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'''Systems biology''' is an academic field that seeks to integrate different levels of information to understand how biological [[system]]s function. By studying the relationships and interactions between various parts of a biological system (e.g., gene and protein networks involved in [[cell signaling]], [[metabolic]] pathways, [[organelle]]s, [[Cell (biology)|cell]]s, [[physiology|physiological systems]], [[organism]]s, etc.) it is hoped that eventually an understandable model of the whole system can be developed. Since the mathematical and analytical foundation of systems biology is far from being perfect, computer [[simulation]] and [[heuristic]]s are often used as research methods.
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'''Systems biology''', a field of study in the [[biosciences]], focuses on the systematic study of [[complex]] interactions in [[biological systems]]. Particularly from 2000 onwards, the term is used widely in the [[biosciences]], and in a variety of contexts.
   
==History==
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== Overview ==
In 1952, the British neurophysiologists and nobel prize winners [[Alan Lloyd Hodgkin]] and [[Andrew Fielding Huxley]] constructed a mathematical model of the nerve cell. In 1960, [http://noble.physiol.ox.ac.uk/People/DNoble/ Denis Noble] developed the first computer model of a beating heart. Systems biologists invoke these pioneering pieces of work as illustrative of the systems biology project. The possibility of performing systems biology increased around the year 2000 with the completion of various genome projects and the proliferation of genomic and proteomic data, and the accompanying advances in experimental methodology.
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Systems biology can be considered from a number of different aspects:
   
The experimental procedures available during the 20th century necessitated 'one protein at a time' projects which have been the mainstay of molecular biology since its inception. Some [[biologists]] and [[biochemists]] believe that this approach of individual biomolecules has fostered a ''reductionist'' perspective, and that it is just the first step toward an understanding of the overall (integrated) life process, which can only be properly addressed from a systems biology persepective. However, the current advances in biology (coming from [[bioinformatics]] in the [[post genomic era]]) are a direct result of the successes of 20th century molecular biology, and it is clear to most biologists that individual biomolecules or complexes will always be the central focus in drug development and will continue indefinitely to play a role in developing the higher-level understanding which systems biology claims to pursue.
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* Some sources discuss systems biology as a '''field of study''', particularly, the study of the interactions between the components of ''biological systems'', and how these interactions give rise to the function and behavior of that system (for example, the [[enzymes]] and [[metabolites]] in a [[metabolic pathway]])<ref name = "defandperspectives">{{cite conference | last = Snoep J.L. and Westerhoff H.V. | coauthors = Alberghina L. and Westerhoff H.V. (Eds.)| title = From isolation to integration, a systems biology approach for building the Silicon Cell | booktitle = Systems Biology: Definitions and Perspectives | publisher = Springer-Verlag | date = 2005. | pages = p7}}</ref><ref name = "isbdef">{{cite web | url = http://www.systemsbiology.org/Intro_to_ISB_and_Systems_Biology/Systems_Biology_--_the_21st_Century_Science | title = Systems Biology - the 21st Century Science }}</ref>.
   
==Approaches==
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* Other sources consider systems biology as a '''[[paradigm]]''', usually defined in antithesis to the so-called [[reductionist]] paradigm, although fully consistent with the [[scientific method]]. The distinction between the two paradigms is referred to in these quotations:
There are two major and complimentary focuses in systems biology:
 
* Quantitative Systems Biology - otherwise known as "systems biology measurement", it focuses on measuring and monitoring biological systems on the system level.
 
* Systems Biology Modeling - focuses on mapping, explaining and predicting systemic biological processes and events through the building of computational and visualization models.
 
   
===Quantitative systems biology===
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:''"The reductionist approach has successfully identified most of the components and many of the interactions but, unfortunately, offers no convincing concepts or methods to understand how system properties emerge...the pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration with mathematical models"'' [[Science (journal)|Science]]<ref>Sauer, U. et al. "Getting Closer to the Whole Picture" [[Science (journal)]] '''316''' 550 17 April 2007</ref>
This subfield is concerned with quantifying molecular reponses in a biological system to a given perturbation.
 
   
Some typical technology platforms are:
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:''"Systems biology...is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different....It means changing our philosophy, in the full sense of the term"'' [[Denis Noble]]<ref>[[Denis Noble]] ''The Music of Life'' [[Oxford University Press]] (2006) p21</ref>
* Gene expression measurement through [[DNA microarray]]s and [[Serial analysis of gene expression|SAGE]]
 
* Protein levels through [[two-dimensional gel electrophoresis]] and [[mass spectrometry]], including [[phosphoproteomics]] and other methods to detect chemically modified proteins.
 
* [[metabolomics]] for small-molecule [[metabolites]]
 
* [[glycomics]] for sugars
 
   
These are frequently combined with large scale perturbation methods, including gene-based ([[RNAi]], misexpression of wild type and mutant genes) and chemical approaches using small molecule libraries. Robots and automated sensors enable such large-scale experimentation and data acquisition.
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*Still other sources view systems biology in terms of the '''operational protocols used for performing research''', namely a cycle composed of theory, computational modelling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory.<ref name="bbsrc">{{cite web | url = http://www.bbsrc.ac.uk/science/areas/ebs/themes/main_sysbio.html | title = Systems Biology: Modelling, Simulation and Experimental Validation }}</ref><ref name="quant">{{cite conference | last = Kholodenko B.N., Bruggeman F.J., Sauro H.M. | coauthors = Alberghina L. and Westerhoff H.V.(Eds.)| title = Mechanistic and modular approaches to modeling and inference of cellular regulatory networks | booktitle = Systems Biology: Definitions and Perspectives | publisher = Springer-Verlag | date = 2005. | pages = p143}}</ref>. Since the objective is a model of the interactions in a system, the experimental techniques that most suit systems biology are those that are system-wide and attempt to be as complete as possible. Therefore, [[transcriptomics]], [[metabolomics]], [[proteomics]] and high-throughput techniques are used to collect quantitative data for the construction and validation of models.
   
These technologies are still emerging and many face problems that the larger the quantity of data produced, the lower the quality. A wide variety of quantitative scientists (computational biologists, statisticians, mathematicians, computer scientists, engineers, and physicists) are working to improve the quality of these approaches and to create, refine, and retest the models until the predicted behavior accurately reflects the phenotype seen.
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* Finally, some sources see it as a '''socioscientific phenomenon''' defined by the strategy of pursuing integration of complex data about the interactions in biological systems from diverse experimental sources using interdisciplinary tools and personnel.<!-- sourced below.-->
   
===Systems biology modeling===
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This variety of viewpoints is illustrative of the fact that systems biology refers to a cluster of peripherally overlapping concepts rather than a single well-delineated field. However the term has widespread currency and popularity as of [[2007]], with chairs and institutes of systems biology proliferating worldwide.
Using knowledge from molecular biology, the systems biologist can [[causal model|causally model]] the biological system of interest and propose hypotheses that explain a system's behavior. These hypotheses can then be confirmed and be used as a basis for [[mathematical model|mathematically model]] the system. The difference between the two modeling approaches is that causal models are used to explain the effects of a biological perterbations while mathematical models are used to predict how different perterbations in the system's environment affect the system.
 
   
== Applications ==
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==History==
Many predictions concerning the impact of genomics on health care have been proposed. For example, the development of novel therapeutics and the introduction of personalised treatments are conjectured and may become reality as a small number of biