)

Casas, Jérôme; Lazzari, Claudio; Insausti, Teresita; Launois, Pascal; Fouque, Florence

2016-01-01

Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC) powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR). PMID:27759770

Radiological/biological/aerosol removal system

Science.gov (United States)

Haslam, Jeffery J

2015-03-17

An air filter replacement system for existing buildings, vehicles, arenas, and other enclosed airspaces includes a replacement air filter for replacing a standard air filter. The replacement air filter has dimensions and air flow specifications that allow it to replace the standard air filter. The replacement air filter includes a filter material that removes radiological or biological or aerosol particles.

Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

Directory of Open Access Journals (Sweden)

Ina Aretz

2016-04-01

Full Text Available Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology.

Science.gov (United States)

Aretz, Ina; Meierhofer, David

2016-04-27

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

A self-contained, programmable microfluidic cell culture system with real-time microscopy access

DEFF Research Database (Denmark)

Skafte-Pedersen, Peder; Hemmingsen, Mette; Sabourin, David

2011-01-01

Utilizing microfluidics is a promising way for increasing the throughput and automation of cell biology research. We present a complete self-contained system for automated cell culture and experiments with real-time optical read-out. The system offers a high degree of user-friendliness, stability...... enables the system to perform parallel, programmable and multiconditional assays on a single chip. A modular approach provides system versatility and allows many different chips to be used dependent upon application. We validate the system's performance by demonstrating on-chip passive switching...... and mixing by peristaltically driven flows. Applicability for biological assays is demonstrated by on-chip cell culture including on-chip transfection and temporally programmable gene expression....

Specifications of Standards in Systems and Synthetic Biology.

Science.gov (United States)

Schreiber, Falk; Bader, Gary D; Golebiewski, Martin; Hucka, Michael; Kormeier, Benjamin; Le Novère, Nicolas; Myers, Chris; Nickerson, David; Sommer, Björn; Waltemath, Dagmar; Weise, Stephan

2015-09-04

Standards shape our everyday life. From nuts and bolts to electronic devices and technological processes, standardised products and processes are all around us. Standards have technological and economic benefits, such as making information exchange, production, and services more efficient. However, novel, innovative areas often either lack proper standards, or documents about standards in these areas are not available from a centralised platform or formal body (such as the International Standardisation Organisation). Systems and synthetic biology is a relatively novel area, and it is only in the last decade that the standardisation of data, information, and models related to systems and synthetic biology has become a community-wide effort. Several open standards have been established and are under continuous development as a community initiative. COMBINE, the ‘COmputational Modeling in BIology’ NEtwork has been established as an umbrella initiative to coordinate and promote the development of the various community standards and formats for computational models. There are yearly two meeting, HARMONY (Hackathons on Resources for Modeling in Biology), Hackathon-type meetings with a focus on development of the support for standards, and COMBINE forums, workshop-style events with oral presentations, discussion, poster, and breakout sessions for further developing the standards. For more information see http://co.mbine.org/. So far the different standards were published and made accessible through the standards’ web- pages or preprint services. The aim of this special issue is to provide a single, easily accessible and citable platform for the publication of standards in systems and synthetic biology. This special issue is intended to serve as a central access point to standards and related initiatives in systems and synthetic biology, it will be published annually to provide an opportunity for standard development groups to communicate updated specifications.

Time scale of diffusion in molecular and cellular biology

International Nuclear Information System (INIS)

Holcman, D; Schuss, Z

2014-01-01

Diffusion is the driver of critical biological processes in cellular and molecular biology. The diverse temporal scales of cellular function are determined by vastly diverse spatial scales in most biophysical processes. The latter are due, among others, to small binding sites inside or on the cell membrane or to narrow passages between large cellular compartments. The great disparity in scales is at the root of the difficulty in quantifying cell function from molecular dynamics and from simulations. The coarse-grained time scale of cellular function is determined from molecular diffusion by the mean first passage time of molecular Brownian motion to a small targets or through narrow passages. The narrow escape theory (NET) concerns this issue. The NET is ubiquitous in molecular and cellular biology and is manifested, among others, in chemical reactions, in the calculation of the effective diffusion coefficient of receptors diffusing on a neuronal cell membrane strewn with obstacles, in the quantification of the early steps of viral trafficking, in the regulation of diffusion between the mother and daughter cells during cell division, and many other cases. Brownian trajectories can represent the motion of a molecule, a protein, an ion in solution, a receptor in a cell or on its membrane, and many other biochemical processes. The small target can represent a binding site or an ionic channel, a hidden active site embedded in a complex protein structure, a receptor for a neurotransmitter on the membrane of a neuron, and so on. The mean time to attach to a receptor or activator determines diffusion fluxes that are key regulators of cell function. This review describes physical models of various subcellular microdomains, in which the NET coarse-grains the molecular scale to a higher cellular-level, thus clarifying the role of cell geometry in determining subcellular function. (topical review)

Time scale of diffusion in molecular and cellular biology

Science.gov (United States)

Holcman, D.; Schuss, Z.

2014-05-01

Diffusion is the driver of critical biological processes in cellular and molecular biology. The diverse temporal scales of cellular function are determined by vastly diverse spatial scales in most biophysical processes. The latter are due, among others, to small binding sites inside or on the cell membrane or to narrow passages between large cellular compartments. The great disparity in scales is at the root of the difficulty in quantifying cell function from molecular dynamics and from simulations. The coarse-grained time scale of cellular function is determined from molecular diffusion by the mean first passage time of molecular Brownian motion to a small targets or through narrow passages. The narrow escape theory (NET) concerns this issue. The NET is ubiquitous in molecular and cellular biology and is manifested, among others, in chemical reactions, in the calculation of the effective diffusion coefficient of receptors diffusing on a neuronal cell membrane strewn with obstacles, in the quantification of the early steps of viral trafficking, in the regulation of diffusion between the mother and daughter cells during cell division, and many other cases. Brownian trajectories can represent the motion of a molecule, a protein, an ion in solution, a receptor in a cell or on its membrane, and many other biochemical processes. The small target can represent a binding site or an ionic channel, a hidden active site embedded in a complex protein structure, a receptor for a neurotransmitter on the membrane of a neuron, and so on. The mean time to attach to a receptor or activator determines diffusion fluxes that are key regulators of cell function. This review describes physical models of various subcellular microdomains, in which the NET coarse-grains the molecular scale to a higher cellular-level, thus clarifying the role of cell geometry in determining subcellular function.

Time rescaling and pattern formation in biological evolution.

Science.gov (United States)

Igamberdiev, Abir U

2014-09-01

Biological evolution is analyzed as a process of continuous measurement in which biosystems interpret themselves in the environment resulting in changes of both. This leads to rescaling of internal time (heterochrony) followed by spatial reconstructions of morphology (heterotopy). The logical precondition of evolution is the incompleteness of biosystem's internal description, while the physical precondition is the uncertainty of quantum measurement. The process of evolution is based on perpetual changes in interpretation of information in the changing world. In this interpretation the external biospheric gradients are used for establishment of new features of organization. It is concluded that biological evolution involves the anticipatory epigenetic changes in the interpretation of genetic symbolism which cannot generally be forecasted but can provide canalization of structural transformations defined by the existing organization and leading to predictable patterns of form generation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

What does systems biology mean for drug development?

Science.gov (United States)

Schrattenholz, André; Soskić, Vukić

2008-01-01

The complexity and flexibility of cellular architectures is increasingly recognized by impressive progress on the side of molecular analytics, i.e. proteomics, genomics and metabolomics. One of the messages from systems biology is that the number of molecular species in cellular networks is orders of magnitude bigger than anticipated by genomic analysis, in particular by fast posttranslational modifications of proteins. The requirements to manage external signals, integrate spatiotemporal signal transduction inside an organism and at the same time optimizing networks of biochemical and chemical reactions result in chemically extremely fine tuned molecular entities. Chemical side reactions of enzymatic activity, like e.g. random oxidative damage of proteins by free radicals during aging constantly introduce epigenetic alterations of protein targets. These events gradually and on an individual stochastic scale, keep modifying activities of these targets, and their affinities and selectivities towards biological and pharmacological ligands. One further message is that many of the key reactions in living systems are essentially based on interactions of low affinities and even low selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. So, in complex disorders like cancer or neurodegenerative diseases, which are rooted in relatively subtle and multimodal dysfunction of important physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which still dominate the pharmaceutical industry increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade and the treatment of "complex diseases" remains a most pressing medical need. Currently a change of paradigm can be observed with

Network science of biological systems at different scales: A review

Science.gov (United States)

Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

2018-03-01

Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

Quantitative, high-resolution proteomics for data-driven systems biology

DEFF Research Database (Denmark)

Cox, J.; Mann, M.

2011-01-01

Systems biology requires comprehensive data at all molecular levels. Mass spectrometry (MS)-based proteomics has emerged as a powerful and universal method for the global measurement of proteins. In the most widespread format, it uses liquid chromatography (LC) coupled to high-resolution tandem...... primary structure of proteins including posttranslational modifications, to localize proteins to organelles, and to determine protein interactions. Here, we describe the principles of analysis and the areas of biology where proteomics can make unique contributions. The large-scale nature of proteomics...... data and its high accuracy pose special opportunities as well as challenges in systems biology that have been largely untapped so far....

A Gaussian mixture model based cost function for parameter estimation of chaotic biological systems

Science.gov (United States)

Shekofteh, Yasser; Jafari, Sajad; Sprott, Julien Clinton; Hashemi Golpayegani, S. Mohammad Reza; Almasganj, Farshad

2015-02-01

As we know, many biological systems such as neurons or the heart can exhibit chaotic behavior. Conventional methods for parameter estimation in models of these systems have some limitations caused by sensitivity to initial conditions. In this paper, a novel cost function is proposed to overcome those limitations by building a statistical model on the distribution of the real system attractor in state space. This cost function is defined by the use of a likelihood score in a Gaussian mixture model (GMM) which is fitted to the observed attractor generated by the real system. Using that learned GMM, a similarity score can be defined by the computed likelihood score of the model time series. We have applied the proposed method to the parameter estimation of two important biological systems, a neuron and a cardiac pacemaker, which show chaotic behavior. Some simulated experiments are given to verify the usefulness of the proposed approach in clean and noisy conditions. The results show the adequacy of the proposed cost function.

Tritium fractionation in biological systems and in analytical procedures

International Nuclear Information System (INIS)

Kim, M.A.; Baumgaertner, F.

1991-01-01

The organically bound tritium (OBT) is evaluated in biological systems by measuring the tritium distribution ratio (R-value), i.e. tritium concentrations in organic substance to tissue water. The determination of the R-value is found to involve always isotope fractionation in applied analytical procedures and hence the evaluation of the true OBT-value in a given biological system appears more complicated than hitherto known in the literature. The present work concentrates on the tritium isotope fraction in the tissue water separation and on the resulting effects on the R-value. The analytical procedures examined are vacuum freeze drying under equilibrium and non-equilibrium conditions and azeotropic distillation. The vaporization isotope effects are determined separately in the phase transition of solid or liquid to gas in pure water systems as well as in real biological systems, e.g. maize plant. The results are systematically analysed and the influence of isotope effects on the R-value is rigorously quantified. (orig.)

Systematic integration of experimental data and models in systems biology.

Science.gov (United States)

Li, Peter; Dada, Joseph O; Jameson, Daniel; Spasic, Irena; Swainston, Neil; Carroll, Kathleen; Dunn, Warwick; Khan, Farid; Malys, Naglis; Messiha, Hanan L; Simeonidis, Evangelos; Weichart, Dieter; Winder, Catherine; Wishart, Jill; Broomhead, David S; Goble, Carole A; Gaskell, Simon J; Kell, Douglas B; Westerhoff, Hans V; Mendes, Pedro; Paton, Norman W

2010-11-29

The behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources. Taverna workflows have been developed for the automated assembly of quantitative parameterised metabolic networks in the Systems Biology Markup Language (SBML). A SBML model is built in a systematic fashion by the workflows which starts with the construction of a qualitative network using data from a MIRIAM-compliant genome-scale model of yeast metabolism. This is followed by parameterisation of the SBML model with experimental data from two repositories, the SABIO-RK enzyme kinetics database and a database of quantitative experimental results. The models are then calibrated and simulated in workflows that call out to COPASIWS, the web service interface to the COPASI software application for analysing biochemical networks. These systems biology workflows were evaluated for their ability to construct a parameterised model of yeast glycolysis. Distributed information about metabolic reactions that have been described to MIRIAM standards enables the automated assembly of quantitative systems biology models of metabolic networks based on user-defined criteria. Such data integration processes can be implemented as Taverna workflows to provide a rapid overview of the components and their relationships within a biochemical system.

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

NARCIS (Netherlands)

He, F.; Murabito, E.; Westerhoff, H.V.

2016-01-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out throughin silicotheoretical studies with the aim to guide and complement furtherin vitroandin vivoexperimental

Systems biology of stored blood cells: can it help to extend the expiration date?

Science.gov (United States)

Paglia, Giuseppe; Palsson, Bernhard Ø; Sigurjonsson, Olafur E

2012-12-05

With increasingly stringent regulations regarding deferral and elimination of blood donors it will become increasingly important to extend the expiration date of blood components beyond the current allowed storage periods. One reason for the storage time limit for blood components is that platelets and red blood cells develop a condition called storage lesions during their storage in plastic blood containers. Systems biology provides comprehensive bio-chemical descriptions of organisms through quantitative measurements and data integration in mathematical models. The biological knowledge for a target organism can be translated in a mathematical format and used to compute physiological properties. The use of systems biology represents a concrete solution in the study of blood cell storage lesions, and it may open up new avenues towards developing better storage methods and better storage media, thereby extending the storage period of blood components. This article is part of a Special Issue entitled: Integrated omics. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.

Science.gov (United States)

Transtrum, Mark K; Qiu, Peng

2016-05-01

The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.

Guidelines for Developing Successful Short Advanced Courses in Systems Medicine and Systems Biology

KAUST Repository

Gomez-Cabrero, David

2017-08-23

Summary Systems medicine and systems biology have inherent educational challenges. These have largely been addressed either by providing new masters programs or by redesigning undergraduate programs. In contrast, short courses can respond to a different need: they can provide condensed updates for professionals across academia, the clinic, and industry. These courses have received less attention. Here, we share our experiences in developing and providing such courses to current and future leaders in systems biology and systems medicine. We present guidelines for how to reproduce our courses, and we offer suggestions for how to select students who will nurture an interdisciplinary learning environment and thrive there.

Guidelines for Developing Successful Short Advanced Courses in Systems Medicine and Systems Biology

KAUST Repository

Gomez-Cabrero, David; Marabita, Francesco; Tarazona, Sonia; Cano, Isaac; Roca, Josep; Conesa, Ana; Sabatier, Philippe; Tegner, Jesper

2017-01-01

Summary Systems medicine and systems biology have inherent educational challenges. These have largely been addressed either by providing new masters programs or by redesigning undergraduate programs. In contrast, short courses can respond to a different need: they can provide condensed updates for professionals across academia, the clinic, and industry. These courses have received less attention. Here, we share our experiences in developing and providing such courses to current and future leaders in systems biology and systems medicine. We present guidelines for how to reproduce our courses, and we offer suggestions for how to select students who will nurture an interdisciplinary learning environment and thrive there.

Strategies for structuring interdisciplinary education in Systems Biology: an European perspective

NARCIS (Netherlands)

Cvijovic, Marija; Höfer, Thomas; Acimovic, Jure; Alberghina, Lilia; Almaas, Eivind; Besozzi, Daniela; Blomberg, Anders; Bretschneider, Till; Cascante, Marta; Collin, Olivier; Atauri, de Pedro; Depner, Cornelia; Dickinson, Robert; Dobrzynski, Maciej; Fleck, C.; Garcia-Ojalvo, Jordi; Gonze, Didier; Hahn, Jens; Hess, Heide Marie; Hollmann, Susanne; Krantz, Marcus; Kummer, Ursula; Lundh, Torbjörn; Martial, Gifta; Martins dos Santos, V.A.P.; Mauer-Oberthür, Angela; Regierer, Babette; Skene, Barbara; Stalidzans, Egils; Stelling, Jörg; Teusink, Bas; Workman, Christopher T.; Hohmann, Stefan

2016-01-01

Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological

Integrative Systems Biology Applied to Toxicology

DEFF Research Database (Denmark)

Kongsbak, Kristine Grønning

associated with combined exposure to multiple chemicals. Testing all possible combinations of the tens of thousands environmental chemicals is impractical. This PhD project was launched to apply existing computational systems biology methods to toxicological research. In this thesis, I present in three...... of a system thereby suggesting new ways of thinking specific toxicological endpoints. Furthermore, computational methods can serve as valuable input for the hypothesis generating phase of the preparations of a research project....

Category of Metabolic-Replication Systems in Biology and Medicine

OpenAIRE

I. C. Baianu

2012-01-01

Metabolic-repair models, or (M,R)-systems were introduced in Relational Biology by Robert Rosen. Subsequently, Rosen represented such (M,R)-systems (or simply MRs)in terms of categories of sets, deliberately selected without any structure other than the discrete topology of sets. Theoreticians of life's origins postulated that Life on Earth has begun with the simplest possible organism, called the primordial. Mathematicians interested in biology attempted to answer this important questio...

Morphogenesis and pattern formation in biological systems experiments and models

CERN Document Server

Noji, Sumihare; Ueno, Naoto; Maini, Philip

2003-01-01

A central goal of current biology is to decode the mechanisms that underlie the processes of morphogenesis and pattern formation. Concerned with the analysis of those phenomena, this book covers a broad range of research fields, including developmental biology, molecular biology, plant morphogenesis, ecology, epidemiology, medicine, paleontology, evolutionary biology, mathematical biology, and computational biology. In Morphogenesis and Pattern Formation in Biological Systems: Experiments and Models, experimental and theoretical aspects of biology are integrated for the construction and investigation of models of complex processes. This collection of articles on the latest advances by leading researchers not only brings together work from a wide spectrum of disciplines, but also provides a stepping-stone to the creation of new areas of discovery.

Function of dynamic models in systems biology: linking structure to behaviour.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

Glycoengineering in CHO cells: Advances in systems biology

DEFF Research Database (Denmark)

Tejwani, Vijay; Andersen, Mikael Rørdam; Nam, Jong Hyun

2018-01-01

are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling......For several decades, glycoprotein biologics have been successfully produced from Chinese hamster ovary (CHO) cells. The therapeutic efficacy and potency of glycoprotein biologics are often dictated by their post translational modifications, particularly glycosylation, which unlike protein synthesis....... Recently, CHO cells have also been explored for production of therapeutic glycosaminoglycans (e.g. heparin), which presents similar challenges as producing glycoproteins biologics. Approaches to controlling heterogeneity in CHO cells and directing the biosynthetic process toward desired glycoforms...

Evaluation of a commercial biologically based IMRT treatment planning system

International Nuclear Information System (INIS)

Semenenko, Vladimir A.; Reitz, Bodo; Day, Ellen; Qi, X. Sharon; Miften, Moyed; Li, X. Allen

2008-01-01

A new inverse treatment planning system (TPS) for external beam radiation therapy with high energy photons is commercially available that utilizes both dose-volume-based cost functions and a selection of cost functions which are based on biological models. The purpose of this work is to evaluate quality of intensity-modulated radiation therapy (IMRT) plans resulting from the use of biological cost functions in comparison to plans designed using a traditional TPS employing dose-volume-based optimization. Treatment planning was performed independently at two institutions. For six cancer patients, including head and neck (one case from each institution), prostate, brain, liver, and rectal cases, segmental multileaf collimator IMRT plans were designed using biological cost functions and compared with clinically used dose-based plans for the same patients. Dose-volume histograms and dosimetric indices, such as minimum, maximum, and mean dose, were extracted and compared between the two types of treatment plans. Comparisons of the generalized equivalent uniform dose (EUD), a previously proposed plan quality index (fEUD), target conformity and heterogeneity indices, and the number of segments and monitor units were also performed. The most prominent feature of the biologically based plans was better sparing of organs at risk (OARs). When all plans from both institutions were combined, the biologically based plans resulted in smaller EUD values for 26 out of 33 OARs by an average of 5.6 Gy (range 0.24 to 15 Gy). Owing to more efficient beam segmentation and leaf sequencing tools implemented in the biologically based TPS compared to the dose-based TPS, an estimated treatment delivery time was shorter in most (five out of six) cases with some plans showing up to 50% reduction. The biologically based plans were generally characterized by a smaller conformity index, but greater heterogeneity index compared to the dose-based plans. Overall, compared to plans based on dose

Design of fluidized-bed, biological denitrification systems

International Nuclear Information System (INIS)

Patton, B.D.; Hancher, C.W.; Pitt, W.W.; Walker, J.F.

1982-01-01

Many commercial processes yield nitrate-containing wastewaters that are being discharged to the environment because traditional recovery or disposal methods are economically unacceptable. The anticipated discharge limits (i.e., 10 to 20 g (NO 3 - )/m 3 ) being considered by many states will not allow continued release of these wastewaters. The new discharge standards can be met economically by use of the fluidizied-bed, biological denitrification process. Research and development studies were conducted with 0.05-, 0.10-, 0.20-, and 0.50-m-diam fluidized-bed bioreactor systems. Feed nitrate concentrations were in the 0 to 10,000 g (NO 3 - )/m 3 range. Using the data from these studies, rate expressions were developed for the destruction of nitrate as a function of nitrate concentration. Methods were also developed for sizing bioreactors and biomass control systems. The sizing methods for fluidized-bed denitrification systems are described, and support systems such as sampling and analysis, instrumentation and controls, utilities, and bacteria storage are discussed. Operation of the process is also briefly discussed to aid the designer. Using the methods presented in this report, fluidized-bed, biological denitrification systems can be designed to treat nitrate wastewater streams

Stochastic chemical kinetics theory and (mostly) systems biological applications

CERN Document Server

Érdi, Péter; Lente, Gabor

2014-01-01

This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.

Learning (from) the errors of a systems biology model.

Science.gov (United States)

Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

2016-02-11

Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.

Investigating cholesterol metabolism and ageing using a systems biology approach.

Science.gov (United States)

Morgan, A E; Mooney, K M; Wilkinson, S J; Pickles, N A; Mc Auley, M T

2017-08-01

CVD accounted for 27 % of all deaths in the UK in 2014, and was responsible for 1·7 million hospital admissions in 2013/2014. This condition becomes increasingly prevalent with age, affecting 34·1 and 29·8 % of males and females over 75 years of age respectively in 2011. The dysregulation of cholesterol metabolism with age, often observed as a rise in LDL-cholesterol, has been associated with the pathogenesis of CVD. To compound this problem, it is estimated by 2050, 22 % of the world's population will be over 60 years of age, in culmination with a growing resistance and intolerance to pre-existing cholesterol regulating drugs such as statins. Therefore, it is apparent research into additional therapies for hypercholesterolaemia and CVD prevention is a growing necessity. However, it is also imperative to recognise this complex biological system cannot be studied using a reductionist approach; rather its biological uniqueness necessitates a more integrated methodology, such as that offered by systems biology. In this review, we firstly discuss cholesterol metabolism and how it is affected by diet and the ageing process. Next, we describe therapeutic strategies for hypercholesterolaemia, and finally how the systems biology paradigm can be utilised to investigate how ageing interacts with complex systems such as cholesterol metabolism. We conclude by emphasising the need for nutritionists to work in parallel with the systems biology community, to develop novel approaches to studying cholesterol metabolism and its interaction with ageing.

Systems Biology of Meridians, Acupoints, and Chinese Herbs in Disease

Directory of Open Access Journals (Sweden)

Li-Ling Lin

2012-01-01

Full Text Available Meridians, acupoints, and Chinese herbs are important components of traditional Chinese medicine (TCM. They have been used for disease treatment and prevention and as alternative and complementary therapies. Systems biology integrates omics data, such as transcriptional, proteomic, and metabolomics data, in order to obtain a more global and complete picture of biological activity. To further understand the existence and functions of the three components above, we reviewed relevant research in the systems biology literature and found many recent studies that indicate the value of acupuncture and Chinese herbs. Acupuncture is useful in pain moderation and relieves various symptoms arising from acute spinal cord injury and acute ischemic stroke. Moreover, Chinese herbal extracts have been linked to wound repair, the alleviation of postmenopausal osteoporosis severity, and anti-tumor effects, among others. Different acupoints, variations in treatment duration, and herbal extracts can be used to alleviate various symptoms and conditions and to regulate biological pathways by altering gene and protein expression. Our paper demonstrates how systems biology has helped to establish a platform for investigating the efficacy of TCM in treating different diseases and improving treatment strategies.

Simultaneous biological nutrient removal: evaluation of autotrophic denitrification, heterotrophic nitrification, and biological phosphorus removal in full-scale systems.

Science.gov (United States)

Littleton, Helen X; Daigger, Glen T; Strom, Peter F; Cowan, Robert A

2003-01-01

Simultaneous biological nutrient removal (SBNR) is the biological removal of nitrogen and phosphorus in excess of that required for biomass synthesis in a biological wastewater treatment system without defined anaerobic or anoxic zones. Evidence is growing that significant SBNR can occur in many systems, including the aerobic zone of systems already configured for biological nutrient removal. Although SBNR systems offer several potential advantages, they cannot be fully realized until the mechanisms responsible for SBNR are better understood. Consequently, a research program was initiated with the basic hypothesis that three mechanisms might be responsible for SBNR: the reactor macroenvironment, the floc microenvironment, and novel microorganisms. Previously, the nutrient removal capabilities of seven full-scale, staged, closed-loop bioreactors known as Orbal oxidation ditches were evaluated. Chemical analysis and microbiological observations suggested that SBNR occurred in these systems. Three of these plants were further examined in this research to evaluate the importance of novel microorganisms, especially for nitrogen removal. A screening tool was developed to determine the relative significance of the activities of microorganisms capable of autotrophic denitrification and heterotrophic nitrification-aerobic denitrification in biological nutrient removal systems. The results indicated that novel microorganisms were not substantial contributors to SBNR in the plants studied. Phosphorus metabolism (anaerobic release, aerobic uptake) was also tested in one of the plants. Activity within the mixed liquor that was consistent with current theories for phosphorus-accumulating organisms (PAOs) was observed. Along with other observations, this suggests the presence of PAOs in the facilities studied.

From experimental systems to evolutionary biology: an impossible journey?

Science.gov (United States)

Morange, Michel

2013-01-01

The historical approach to the sciences has undergone a sea change during recent decades. Maybe the major contribution of Hans-Jörg Rheinberger to this movement was his demonstration of the importance of experimental systems, and of their transformations, in the development of the sciences. To describe these transformations, Hans-Jörg borrows metaphors from evolutionary biology. I want to argue that evolutionary biologists can find in these recent historical studies plenty of models and concepts to address unresolved issues in their discipline. At a time when transdisciplinarity is highly praised, it is useful to provide a precise description of the obstacles that have so far prevented this exchange.

Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

Science.gov (United States)

Hilfinger, Andreas; Paulsson, Johan

2011-07-19

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.

Clinical and biological features of multiple myeloma involving the gastrointestinal system.

Science.gov (United States)

Talamo, Giampaolo; Cavallo, Federica; Zangari, Maurizio; Barlogie, Bart; Lee, Choon-Kee; Pineda-Roman, Mauricio; Kiwan, Elias; Krishna, Somashekar; Tricot, Guido

2006-07-01

We report 24 cases of multiple myeloma (MM) with involvement of the gastrointestinal (GI) system. We found a strong association with high A lactate dehydrogenase levels, plasmablastic morphology, and A unfavorable karyotype. GI involvement at the time of initial diagnosis was much rarer than later in the course of the disease. The A median survival after diagnosis of GI involvement was 7 months. Among 13 patients treated with stem cell transplantation, the response rate was 92%, and median progression-free survival was 4 months. We conclude that MM involving the GI system is associated with adverse biological features and with short-lasting remissions, even after A high-dose chemotherapy.

System biology and the project Encode

Directory of Open Access Journals (Sweden)

M. Yu. Obolenskaya

2014-08-01

Full Text Available The goal of this review is to give an incipient knowledge on the background of system biology, the premises to its assignment as a new branch of biology, its principles, methodology and its great achievements in identification of functional elements of human genome and regulation of their concordant­ and differential activity. The short characteristics of functional elements including the protein-coding sequences and those coding noncoding RNAs, the DNAse 1 hypersensitivity sites and methylated CpG islets, modified histones and specific 3D structure of chromatin, are represented. The topology of transcription factors network with its main motifs, hierar­chy, combination and association of transcription factors and their allelic specificity are highlighted­.

Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

Science.gov (United States)

Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Integrating phosphoproteomics in systems biology

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Yu Liu

2014-07-01

Full Text Available Phosphorylation of serine, threonine and tyrosine plays significant roles in cellular signal transduction and in modifying multiple protein functions. Phosphoproteins are coordinated and regulated by a network of kinases, phosphatases and phospho-binding proteins, which modify the phosphorylation states, recognize unique phosphopeptides, or target proteins for degradation. Detailed and complete information on the structure and dynamics of these networks is required to better understand fundamental mechanisms of cellular processes and diseases. High-throughput technologies have been developed to investigate phosphoproteomes in model organisms and human diseases. Among them, mass spectrometry (MS-based technologies are the major platforms and have been widely applied, which has led to explosive growth of phosphoproteomic data in recent years. New bioinformatics tools are needed to analyze and make sense of these data. Moreover, most research has focused on individual phosphoproteins and kinases. To gain a more complete knowledge of cellular processes, systems biology approaches, including pathways and networks modeling, have to be applied to integrate all components of the phosphorylation machinery, including kinases, phosphatases, their substrates, and phospho-binding proteins. This review presents the latest developments of bioinformatics methods and attempts to apply systems biology to analyze phosphoproteomics data generated by MS-based technologies. Challenges and future directions in this field will be also discussed.

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

Science.gov (United States)

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/.

Nonlinear dynamics in biological systems

CERN Document Server

Carballido-Landeira, Jorge

2016-01-01

This book presents recent research results relating to applications of nonlinear dynamics, focusing specifically on four topics of wide interest: heart dynamics, DNA/RNA, cell mobility, and proteins. The book derives from the First BCAM Workshop on Nonlinear Dynamics in Biological Systems, held in June 2014 at the Basque Center of Applied Mathematics (BCAM). At this international meeting, researchers from different but complementary backgrounds, including molecular dynamics, physical chemistry, bio-informatics and biophysics, presented their most recent results and discussed the future direction of their studies using theoretical, mathematical modeling and experimental approaches. Such was the level of interest stimulated that the decision was taken to produce this publication, with the organizers of the event acting as editors. All of the contributing authors are researchers working on diverse biological problems that can be approached using nonlinear dynamics. The book will appeal especially to applied math...

Radical production in biological systems

International Nuclear Information System (INIS)

Johnson, J.R.; Akabani, G.

1994-10-01

This paper describes our effort to develop a metric for radiation exposure that is more fundamental than adsorbed dose and upon which a metric for exposure to chemicals could be based. This metric is based on the production of radicals by the two agents. Radicals produced by radiation in biological systems commonly assumed to be the same as those produced in water despite the presence of a variety of complex molecules. This may explain why the extensive efforts to describe the relationship between energy deposition (track structure) and molecular damage to DNA, based on the spectrum of radicals produced, have not been successful in explaining simple biological effects such as cell killing. Current models assume that DNA and its basic elements are immersed in water-like media and only model the production and diffusion of water-based radicals and their interaction with DNA structures; these models lack the cross sections associated with each macro-component of DNA and only treat water-based radicals. It has been found that such models are not realistic because DNA is not immersed in pure water. A computer code capable of simulating electron tracks, low-energy electrons, energy deposition in small molecules, and radical production and diffusion in water like media has been developed. This code is still in at a primitive stage and development is continuing. It is being used to study radical production by radiation, and radical diffusion and interactions in simple molecular systems following their production. We are extending the code to radical production by chemicals to complement our PBPK modeling efforts. It therefore has been developed primarily for use with radionuclides that are in biological materials, and not for radiation fields

Promoting Systems Thinking through Biology Lessons

Science.gov (United States)

Riess, Werner; Mischo, Christoph

2010-01-01

This study's goal was to analyze various teaching approaches within the context of natural science lessons, especially in biology. The main focus of the paper lies on the effectiveness of different teaching methods in promoting systems thinking in the field of Education for Sustainable Development. The following methods were incorporated into the…

Systems Biology of Immune Response to Live and Inactivated Dengue Virus Vaccines

Science.gov (United States)

2017-09-01

AWARD NUMBER: W81XWH-16-2-0032 TITLE: Systems Biology of Immune Response to Live and Inactivated Dengue Virus Vaccines PRINCIPAL INVESTIGATOR...CONTRACT NUMBER Systems Biology of Immune Response to Live and Inactivated Dengue Virus Vaccines 5b. GRANT NUMBER W81XWH-16-2-0032 5c. PROGRAM ELEMENT...cell) responses will be measured using molecular and cellular approaches and the data analyzed using a systems biology approach. During the first

Lie Symmetry of the Diffusive Lotka–Volterra System with Time-Dependent Coefficients

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Vasyl’ Davydovych

2018-02-01

Full Text Available Lie symmetry classification of the diffusive Lotka–Volterra system with time-dependent coefficients in the case of a single space variable is studied. A set of such symmetries in an explicit form is constructed. A nontrivial ansatz reducing the Lotka–Volterra system with correctly-specified coefficients to the system of ordinary differential equations (ODEs and an example of the exact solution with a biological interpretation are found.

Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project.

Science.gov (United States)

Hucka, M; Finney, A; Bornstein, B J; Keating, S M; Shapiro, B E; Matthews, J; Kovitz, B L; Schilstra, M J; Funahashi, A; Doyle, J C; Kitano, H

2004-06-01

Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

Biological variation in tPA-induced plasma clot lysis time.

Science.gov (United States)

Talens, Simone; Malfliet, Joyce J M C; Rudež, Goran; Spronk, Henri M H; Janssen, Nicole A H; Meijer, Piet; Kluft, Cornelis; de Maat, Moniek P M; Rijken, Dingeman C

2012-10-01

Hypofibrinolysis is a risk factor for venous and arterial thrombosis, and can be assessed by using a turbidimetric tPA-induced clot lysis time (CLT) assay. Biological variation in clot lysis time may affect the interpretation and usefulness of CLT as a risk factor for thrombosis. Sufficient information about assay variation and biological variation in CLT is not yet available. Thus, this study aimed to determine the analytical, within-subject and between-subject variation in CLT. We collected blood samples from 40 healthy individuals throughout a period of one year (average 11.8 visits) and determined the CLT of each plasma sample in duplicate. The mean (± SD) CLT was 83.8 (± 11.1) minutes. The coefficients of variation for total variation, analytical variation, within-subject variation and between-subject variation were 13.4%, 2.6%, 8.2% and 10.2%, respectively. One measurement can estimate the CLT that does not deviate more than 20% from its true value. The contribution of analytical variation to the within-subject variation was 5.0%, the index of individuality was 0.84 and the reference change value was 23.8%. The CLT was longer in the morning compared to the afternoon and was slightly longer in older individuals (> 40 years) compared to younger (≤40 years) individuals. There was no seasonal variation in CLT and no association with air pollution. CLT correlated weakly with fibrinogen, C-reactive protein, prothrombin time and thrombin generation. This study provides insight into the biological variation of CLT, which can be used in future studies testing CLT as a potential risk factor for thrombosis.

Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research.

Science.gov (United States)

Jinawath, Natini; Bunbanjerdsuk, Sacarin; Chayanupatkul, Maneerat; Ngamphaiboon, Nuttapong; Asavapanumas, Nithi; Svasti, Jisnuson; Charoensawan, Varodom

2016-11-22

With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians' point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world's major diseases.

Systems biology and p4 medicine: past, present, and future.

Science.gov (United States)

Hood, Leroy

2013-04-01

Studying complex biological systems in a holistic rather than a "one gene or one protein" at a time approach requires the concerted effort of scientists from a wide variety of disciplines. The Institute for Systems Biology (ISB) has seamlessly integrated these disparate fields to create a cross-disciplinary platform and culture in which "biology drives technology drives computation." To achieve this platform/culture, it has been necessary for cross-disciplinary ISB scientists to learn one another's languages and work together effectively in teams. The focus of this "systems" approach on disease has led to a discipline denoted systems medicine. The advent of technological breakthroughs in the fields of genomics, proteomics, and, indeed, the other "omics" is catalyzing striking advances in systems medicine that have and are transforming diagnostic and therapeutic strategies. Systems medicine has united genomics and genetics through family genomics to more readily identify disease genes. It has made blood a window into health and disease. It is leading to the stratification of diseases (division into discrete subtypes) for proper impedance match against drugs and the stratification of patients into subgroups that respond to environmental challenges in a similar manner (e.g. response to drugs, response to toxins, etc.). The convergence of patient-activated social networks, big data and their analytics, and systems medicine has led to a P4 medicine that is predictive, preventive, personalized, and participatory. Medicine will focus on each individual. It will become proactive in nature. It will increasingly focus on wellness rather than disease. For example, in 10 years each patient will be surrounded by a virtual cloud of billions of data points, and we will have the tools to reduce this enormous data dimensionality into simple hypotheses about how to optimize wellness and avoid disease for each individual. P4 medicine will be able to detect and treat perturbations in

What it takes to understand and cure a living system: computational systems biology and a systems biology-driven pharmacokinetics-pharmacodynamics platform

NARCIS (Netherlands)

Swat, Maciej; Kiełbasa, Szymon M.; Polak, Sebastian; Olivier, Brett; Bruggeman, Frank J.; Tulloch, Mark Quinton; Snoep, Jacky L.; Verhoeven, Arthur J.; Westerhoff, Hans V.

2011-01-01

The utility of model repositories is discussed in the context of systems biology (SB). It is shown how such repositories, and in particular their live versions, can be used for computational SB: we calculate the robustness of the yeast glycolytic network with respect to perturbations of one of its

Standards, Data Exchange and Intellectual Property Rights in Systems Biology

DEFF Research Database (Denmark)

van Zimmeren, Esther; Rutz, Berthold; Minssen, Timo

2016-01-01

” of scientists. In 2015, Biotechnology Journal published a report from an expert meeting on “Synthetic Biology & Intellectual Property Rights” organized by the Danish Agency for Science, Technology and Innovation sponsored by the European Research Area Network (ERA-Net) in Synthetic Biology (ERASynBio), in which...... we provided a number of recommendations for a variety of stakeholders. The current article offers some deeper reflections about the interface between IPRs, standards and data exchange in Systems Biology resulting from an Expert Meeting funded by another ERA-Net, ERASysAPP. The meeting brought...... together experts and stakeholders (e.g. scientists, company representatives, officials from public funding organizations) in systems biology (SysBio) from different countries.  Despite the different profiles of the stakeholders at the meeting and the variety of interests, many concerns and opinions were...

Integrative systems and synthetic biology of cell-matrix adhesion sites.

Science.gov (United States)

Zamir, Eli

2016-09-02

The complexity of cell-matrix adhesion convolves its roles in the development and functioning of multicellular organisms and their evolutionary tinkering. Cell-matrix adhesion is mediated by sites along the plasma membrane that anchor the actin cytoskeleton to the matrix via a large number of proteins, collectively called the integrin adhesome. Fundamental challenges for understanding how cell-matrix adhesion sites assemble and function arise from their multi-functionality, rapid dynamics, large number of components and molecular diversity. Systems biology faces these challenges in its strive to understand how the integrin adhesome gives rise to functional adhesion sites. Synthetic biology enables engineering intracellular modules and circuits with properties of interest. In this review I discuss some of the fundamental questions in systems biology of cell-matrix adhesion and how synthetic biology can help addressing them.

Boolean modeling in systems biology: an overview of methodology and applications

International Nuclear Information System (INIS)

Wang, Rui-Sheng; Albert, Réka; Saadatpour, Assieh

2012-01-01

Mathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology. (paper)

Converting differential-equation models of biological systems to membrane computing.

Science.gov (United States)

Muniyandi, Ravie Chandren; Zin, Abdullah Mohd; Sanders, J W

2013-12-01

This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Structural identifiability of systems biology models: a critical comparison of methods.

Directory of Open Access Journals (Sweden)

Oana-Teodora Chis

Full Text Available Analysing the properties of a biological system through in silico experimentation requires a satisfactory mathematical representation of the system including accurate values of the model parameters. Fortunately, modern experimental techniques allow obtaining time-series data of appropriate quality which may then be used to estimate unknown parameters. However, in many cases, a subset of those parameters may not be uniquely estimated, independently of the experimental data available or the numerical techniques used for estimation. This lack of identifiability is related to the structure of the model, i.e. the system dynamics plus the observation function. Despite the interest in knowing a priori whether there is any chance of uniquely estimating all model unknown parameters, the structural identifiability analysis for general non-linear dynamic models is still an open question. There is no method amenable to every model, thus at some point we have to face the selection of one of the possibilities. This work presents a critical comparison of the currently available techniques. To this end, we perform the structural identifiability analysis of a collection of biological models. The results reveal that the generating series approach, in combination with identifiability tableaus, offers the most advantageous compromise among range of applicability, computational complexity and information provided.

Microfluidic Technologies for Synthetic Biology

Directory of Open Access Journals (Sweden)

Sung Kuk Lee

2011-06-01

Full Text Available Microfluidic technologies have shown powerful abilities for reducing cost, time, and labor, and at the same time, for increasing accuracy, throughput, and performance in the analysis of biological and biochemical samples compared with the conventional, macroscale instruments. Synthetic biology is an emerging field of biology and has drawn much attraction due to its potential to create novel, functional biological parts and systems for special purposes. Since it is believed that the development of synthetic biology can be accelerated through the use of microfluidic technology, in this review work we focus our discussion on the latest microfluidic technologies that can provide unprecedented means in synthetic biology for dynamic profiling of gene expression/regulation with high resolution, highly sensitive on-chip and off-chip detection of metabolites, and whole-cell analysis.

Quantum mechanical simulation methods for studying biological systems

International Nuclear Information System (INIS)

Bicout, D.; Field, M.

1996-01-01

Most known biological mechanisms can be explained using fundamental laws of physics and chemistry and a full understanding of biological processes requires a multidisciplinary approach in which all the tools of biology, chemistry and physics are employed. An area of research becoming increasingly important is the theoretical study of biological macromolecules where numerical experimentation plays a double role of establishing a link between theoretical models and predictions and allowing a quantitative comparison between experiments and models. This workshop brought researchers working on different aspects of the development and application of quantum mechanical simulation together, assessed the state-of-the-art in the field and highlighted directions for future research. Fourteen lectures (theoretical courses and specialized seminars) deal with following themes: 1) quantum mechanical calculations of large systems, 2) ab initio molecular dynamics where the calculation of the wavefunction and hence the energy and forces on the atoms for a system at a single nuclear configuration are combined with classical molecular dynamics algorithms in order to perform simulations which use a quantum mechanical potential energy surface, 3) quantum dynamical simulations, electron and proton transfer processes in proteins and in solutions and finally, 4) free seminars that helped to enlarge the scope of the workshop. (N.T.)

[Network structures in biological systems].

Science.gov (United States)

Oleskin, A V

2013-01-01

Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

The extinction probability in systems randomly varying in time

Directory of Open Access Journals (Sweden)

Imre Pázsit

2017-09-01

Full Text Available The extinction probability of a branching process (a neutron chain in a multiplying medium is calculated for a system randomly varying in time. The evolution of the first two moments of such a process was calculated previously by the authors in a system randomly shifting between two states of different multiplication properties. The same model is used here for the investigation of the extinction probability. It is seen that the determination of the extinction probability is significantly more complicated than that of the moments, and it can only be achieved by pure numerical methods. The numerical results indicate that for systems fluctuating between two subcritical or two supercritical states, the extinction probability behaves as expected, but for systems fluctuating between a supercritical and a subcritical state, there is a crucial and unexpected deviation from the predicted behaviour. The results bear some significance not only for neutron chains in a multiplying medium, but also for the evolution of biological populations in a time-varying environment.

Modeling of nonlinear biological phenomena modeled by S-systems.

Science.gov (United States)

Mansouri, Majdi M; Nounou, Hazem N; Nounou, Mohamed N; Datta, Aniruddha A

2014-03-01

A central challenge in computational modeling of biological systems is the determination of the model parameters. In such cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. For example, time-series dynamic genomic data can be used to develop models representing dynamic genetic regulatory networks, which can be used to design intervention strategies to cure major diseases and to better understand the behavior of biological systems. Unfortunately, biological measurements are usually highly infected by errors that hide the important characteristics in the data. Therefore, these noisy measurements need to be filtered to enhance their usefulness in practice. This paper addresses the problem of state and parameter estimation of biological phenomena modeled by S-systems using Bayesian approaches, where the nonlinear observed system is assumed to progress according to a probabilistic state space model. The performances of various conventional and state-of-the-art state estimation techniques are compared. These techniques include the extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF), and the developed variational Bayesian filter (VBF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the enzyme CadA, the model cadBA, the cadaverine Cadav and the lysine Lys for a model of the Cad System in Escherichia coli (CSEC)) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of the number of estimated model parameters on the accuracy and convergence of these

Ambient measurements of biological aerosol particles near Killarney, Ireland: a comparison between real-time fluorescence and microscopy techniques

Science.gov (United States)

Healy, D. A.; Huffman, J. A.; O'Connor, D. J.; Pöhlker, C.; Pöschl, U.; Sodeau, J. R.

2014-08-01

Primary biological aerosol particles (PBAPs) can contribute significantly to the coarse particle burden in many environments. PBAPs can thus influence climate and precipitation systems as cloud nuclei and can spread disease to humans, animals, and plants. Measurement data and techniques for PBAPs in natural environments at high time- and size resolution are, however, sparse, and so large uncertainties remain in the role that biological particles play in the Earth system. In this study two commercial real-time fluorescence particle sensors and a Sporewatch single-stage particle impactor were operated continuously from 2 August to 2 September 2010 at a rural sampling location in Killarney National Park in southwestern Ireland. A cascade impactor was operated periodically to collect size-resolved particles during exemplary periods. Here we report the first ambient comparison of a waveband integrated bioaerosol sensor (WIBS-4) with a ultraviolet aerodynamic particle sizer (UV-APS) and also compare these real-time fluorescence techniques with results of fluorescence and optical microscopy of impacted samples. Both real-time instruments showed qualitatively similar behavior, with increased fluorescent bioparticle concentrations at night, when relative humidity was highest and temperature was lowest. The fluorescent particle number from the FL3 channel of the WIBS-4 and from the UV-APS were strongly correlated and dominated by a 3 μm mode in the particle size distribution. The WIBS FL2 channel exhibited particle modes at approx. 1 and 3 μm, and each was correlated with the concentration of fungal spores commonly observed in air samples collected at the site (ascospores, basidiospores, Ganoderma spp.). The WIBS FL1 channel exhibited variable multimodal distributions turning into a broad featureless single mode after averaging, and exhibited poor correlation with fungal spore concentrations, which may be due to the detection of bacterial and non-biological fluorescent

Systems Biology and P4 Medicine: Past, Present, and Future

Directory of Open Access Journals (Sweden)

Leroy Hood

2013-04-01

Full Text Available Studying complex biological systems in a holistic rather than a “one gene or one protein” at a time approach requires the concerted effort of scientists from a wide variety of disciplines. The Institute for Systems Biology (ISB has seamlessly integrated these disparate fields to create a cross-disciplinary platform and culture in which “biology drives technology drives computation.” To achieve this platform/culture, it has been necessary for cross-disciplinary ISB scientists to learn one another’s languages and work together effectively in teams. The focus of this “systems” approach on disease has led to a discipline denoted systems medicine. The advent of technological breakthroughs in the fields of genomics, proteomics, and, indeed, the other “omics” is catalyzing striking advances in systems medicine that have and are transforming diagnostic and therapeutic strategies. Systems medicine has united genomics and genetics through family genomics to more readily identify disease genes. It has made blood a window into health and disease. It is leading to the stratification of diseases (division into discrete subtypes for proper impedance match against drugs and the stratification of patients into subgroups that respond to environmental challenges in a similar manner (e.g. response to drugs, response to toxins, etc.. The convergence of patient-activated social networks, big data and their analytics, and systems medicine has led to a P4 medicine that is predictive, preventive, personalized, and participatory. Medicine will focus on each individual. It will become proactive in nature. It will increasingly focus on wellness rather than disease. For example, in 10 years each patient will be surrounded by a virtual cloud of billions of data points, and we will have the tools to reduce this enormous data dimensionality into simple hypotheses about how to optimize wellness and avoid disease for each individual. P4 medicine will be able to

Breeding system and pollination biology of the semidomesticated ...

African Journals Online (AJOL)

Breeding system and pollination biology of the semidomesticated fruit tree, Tamarindus indica L. (Leguminosae: Caesalpinioideae ): Implications for fruit production, selective breeding, and conservation of genetic resources.

Biologically inspired collision avoidance system for unmanned vehicles

Science.gov (United States)

Ortiz, Fernando E.; Graham, Brett; Spagnoli, Kyle; Kelmelis, Eric J.

2009-05-01

In this project, we collaborate with researchers in the neuroscience department at the University of Delaware to develop an Field Programmable Gate Array (FPGA)-based embedded computer, inspired by the brains of small vertebrates (fish). The mechanisms of object detection and avoidance in fish have been extensively studied by our Delaware collaborators. The midbrain optic tectum is a biological multimodal navigation controller capable of processing input from all senses that convey spatial information, including vision, audition, touch, and lateral-line (water current sensing in fish). Unfortunately, computational complexity makes these models too slow for use in real-time applications. These simulations are run offline on state-of-the-art desktop computers, presenting a gap between the application and the target platform: a low-power embedded device. EM Photonics has expertise in developing of high-performance computers based on commodity platforms such as graphic cards (GPUs) and FPGAs. FPGAs offer (1) high computational power, low power consumption and small footprint (in line with typical autonomous vehicle constraints), and (2) the ability to implement massively-parallel computational architectures, which can be leveraged to closely emulate biological systems. Combining UD's brain modeling algorithms and the power of FPGAs, this computer enables autonomous navigation in complex environments, and further types of onboard neural processing in future applications.

PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

Science.gov (United States)

Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

2016-03-10

Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and

Tritium isotope fractionation in biological systems and in analytical procedures

International Nuclear Information System (INIS)

Kim, M.A.; Baumgaertner, Franz

1989-01-01

The organically bound tritium (OBT) is evaluated in biological systems by determining the tritium distribution ratio (R-value), i.e. tritium concentrations in organic substance to cell water. The determination of the R-value always involves isotope fractionation is applied analytical procedures and hence the evaluation of the true OBT -value in a given biological system appears more complicated than hitherto known in the literature. The present work concentrates on the tritium isotope fractionation in the cell water separation and on the resulting effects on the R-value. The analytical procedures examined are vacuum freeze drying under equilibrium and non-equilibrium conditions and azeotropic distillation. The vaporization isotope effects are determined separately in the phase transition of solid or liquid to gas in pure tritium water systems as well as in real biological systems, e.g. corn plant. The results are systematically analyzed and the influence of isotope effects on the R-value is rigorously quantified

Biochemical Space: A Framework for Systemic Annotation of Biological Models

Czech Academy of Sciences Publication Activity Database

Klement, M.; Děd, T.; Šafránek, D.; Červený, Jan; Müller, Stefan; Steuer, Ralf

2014-01-01

Roč. 306, JUL (2014), s. 31-44 ISSN 1571-0661 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : biological models * model annotation * systems biology * cyanobacteria Subject RIV: EH - Ecology, Behaviour

Review of "Stochastic Modelling for Systems Biology" by Darren Wilkinson

Directory of Open Access Journals (Sweden)

Bullinger Eric

2006-12-01

Full Text Available Abstract "Stochastic Modelling for Systems Biology" by Darren Wilkinson introduces the peculiarities of stochastic modelling in biology. This book is particularly suited to as a textbook or for self-study, and for readers with a theoretical background.

Surface mixing and biological activity in the four Eastern Boundary Upwelling Systems

Directory of Open Access Journals (Sweden)

V. Rossi

2009-08-01

Full Text Available Eastern Boundary Upwelling Systems (EBUS are characterized by a high productivity of plankton associated with large commercial fisheries, thus playing key biological and socio-economical roles. Since they are populated by several physical oceanic structures such as filaments and eddies, which interact with the biological processes, it is a major challenge to study this sub- and mesoscale activity in connection with the chlorophyll distribution. The aim of this work is to make a comparative study of these four upwelling systems focussing on their surface stirring, using the Finite Size Lyapunov Exponents (FSLEs, and their biological activity, based on satellite data. First, the spatial distribution of horizontal mixing is analysed from time averages and from probability density functions of FSLEs, which allow us to divide each areas in two different subsystems. Then we studied the temporal variability of surface stirring focussing on the annual and seasonal cycle. We also proposed a ranking of the four EBUS based on the averaged mixing intensity. When investigating the links with chlorophyll concentration, the previous subsystems reveal distinct biological signatures. There is a global negative correlation between surface horizontal mixing and chlorophyll standing stocks over the four areas. To try to better understand this inverse relationship, we consider the vertical dimension by looking at the Ekman-transport and vertical velocities. We suggest the possibility of a changing response of the phytoplankton to sub/mesoscale turbulence, from a negative effect in the very productive coastal areas to a positive one in the open ocean. This study provides new insights for the understanding of the variable biological productivity in the ocean, which results from both dynamics of the marine ecosystem and of the 3-D turbulent medium.

A Generic Language for Biological Systems based on Bigraphs

DEFF Research Database (Denmark)

Damgaard, Troels Christoffer; Krivine, Jean

Several efforts have shown that process calculi developed for reasoning about concurrent and mobile systems may be employed for modelling biological systems at the molecular level. In this paper, we initiate investigation of the meta-language framework bigraphical reactive systems, due to Milner et...

Real-time systems

OpenAIRE

Badr, Salah M.; Bruztman, Donald P.; Nelson, Michael L.; Byrnes, Ronald Benton

1992-01-01

This paper presents an introduction to the basic issues involved in real-time systems. Both real-time operating sys and real-time programming languages are explored. Concurrent programming and process synchronization and communication are also discussed. The real-time requirements of the Naval Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real-time operating system, real-time programming language, real-time sy...

Metabolomics for functional genomics, systems biology, and biotechnology.

Science.gov (United States)

Saito, Kazuki; Matsuda, Fumio

2010-01-01

Metabolomics now plays a significant role in fundamental plant biology and applied biotechnology. Plants collectively produce a huge array of chemicals, far more than are produced by most other organisms; hence, metabolomics is of great importance in plant biology. Although substantial improvements have been made in the field of metabolomics, the uniform annotation of metabolite signals in databases and informatics through international standardization efforts remains a challenge, as does the development of new fields such as fluxome analysis and single cell analysis. The principle of transcript and metabolite cooccurrence, particularly transcriptome coexpression network analysis, is a powerful tool for decoding the function of genes in Arabidopsis thaliana. This strategy can now be used for the identification of genes involved in specific pathways in crops and medicinal plants. Metabolomics has gained importance in biotechnology applications, as exemplified by quantitative loci analysis, prediction of food quality, and evaluation of genetically modified crops. Systems biology driven by metabolome data will aid in deciphering the secrets of plant cell systems and their application to biotechnology.

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

Science.gov (United States)

He, Fei; Murabito, Ettore; Westerhoff, Hans V

2016-04-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. © 2016 The Author(s).

Biologic and Conventional Systemic Therapies Show Similar Safety and Efficacy in Elderly and Adult Patients With Moderate to Severe Psoriasis.

Science.gov (United States)

Garber, Caren; Plotnikova, Natalia; Au, Shiu-chung; Sorensen, Eric P; Gottlieb, Alice

2015-08-01

Despite the aging population, few studies have documented the treatment of geriatric psoriasis. The purpose of this study is to compare the efficacy, safety, and prescribing patterns of biologics and conventional systemic medications in elderly versus adult psoriasis. All patient visits coded for psoriasis or psoriatic arthritis (ICD-9 696.1 or 696.0) at the Tufts Medical Center General Dermatology Clinic from January 1, 2008, to March 1, 2015 were included in this retrospective cohort study. The outcome measure used was the validated simple-measure for assessing psoriasis activity (S-MAPA), the product of the physician's global assessment and the body surface area. 194 patients who underwent 278 treatment courses were included in the study. 48 patients were included in the elderly cohort (≥ 65 years old) and 146 in the adult cohort (18-64 years old). There was no significant difference in S-MAPA improvement at 12 weeks between the two cohorts when treated with biologics (42.92% improvement in adults, 48.77% in elderly; P=0.498) or conventional systemics (43.96% and 51.82%, respectively; P=0.448). Within the elderly cohort, there was no significant difference in efficacy of biologics versus conventional systemics at any time point. Topical prescription rates were significantly higher in the elderly cohort ( P=0.004) while biologic prescription rates were significantly lower ( P=0.014) despite the same baseline S-MAPA in both age groups. For both biologics and conventional systemics, there was no statistically significant intergroup difference in the rate of adverse events ( P=0.322 for biologics; P=0.581 for conventional systemics) or infection ( P=0.753 for biologics; P=0.828 for conventional systemics). Within the elderly cohort, there was a higher rate of adverse events with conventional systemic treatment than with biologic treatment ( P=0.033). This study provides preliminary evidence to suggest that biologic and conventional systemic therapies are similarly

Data management and data enrichment for systems biology projects.

Science.gov (United States)

Wittig, Ulrike; Rey, Maja; Weidemann, Andreas; Müller, Wolfgang

2017-11-10

Collecting, curating, interlinking, and sharing high quality data are central to de.NBI-SysBio, the systems biology data management service center within the de.NBI network (German Network for Bioinformatics Infrastructure). The work of the center is guided by the FAIR principles for scientific data management and stewardship. FAIR stands for the four foundational principles Findability, Accessibility, Interoperability, and Reusability which were established to enhance the ability of machines to automatically find, access, exchange and use data. Within this overview paper we describe three tools (SABIO-RK, Excemplify, SEEK) that exemplify the contribution of de.NBI-SysBio services to FAIR data, models, and experimental methods storage and exchange. The interconnectivity of the tools and the data workflow within systems biology projects will be explained. For many years we are the German partner in the FAIRDOM initiative (http://fair-dom.org) to establish a European data and model management service facility for systems biology. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments.

Science.gov (United States)

Kudoh, Hiroshi

2016-04-01

Phenology refers to the study of seasonal schedules of organisms. Molecular phenology is defined here as the study of the seasonal patterns of organisms captured by molecular biology techniques. The history of molecular phenology is reviewed briefly in relation to advances in the quantification technology of gene expression. High-resolution molecular phenology (HMP) data have enabled us to study phenology with an approach of in natura systems biology. I review recent analyses of FLOWERING LOCUS C (FLC), a temperature-responsive repressor of flowering, along the six steps in the typical flow of in natura systems biology. The extensive studies of the regulation of FLC have made this example a successful case in which a comprehensive understanding of gene functions has been progressing. The FLC-mediated long-term memory of past temperatures creates time lags with other seasonal signals, such as photoperiod and short-term temperature. Major signals that control flowering time have a phase lag between them under natural conditions, and hypothetical phase lag calendars are proposed as mechanisms of season detection in plants. Transcriptomic HMP brings a novel strategy to the study of molecular phenology, because it provides a comprehensive representation of plant functions. I discuss future perspectives of molecular phenology from the standpoints of molecular biology, evolutionary biology and ecology. © 2015 The Author. New Phytologist © 2015 New Phytologist Trust.

Construction of a Linux based chemical and biological information system.

Science.gov (United States)

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.

Polynomial algebra of discrete models in systems biology.

Science.gov (United States)

Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2010-07-01

An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.

Synthetic and systems biology for microbial production of commodity chemicals.

Science.gov (United States)

Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J; Keasling, Jay D; Martín, Héctor García

2016-01-01

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Creating biological nanomaterials using synthetic biology

International Nuclear Information System (INIS)

Rice, MaryJoe K; Ruder, Warren C

2014-01-01

Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems. (review)

Creating biological nanomaterials using synthetic biology.

Science.gov (United States)

Rice, MaryJoe K; Ruder, Warren C

2014-02-01

Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems.

Optical sensors and their applications for probing biological systems

DEFF Research Database (Denmark)

Palanco, Marta Espina

There is a great interest in exploring and developing new optical sensitive methodologies for probing complex biological systems. In this project we developed non-invasive and sensitive biosensor strategies for studying physiologically relevant chemical and physical properties of plant and mammal......There is a great interest in exploring and developing new optical sensitive methodologies for probing complex biological systems. In this project we developed non-invasive and sensitive biosensor strategies for studying physiologically relevant chemical and physical properties of plant...... of a trapped cell. The project could provide new insights into the desired biosensor for future membrane-protein cell studies....

Scale relativity theory and integrative systems biology: 2. Macroscopic quantum-type mechanics.

Science.gov (United States)

Nottale, Laurent; Auffray, Charles

2008-05-01

In these two companion papers, we provide an overview and a brief history of the multiple roots, current developments and recent advances of integrative systems biology and identify multiscale integration as its grand challenge. Then we introduce the fundamental principles and the successive steps that have been followed in the construction of the scale relativity theory, which aims at describing the effects of a non-differentiable and fractal (i.e., explicitly scale dependent) geometry of space-time. The first paper of this series was devoted, in this new framework, to the construction from first principles of scale laws of increasing complexity, and to the discussion of some tentative applications of these laws to biological systems. In this second review and perspective paper, we describe the effects induced by the internal fractal structures of trajectories on motion in standard space. Their main consequence is the transformation of classical dynamics into a generalized, quantum-like self-organized dynamics. A Schrödinger-type equation is derived as an integral of the geodesic equation in a fractal space. We then indicate how gauge fields can be constructed from a geometric re-interpretation of gauge transformations as scale transformations in fractal space-time. Finally, we introduce a new tentative development of the theory, in which quantum laws would hold also in scale space, introducing complexergy as a measure of organizational complexity. Initial possible applications of this extended framework to the processes of morphogenesis and the emergence of prokaryotic and eukaryotic cellular structures are discussed. Having founded elements of the evolutionary, developmental, biochemical and cellular theories on the first principles of scale relativity theory, we introduce proposals for the construction of an integrative theory of life and for the design and implementation of novel macroscopic quantum-type experiments and devices, and discuss their potential

Request for Travel Funds for Systems Radiation Biology Workshop

Energy Technology Data Exchange (ETDEWEB)

Barcellos-Hoff, Mary Helen [NYU School of Medicine

2014-03-22

The 3rd International Systems Radiation Biology Workshop brought together the major European, US and Japanese research programs on radiation risk as well as selected experts representing systems biological approaches to discuss how the new methodologies could be best exploited for low dose research. A significant part of the workshop was devoted to discussions organised as breakout group sessions. To facilitate discussions number of participants was limited to 60 persons. To achieve the goals of this symposium in this international conference, support from DOE is vital. Hence, this proposal requested support in the amount of $15,000 to cover the travel expenses of international experts and radiation biology scientists from the United States. This supporting mechanism was clearly identified to the selected US participants as a conference support award from the DOE (See attached PDF). The workshop was an outstanding opportunity to strengthen interactions between leading experts in the emerging areas of radiation sciences, and will also provide opportunities for younger scientists to meet with experts and discuss their results. This workshop was designed to endorse active engagement in international collaboration. A major objective of this conference was to effectively communicate research results, in order to ensure that current thinking reflects sound science of radiation biology. Further, this international event addressed the use and success of scientific initiatives in radiation biology for policymakers, standard-setters, and the general public.

Continuum analysis of biological systems conserved quantities, fluxes and forces

CERN Document Server

Suraishkumar, G K

2014-01-01

This book addresses the analysis, in the continuum regime, of biological systems at various scales, from the cellular level to the industrial one. It presents both fundamental conservation principles (mass, charge, momentum and energy) and relevant fluxes resulting from appropriate driving forces, which are important for the analysis, design and operation of biological systems. It includes the concept of charge conservation, an important principle for biological systems that is not explicitly covered in any other book of this kind. The book is organized in five parts: mass conservation; charge conservation; momentum conservation; energy conservation; and multiple conservations simultaneously applied. All mathematical aspects are presented step by step, allowing any reader with a basic mathematical background (calculus, differential equations, linear algebra, etc.) to follow the text with ease. The book promotes an intuitive understanding of all the relevant principles and in so doing facilitates their applica...

Childhood stress and birth timing among African American women: Cortisol as biological mediator.

Science.gov (United States)

Gillespie, Shannon L; Christian, Lisa M; Alston, Angela D; Salsberry, Pamela J

2017-10-01

Preterm birth (PTB) occurs among 1:11U.S. white women and 1:7.5 African American women and is a significant driver of racial disparities in infant mortality. Maternal stress is the most common clinical phenotype underlying spontaneous PTB. Specific patterns of stress and biological mediators driving PTB remain unclear. We examined the effect of childhood stress on birth timing among African American women and evaluated maternal cortisol elevation as a biological mediator. A prospective observational design was employed, with a single study visit at 28-32 weeks gestation and medical record review. The Stress and Adversity Inventory was administered, which provides a comprehensive estimate of childhood stress, stress in adulthood, and five core characteristic subscales (interpersonal loss, physical danger, humiliation, entrapment, role disruption). Venipuncture was performed between 11:00am and 4:00pm and plasma cortisol quantified by ELISA. Analyses controlled for stress in adulthood. Among a final sample of 89, cumulative childhood stress predicted birth timing (p=0.01). The association was driven by stress related to interpersonal loss and physical danger, with support for maternal cortisol as a biological mediator (ab=0.02, 95% CI [0.001, 0.045]; ab=0.02, 95% CI [0.001, 0.043], respectively). Results were similar, overall, in sub-group analyses among spontaneously laboring women (n=53); however, role disruption arose as an additional predictor, as mediated by cortisol elevations (ab=0.03, 95% CI [0.005, 0.074]). Of note, cortisol was no longer supported as a mediator linking physical danger to birth timing after adjusting for sleep quality and hours awake prior to venipuncture (ab=0.02, 95% CI [-0.0001, 0.046]). We provide preliminary evidence that, independent of stress in adulthood, childhood stress of specific core characteristics may shape birth timing, with cortisol elevation as a biological mediator. Further investigation is warranted and may bolster the

ADAPTIVE MONITORING TO ENHANCE WATER SENSOR CAPABILITIES FOR CHEMICAL AND BIOLOGICAL CONTAMINANT DETECTION IN DRINKING WATER SYSTEMS

Science.gov (United States)

Optoelectronic and other conventional water quality sensors offer a potential for real-time online detection of chemical and biological contaminants in a drinking water supply and distribution system. The nature of the application requires sensors of detection capabilities at lo...

Stochastic transport processes in discrete biological systems

CERN Document Server

Frehland, Eckart

1982-01-01

These notes are in part based on a course for advanced students in the applications of stochastic processes held in 1978 at the University of Konstanz. These notes contain the results of re­ cent studies on the stochastic description of ion transport through biological membranes. In particular, they serve as an introduction to an unified theory of fluctuations in complex biological transport systems. We emphasize that the subject of this volume is not to introduce the mathematics of stochastic processes but to present a field of theoretical biophysics in which stochastic methods are important. In the last years the study of membrane noise has become an important method in biophysics. Valuable information on the ion transport mechanisms in membranes can be obtained from noise analysis. A number of different processes such as the opening and closing of ion channels have been shown to be sources of the measured current or voltage fluctuations. Bio­ logical 'transport systems can be complex. For example, the tr...

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

Science.gov (United States)

Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

Biological diversity in the patent system.

Directory of Open Access Journals (Sweden)

Paul Oldham

Full Text Available Biological diversity in the patent system is an enduring focus of controversy but empirical analysis of the presence of biodiversity in the patent system has been limited. To address this problem we text mined 11 million patent documents for 6 million Latin species names from the Global Names Index (GNI established by the Global Biodiversity Information Facility (GBIF and Encyclopedia of Life (EOL. We identified 76,274 full Latin species names from 23,882 genera in 767,955 patent documents. 25,595 species appeared in the claims section of 136,880 patent documents. This reveals that human innovative activity involving biodiversity in the patent system focuses on approximately 4% of taxonomically described species and between 0.8-1% of predicted global species. In this article we identify the major features of the patent landscape for biological diversity by focusing on key areas including pharmaceuticals, neglected diseases, traditional medicines, genetic engineering, foods, biocides, marine genetic resources and Antarctica. We conclude that the narrow focus of human innovative activity and ownership of genetic resources is unlikely to be in the long term interest of humanity. We argue that a broader spectrum of biodiversity needs to be opened up to research and development based on the principles of equitable benefit-sharing, respect for the objectives of the Convention on Biological Diversity, human rights and ethics. Finally, we argue that alternative models of innovation, such as open source and commons models, are required to open up biodiversity for research that addresses actual and neglected areas of human need. The research aims to inform the implementation of the 2010 Nagoya Protocol on Access to Genetic Resources and the Equitable Sharing of Benefits Arising from their Utilization and international debates directed to the governance of genetic resources. Our research also aims to inform debates under the Intergovernmental Committee on

Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2.

Science.gov (United States)

Mi, Huaiyu; Schreiber, Falk; Moodie, Stuart; Czauderna, Tobias; Demir, Emek; Haw, Robin; Luna, Augustin; Le Novère, Nicolas; Sorokin, Anatoly; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

cellPACK: a virtual mesoscope to model and visualize structural systems biology.

Science.gov (United States)

Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2015-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

System as metaphor in the psychology and biology of shame.

Science.gov (United States)

Maunder, R

1996-01-01

Biological theories of brain and psychological theories of mind are two systems of explanation that seem related to one another. The nature of the relationship is problematic and constitutes the age-old mind-body problem. The most prominent solutions currently are variations of materialism. While psychological theories can be consistent with materialism, there remains a difficulty in comprehending nonphysical (social, psychological) causes of physical effects. This difficulty is an obstacle to integration in psychiatry, where we routinely assume that illnesses that include or depend on biological dysfunction are caused multifactorially by causal agents such as perceived parental warmth, parental loss, stressful life events, genetics, and personality (Hammen et al. 1992; Kendler et al. 1993). Unity theory adopts the stance that neurobiological theories and psychological theories are essentially disparate explanations of the same psychobiological events; thus the relationship of mind to brain is one of shared reference (Goodman 1991; Maunder 1995). In Goodman's model the gap between biological and psychological systems is not bridgeable. Different conceptual categories refer to the same referents but cannot interact with each other. Stepping into the breach, systems theory has been presented as offering a language that can bridge the gap between psychological and biological theories of causation (Schwartz 1981; Weiner 1989). Thus, there is a controversy about the applicability of systems theory for integration in psychiatry.

Networks as a Privileged Way to Develop Mesoscopic Level Approaches in Systems Biology

OpenAIRE

Alessandro Giuliani

2014-01-01

The methodologies advocated in computational biology are in many cases proper system-level approaches. These methodologies are variously connected to the notion of “mesosystem” and thus on the focus on relational structures that are at the basis of biological regulation. Here, I describe how the formalization of biological systems by means of graph theory constitutes an extremely fruitful approach to biology. I suggest the epistemological relevance of the notion of graph resides in its multil...

When one model is not enough: Combining epistemic tools in systems biology

DEFF Research Database (Denmark)

Green, Sara

2013-01-01

. The conceptual repertoire of Rheinberger’s historical epistemology offers important insights for an analysis of the modelling practice. I illustrate this with a case study on network modeling in systems biology where engineering approaches are applied to the study of biological systems. I shall argue...

A distributed approach for parameters estimation in System Biology models

International Nuclear Information System (INIS)

Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

2009-01-01

Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

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

Science.gov (United States)

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.

Biological effects of particles from the paris subway system.

Science.gov (United States)

Bachoual, Rafik; Boczkowski, Jorge; Goven, Delphine; Amara, Nadia; Tabet, Lyes; On, Dinhill; Leçon-Malas, Véronique; Aubier, Michel; Lanone, Sophie

2007-10-01

Particulate matter (PM) from atmospheric pollution can easily deposit in the lungs and induce recruitment of inflammatory cells, a source of inflammatory cytokines, oxidants, and matrix metalloproteases (MMPs), which are important players in lung structural homeostasis. In many large cities, the subway system is a potent source of PM emission, but little is known about the biological effects of PM from this source. We performed a comprehensive study to evaluate the biological effects of PM sampled at two sites (RER and Metro) in the Paris subway system. Murine macrophages (RAW 264.7) and C57Bl/6 mice, respectively, were exposed to 0.01-10 microg/cm2 and 5-100 microg/mouse subway PM or reference materials [carbon black (CB), titanium dioxide (TiO2), or diesel exhaust particles (DEPs)]. We analyzed cell viability, production of cellular and lung proinflammatory cytokines [tumor necrosis factor alpha (TNFalpha), macrophage inflammatory protein (MIP-2), KC (the murin analog of interleukin-8), and granulocyte macrophage-colony stimulating factor (GM-CSF)], and mRNA or protein expression of MMP-2, -9, and -12 and heme oxygenase-1 (HO-1). Deferoxamine and polymixin B were used to evaluate the roles of iron and endotoxin, respectively. Noncytotoxic concentrations of subway PM (but not CB, TiO2, or DEPs) induced a time- and dose-dependent increase in TNFalpha and MIP-2 production by RAW 264.7 cells, in a manner involving, at least in part, PM iron content (34% inhibition of TNF production 8 h after stimulation of RAW 264.7 cells with 10 microg/cm2 RER particles pretreated with deferoxamine). Similar increased cytokine production was transiently observed in vivo in mice and was accompanied by an increased neutrophil cellularity of bronchoalveolar lavage (84.83+/-0.98% of polymorphonuclear neutrophils for RER-treated mice after 24 h vs 7.33+/-0.99% for vehicle-treated animals). Subway PM induced an increased expression of MMP-12 and HO-1 both in vitro and in vivo. PM from the

Disentangling physical and biological drivers of phytoplankton dynamics in a coastal system.

Science.gov (United States)

Cianelli, Daniela; D'Alelio, Domenico; Uttieri, Marco; Sarno, Diana; Zingone, Adriana; Zambianchi, Enrico; d'Alcalà, Maurizio Ribera

2017-11-20

This proof-of-concept study integrates the surface currents measured by high-frequency coastal radars with plankton time-series data collected at a fixed sampling point from the Mediterranean Sea (MareChiara Long Term Ecological Research site in the Gulf of Naples) to characterize the spatial origin of phytoplankton assemblages and to scrutinize the processes ruling their dynamics. The phytoplankton community generally originated from the coastal waters whereby species succession was mainly regulated by biological factors (life-cycle processes, species-specific physiological performances and inter-specific interactions). Physical factors, e.g. the alternation between coastal and offshore waters and the horizontal mixing, were also important drivers of phytoplankton dynamics promoting diversity maintenance by i) advecting species from offshore and ii) diluting the resident coastal community so as to dampen resource stripping by dominant species and thereby increase the numerical importance of rarer species. Our observations highlight the resilience of coastal communities, which may favour their persistence over time and the prevalence of successional events over small time and space scales. Although coastal systems may act differently from one another, our findings provide a conceptual framework to address physical-biological interactions occurring in coastal basins, which can be generalised to other areas.

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

Science.gov (United States)

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour

Systems Biology of the Immune Response to Live and Inactivated Dengue Virus Vaccines

Science.gov (United States)

2017-09-01

AWARD NUMBER: W81XWH-16-2-0031 TITLE: Systems Biology of the Immune Response to Live and Inactivated Dengue Virus Vaccines PRINCIPAL...SUBTITLE 5a. CONTRACT NUMBER Systems Biology of the Immune Response to Live and Inactivated Dengue Virus Vaccines 5b. GRANT NUMBER W81XWH-16-2-0031 5c...adaptive (T and B cell) responses will be measured using molecular and cellular approaches and the data analyzed using a systems biology approach

Complex systems of biological interest stability under ionising radiations

International Nuclear Information System (INIS)

Maclot, Sylvain

2014-01-01

This PhD work presents the study of stability of molecular systems of biological interest in the gas phase after interaction with ionising radiations. The use of ionising radiation can probe the physical chemistry of complex systems at the molecular scale and thus consider their intrinsic properties. Beyond the fundamental aspect, this work is part of the overall understanding of radiation effects on living organisms and in particular the use of ionizing radiation in radiotherapy. Specifically, this study focused on the use of low-energy multiply charged ions (tens of keV) provided by the GANIL (Caen), which includes most of the experiments presented. In addition, experiments using VUV photons were also conducted at synchrotron ELETTRA (Trieste, Italy). The bio-molecular systems studied are amino acids and nucleic acid constituents. Using an experimental crossed beams device allows interaction between biomolecules and ionising radiation leads mainly to the ionization and fragmentation of the system. The study of its relaxation dynamics is by time-of-flight mass spectrometry coupled to a coincidences measurements method. It is shown that an approach combining experiment and theory allows a detailed study of the fragmentation dynamics of complex systems. The results indicate that fragmentation is generally governed by the Coulomb repulsion but the intramolecular rearrangements involve specific relaxation mechanisms. (author) [fr

Interactions of nanomaterials and biological systems: implications to personalized nanomedicine☆

Science.gov (United States)

Zhang, Xue-Qing; Xu, Xiaoyang; Bertrand, Nicolas; Pridgen, Eric; Swami, Archana; Farokhzad, Omid C.

2012-01-01

The application of nanotechnology to personalized medicine provides an unprecedented opportunity to improve the treatment of many diseases. Nanomaterials offer several advantages as therapeutic and diagnostic tools due to design flexibility, small sizes, large surface-to-volume ratio, and ease of surface modification with multivalent ligands to increase avidity for target molecules. Nanomaterials can be engineered to interact with specific biological components, allowing them to benefit from the insights provided by personalized medicine techniques. To tailor these interactions, a comprehensive knowledge of how nanomaterials interact with biological systems is critical. Herein, we discuss how the interactions of nanomaterials with biological systems can guide their design for diagnostic, imaging and drug delivery purposes. A general overview of nanomaterials under investigation is provided with an emphasis on systems that have reached clinical trials. Finally, considerations for the development of personalized nanomedicines are summarized such as the potential toxicity, scientific and technical challenges in fabricating them, and regulatory and ethical issues raised by the utilization of nanomaterials. PMID:22917779

Biological Detection System Technologies Technology and Industrial Base Study. A Primer on Biological Detection Technologies

National Research Council Canada - National Science Library

2001-01-01

.... and Canadian military personnel. In light of these concerns both defense departments have increased efforts to develop and field biological agent detection systems to help protect their military forces and fixed assets...

Biological and geophysical feedbacks with fire in the Earth system

Science.gov (United States)

Archibald, S.; Lehmann, C. E. R.; Belcher, C. M.; Bond, W. J.; Bradstock, R. A.; Daniau, A.-L.; Dexter, K. G.; Forrestel, E. J.; Greve, M.; He, T.; Higgins, S. I.; Hoffmann, W. A.; Lamont, B. B.; McGlinn, D. J.; Moncrieff, G. R.; Osborne, C. P.; Pausas, J. G.; Price, O.; Ripley, B. S.; Rogers, B. M.; Schwilk, D. W.; Simon, M. F.; Turetsky, M. R.; Van der Werf, G. R.; Zanne, A. E.

2018-03-01

Roughly 3% of the Earth’s land surface burns annually, representing a critical exchange of energy and matter between the land and atmosphere via combustion. Fires range from slow smouldering peat fires, to low-intensity surface fires, to intense crown fires, depending on vegetation structure, fuel moisture, prevailing climate, and weather conditions. While the links between biogeochemistry, climate and fire are widely studied within Earth system science, these relationships are also mediated by fuels—namely plants and their litter—that are the product of evolutionary and ecological processes. Fire is a powerful selective force and, over their evolutionary history, plants have evolved traits that both tolerate and promote fire numerous times and across diverse clades. Here we outline a conceptual framework of how plant traits determine the flammability of ecosystems and interact with climate and weather to influence fire regimes. We explore how these evolutionary and ecological processes scale to impact biogeochemical and Earth system processes. Finally, we outline several research challenges that, when resolved, will improve our understanding of the role of plant evolution in mediating the fire feedbacks driving Earth system processes. Understanding current patterns of fire and vegetation, as well as patterns of fire over geological time, requires research that incorporates evolutionary biology, ecology, biogeography, and the biogeosciences.

Biology and Mechanics of Blood Flows Part I: Biology

CERN Document Server

Thiriet, Marc

2008-01-01

Biology and Mechanics of Blood Flows presents the basic knowledge and state-of-the-art techniques necessary to carry out investigations of the cardiovascular system using modeling and simulation. Part I of this two-volume sequence, Biology, addresses the nanoscopic and microscopic scales. The nanoscale corresponds to the scale of biochemical reaction cascades involved in cell adaptation to mechanical stresses among other stimuli. The microscale is the scale of stress-induced tissue remodeling associated with acute or chronic loadings. The cardiovascular system, like any physiological system, has a complicated three-dimensional structure and composition. Its time dependent behavior is regulated, and this complex system has many components. In this authoritative work, the author provides a survey of relevant cell components and processes, with detailed coverage of the electrical and mechanical behaviors of vascular cells, tissues, and organs. Because the behaviors of vascular cells and tissues are tightly coupl...

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

Science.gov (United States)

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Frontiers in mathematical biology

CERN Document Server

1994-01-01

Volume 100, which is the final volume of the LNBM series serves to commemorate the acievements in two decades of this influential collection of books in mathematical biology. The contributions, by the leading mathematical biologists, survey the state of the art in the subject, and offer speculative, philosophical and critical analyses of the key issues confronting the field. The papers address fundamental issues in cell and molecular biology, organismal biology, evolutionary biology, population ecology, community and ecosystem ecology, and applied biology, plus the explicit and implicit mathematical challenges. Cross-cuttting issues involve the problem of variation among units in nonlinear systems, and the related problems of the interactions among phenomena across scales of space, time and organizational complexity.

Notions of radiation chemistry in biological systems

International Nuclear Information System (INIS)

Mastro, N.L. del.

1989-10-01

The present paper examines some aspects of the direct and indirect biological radiation effects: pair formation, free radicals, superoxide ion, hydrogen peroxide, hydroxyl radical, oxygen singlet together with the endogen radioprotector mechanisms of organisms and the ways in which an improved radioresistance of biochemical systems can be achieved. (author) [pt

Distribution and Biological Effects of Nanoparticles in the Reproductive System.

Science.gov (United States)

Liu, Ying; Li, Hongxia; Xiao, Kai

2016-01-01

Nanoparticles have shown great potential in biomedical applications such as imaging probes and drug delivery. However, the increasing use of nanoparticles has raised concerns about their adverse effects on human health and environment. Reproductive tissues and gametes represent highly delicate biological systems with the essential function of transmitting genetic information to the offspring, which is highly sensitive to environmental toxicants. This review aims to summarzie the penetration of physiological barriers (blood-testis barrier and placental barrier), distribution and biological effects of nanoparticles in the reproductive system, which is essential to control the beneficial effects of nanoparticles applications and to avoid their adverse effects on the reproductive system. We referred to a large number of relevant peer-reviewed research articles about the reproductive toxicity of nanoparticles. The comprehensive information was summarized into two parts: physiological barrier penetration and biological effects of nanoparticles in male or female reproductive system; distribution and metabolism of nanoparticles in the reproductive system. The representative examples were also presented in four tables. The in vitro and in vivo studies imply that some nanoparticles are able to cross the blood-testis barrier or placental barrier, and their penetration depends on the physicochemical characteristics of nanoparticles (e.g., composition, shape, particle size and surface coating). The toxicity assays indicate that nanoparticles might induce adverse physiological effects and impede fertility or embryogenesis. The barrier penetration, adverse physiological effects, distribution and metabolism are closely related to physicochemical characteristics of nanoparticles. Further systematic and mechanistic studies using well-characterized nanoparticles, relevant administration routes, and doses relevant to the expected exposure level are required to improve our

MORE: mixed optimization for reverse engineering--an application to modeling biological networks response via sparse systems of nonlinear differential equations.

Science.gov (United States)

Sambo, Francesco; de Oca, Marco A Montes; Di Camillo, Barbara; Toffolo, Gianna; Stützle, Thomas

2012-01-01

Reverse engineering is the problem of inferring the structure of a network of interactions between biological variables from a set of observations. In this paper, we propose an optimization algorithm, called MORE, for the reverse engineering of biological networks from time series data. The model inferred by MORE is a sparse system of nonlinear differential equations, complex enough to realistically describe the dynamics of a biological system. MORE tackles separately the discrete component of the problem, the determination of the biological network topology, and the continuous component of the problem, the strength of the interactions. This approach allows us both to enforce system sparsity, by globally constraining the number of edges, and to integrate a priori information about the structure of the underlying interaction network. Experimental results on simulated and real-world networks show that the mixed discrete/continuous optimization approach of MORE significantly outperforms standard continuous optimization and that MORE is competitive with the state of the art in terms of accuracy of the inferred networks.

International Conference on Intelligent Systems for Molecular Biology (ISMB)

Energy Technology Data Exchange (ETDEWEB)

Goldberg, Debra; Hibbs, Matthew; Kall, Lukas; Komandurglayavilli, Ravikumar; Mahony, Shaun; Marinescu, Voichita; Mayrose, Itay; Minin, Vladimir; Neeman, Yossef; Nimrod, Guy; Novotny, Marian; Opiyo, Stephen; Portugaly, Elon; Sadka, Tali; Sakabe, Noboru; Sarkar, Indra; Schaub, Marc; Shafer, Paul; Shmygelska, Olena; Singer, Gregory; Song, Yun; Soumyaroop, Bhattacharya; Stadler, Michael; Strope, Pooja; Su, Rong; Tabach, Yuval; Tae, Hongseok; Taylor, Todd; Terribilini, Michael; Thomas, Asha; Tran, Nam; Tseng, Tsai-Tien; Vashist, Akshay; Vijaya, Parthiban; Wang, Kai; Wang, Ting; Wei, Lai; Woo, Yong; Wu, Chunlei; Yamanishi, Yoshihiro; Yan, Changhui; Yang, Jack; Yang, Mary; Ye, Ping; Zhang, Miao

2009-12-29

The Intelligent Systems for Molecular Biology (ISMB) conference has provided a general forum for disseminating the latest developments in bioinformatics on an annual basis for the past 13 years. ISMB is a multidisciplinary conference that brings together scientists from computer science, molecular biology, mathematics and statistics. The goal of the ISMB meeting is to bring together biologists and computational scientists in a focus on actual biological problems, i.e., not simply theoretical calculations. The combined focus on "intelligent systems" and actual biological data makes ISMB a unique and highly important meeting, and 13 years of experience in holding the conference has resulted in a consistently well organized, well attended, and highly respected annual conference. The ISMB 2005 meeting was held June 25-29, 2005 at the Renaissance Center in Detroit, Michigan. The meeting attracted over 1,730 attendees. The science presented was exceptional, and in the course of the five-day meeting, 56 scientific papers, 710 posters, 47 Oral Abstracts, 76 Software demonstrations, and 14 tutorials were presented. The attendees represented a broad spectrum of backgrounds with 7% from commercial companies, over 28% qualifying for student registration, and 41 countries were represented at the conference, emphasizing its important international aspect. The ISMB conference is especially important because the cultures of computer science and biology are so disparate. ISMB, as a full-scale technical conference with refereed proceedings that have been indexed by both MEDLINE and Current Contents since 1996, bridges this cultural gap.

Modeling biological pathway dynamics with timed automata.

Science.gov (United States)

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Creation of computer system for simulation nanoparticles interaction with biological objects concept

International Nuclear Information System (INIS)

Sarana, Yu.V.; Smol'nik, N.S.; Mel'nov, S.B.

2014-01-01

Main problem of nanotoxicology is that biological effects of most nanoparticles are unknown. So creation of system predictioning nanoparticles biological activity spectra is a great challenge. Here we give a concept of such system creation; it includes 6 stages realization of which help to implement nanotechnology most safely and effectively. (authors)

Implied Movement in Static Images Reveals Biological Timing Processing

Directory of Open Access Journals (Sweden)

Francisco Carlos Nather

2015-08-01

Full Text Available Visual perception is adapted toward a better understanding of our own movements than those of non-conspecifics. The present study determined whether time perception is affected by pictures of different species by considering the evolutionary scale. Static (“S” and implied movement (“M” images of a dog, cheetah, chimpanzee, and man were presented to undergraduate students. S and M images of the same species were presented in random order or one after the other (S-M or M-S for two groups of participants. Movement, Velocity, and Arousal semantic scales were used to characterize some properties of the images. Implied movement affected time perception, in which M images were overestimated. The results are discussed in terms of visual motion perception related to biological timing processing that could be established early in terms of the adaptation of humankind to the environment.

Conceptual Model-based Systems Biology: mapping knowledge and discovering gaps in the mRNA transcription cycle.

Directory of Open Access Journals (Sweden)

Judith Somekh

2012-12-01

Full Text Available 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.

Synthetic Biology: Advancing Biological Frontiers by Building Synthetic Systems

OpenAIRE

Chen, Yvonne Yu-Hsuan; Galloway, Kate E; Smolke, Christina D

2012-01-01

Advances in synthetic biology are contributing to diverse research areas, from basic biology to biomanufacturing and disease therapy. We discuss the theoretical foundation, applications, and potential of this emerging field.

Degradation characteristics of 2,4-dichlorophenoxyacetic acid in electro-biological system

Energy Technology Data Exchange (ETDEWEB)

Zhang, JingLi, E-mail: jinglizhangczp@126.com [Tianjin Key Laboratory of Aquatic Science and Technology, Tianjin Institute of Urban Construction, Tianjin 300384 (China); Cao, ZhanPing; Zhang, HongWei [School of Environmental and Chemical Engineering, Tianjin Polytechnic University, Tianjin 300387 (China); Zhao, LianMei [Tianjin Key Laboratory of Aquatic Science and Technology, Tianjin Institute of Urban Construction, Tianjin 300384 (China); Sun, XuDong; Mei, Feng [School of Environmental and Chemical Engineering, Tianjin Polytechnic University, Tianjin 300387 (China)

2013-11-15

Highlights: • The 2,4-D reductive degradation was studied in an electro-biological system. • The electric auxiliary accelerates 2,4-D microbial degradation. • A electron transfer is achieved between the electrode, bacteria and the pollutants. • The paper provides a promising way for the degradation of persistent organics. -- Abstract: The reductive degradation of 2,4-dichlorophenoxyacetic acid (2,4-D) was studied in an electro-biological system, a biological system and an electric catalytic system, respectively. Electrochemical characteristics were monitored by cyclic voltammetry and the intermediate products of 2,4-D degradation were determined by high speed liquid chromatography (HPLC). The results showed that all 2,4-D degradations in the three systems conformed to the kinetics characteristics of one-order reaction, and the degradation kinetics constants were 28.74 × 10{sup −2} h{sup −1}, 19.73 × 10{sup −2} h{sup −1} and 3.54 × 10{sup −2} h{sup −1}, respectively. The kinetics constant in the electro-biological system was higher than the sum in the other two systems by 19%. The electrochemical assistance provided the electrons and accelerated the electron transfer rate in the microbial degradation of 2,4-D. The degradation resulted from the microbial reduction strengthened by the electrochemical assistance. The electron transfer existed between the electrode, cytochrome, NAD and the pollutants. A long-range electron transfer process could be achieved on the multi-phase interfaces between the electrode, bacteria and the pollutants.

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

Science.gov (United States)

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.

The Influence of Gene Expression Time Delays on Gierer–Meinhardt Pattern Formation Systems

KAUST Repository

Seirin Lee, S.

2010-03-23

There are numerous examples of morphogen gradients controlling long range signalling in developmental and cellular systems. The prospect of two such interacting morphogens instigating long range self-organisation in biological systems via a Turing bifurcation has been explored, postulated, or implicated in the context of numerous developmental processes. However, modelling investigations of cellular systems typically neglect the influence of gene expression on such dynamics, even though transcription and translation are observed to be important in morphogenetic systems. In particular, the influence of gene expression on a large class of Turing bifurcation models, namely those with pure kinetics such as the Gierer-Meinhardt system, is unexplored. Our investigations demonstrate that the behaviour of the Gierer-Meinhardt model profoundly changes on the inclusion of gene expression dynamics and is sensitive to the sub-cellular details of gene expression. Features such as concentration blow up, morphogen oscillations and radical sensitivities to the duration of gene expression are observed and, at best, severely restrict the possible parameter spaces for feasible biological behaviour. These results also indicate that the behaviour of Turing pattern formation systems on the inclusion of gene expression time delays may provide a means of distinguishing between possible forms of interaction kinetics. Finally, this study also emphasises that sub-cellular and gene expression dynamics should not be simply neglected in models of long range biological pattern formation via morphogens. © 2010 Society for Mathematical Biology.

SBMLeditor: effective creation of models in the Systems Biology Markup language (SBML).

Science.gov (United States)

Rodriguez, Nicolas; Donizelli, Marco; Le Novère, Nicolas

2007-03-06

The need to build a tool to facilitate the quick creation and editing of models encoded in the Systems Biology Markup language (SBML) has been growing with the number of users and the increased complexity of the language. SBMLeditor tries to answer this need by providing a very simple, low level editor of SBML files. Users can create and remove all the necessary bits and pieces of SBML in a controlled way, that maintains the validity of the final SBML file. SBMLeditor is written in JAVA using JCompneur, a library providing interfaces to easily display an XML document as a tree. This decreases dramatically the development time for a new XML editor. The possibility to include custom dialogs for different tags allows a lot of freedom for the editing and validation of the document. In addition to Xerces, SBMLeditor uses libSBML to check the validity and consistency of SBML files. A graphical equation editor allows an easy manipulation of MathML. SBMLeditor can be used as a module of the Systems Biology Workbench. SBMLeditor contains many improvements compared to a generic XML editor, and allow users to create an SBML model quickly and without syntactic errors.

Uncovering the underlying physical mechanisms of biological systems via quantification of landscape and flux

International Nuclear Information System (INIS)

Xu Li; Chu Xiakun; Yan Zhiqiang; Zheng Xiliang; Zhang Kun; Zhang Feng; Yan Han; Wu Wei; Wang Jin

2016-01-01

In this review, we explore the physical mechanisms of biological processes such as protein folding and recognition, ligand binding, and systems biology, including cell cycle, stem cell, cancer, evolution, ecology, and neural networks. Our approach is based on the landscape and flux theory for nonequilibrium dynamical systems. This theory provides a unifying principle and foundation for investigating the underlying mechanisms and physical quantification of biological systems. (topical review)

Further explorations of the facing bias in biological motion perception: perspective cues, observer sex, and response times.

Directory of Open Access Journals (Sweden)

Ben Schouten

Full Text Available The human visual system has evolved to be highly sensitive to visual information about other persons and their movements as is illustrated by the effortless perception of point-light figures or 'biological motion'. When presented orthographically, a point-light walker is interpreted in two anatomically plausible ways: As 'facing the viewer' or as 'facing away' from the viewer. However, human observers show a 'facing bias': They perceive such a point-light walker as facing towards them in about 70-80% of the cases. In studies exploring the role of social and biological relevance as a possible account for the facing bias, we found a 'figure gender effect': Male point-light figures elicit a stronger facing bias than female point-light figures. Moreover, we also found an 'observer gender effect': The 'figure gender effect' was stronger for male than for female observers. In the present study we presented to 11 males and 11 females point-light walkers of which, very subtly, the perspective information was manipulated by modifying the earlier reported 'perspective technique'. Proportions of 'facing the viewer' responses and reaction times were recorded. Results show that human observers, even in the absence of local shape or size cues, easily pick up on perspective cues, confirming recent demonstrations of high visual sensitivity to cues on whether another person is potentially approaching. We also found a consistent difference in how male and female observers respond to stimulus variations (figure gender or perspective cues that cause variations in the perceived in-depth orientation of a point-light walker. Thus, the 'figure gender effect' is possibly caused by changes in the relative locations and motions of the dots that the perceptual system tends to interpret as perspective cues. Third, reaction time measures confirmed the existence of the facing bias and recent research showing faster detection of approaching than receding biological motion.

Systems biology of Microbial Communities

Energy Technology Data Exchange (ETDEWEB)

Navid, A; Ghim, C; Fenley, A; Yoon, S; Lee, S; Almaas, E

2008-04-11

Microbes exist naturally in a wide range of environments, spanning the extremes of high acidity and high temperature to soil and the ocean, in communities where their interactions are significant. We present a practical discussion of three different approaches for modeling microbial communities: rate equations, individual-based modeling, and population dynamics. We illustrate the approaches with detailed examples. Each approach is best fit to different levels of system representation, and they have different needs for detailed biological input. Thus, this set of approaches is able to address the operation and function of microbial communities on a wide range of organizational levels.

6,7-dimethoxy-coumarin as a probe of hydration dynamics in biologically relevant systems

Science.gov (United States)

Ghose, Avisek; Amaro, Mariana; Kovaricek, Petr; Hof, Martin; Sykora, Jan

2018-04-01

Coumarin derivatives are well known fluorescence reporters for investigating biological systems due to their strong micro-environment sensitivity. Despite having wide range of environment sensitive fluorescence probes, the potential of 6,7-dimethoxy-coumarin has not been studied extensively so far. With a perspective of its use in protein studies, namely using the unnatural amino acid technology or as a substrate for hydrolase enzymes, we study acetyloxymethyl-6,7-dimethoxycoumarin (Ac-DMC). We investigate the photophysics and hydration dynamics of this dye in aerosol-OT (AOT) reverse micelles at various water contents using the time dependent fluorescence shift (TDFS) method. The TDFS response in AOT reverse micelles from water/surfactant ratio of 0 to 20 confirms its sensitivity towards the hydration and mobility of its microenvironment. Moreover, we show that the fluorophore can be efficiently quenched by halide ions. Hence, we conclude that the 6,7-dimethoxy-methylcoumarin fluorophore is useful for studying hydration parameters in biologically relevant systems.

Dynamical systems in population biology

CERN Document Server

Zhao, Xiao-Qiang

2017-01-01

This research monograph provides an introduction to the theory of nonautonomous semiflows with applications to population dynamics. It develops dynamical system approaches to various evolutionary equations such as difference, ordinary, functional, and partial differential equations, and pays more attention to periodic and almost periodic phenomena. The presentation includes persistence theory, monotone dynamics, periodic and almost periodic semiflows, basic reproduction ratios, traveling waves, and global analysis of prototypical population models in ecology and epidemiology. Research mathematicians working with nonlinear dynamics, particularly those interested in applications to biology, will find this book useful. It may also be used as a textbook or as supplementary reading for a graduate special topics course on the theory and applications of dynamical systems. Dr. Xiao-Qiang Zhao is a University Research Professor at Memorial University of Newfoundland, Canada. His main research interests involve applied...

Systems Biology of Glucocorticoids in Muscle Disease

Science.gov (United States)

2010-10-01

Introduction Duchenne muscular dystrophy (DMD) is the most common and incurable muscular dystrophy of childhood. Muscle regeneration fails with...SUBJECT TERMS Duchenne Muscular dystrophy , Glucocorticoids, Systems biology, Drug mechanism 16. SECURITY CLASSIFICATION OF: U 17. LIMITATION...better targeted and more effective therapies for Duchenne muscular dystrophy dynamically. This MDA grant proposal is led by Dr. Eric Hoffman, and it

Measuring the Earth System in a Time of Global Environmental Change with Image Spectroscopy

Science.gov (United States)

Green, Robert O.

2005-01-01

Measuring the Earth system in a time of global environmental change. Imaging Spectroscopy enables remote measurement. Remote Measurement determination of the properties of the Earth's surface and atmosphere through the physics, chemistry and biology of the interaction of electromagnetic energy with matter.

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

Directory of Open Access Journals (Sweden)

Hemminger Bradley M

2009-08-01

Full Text Available Abstract 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

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

Science.gov (United States)

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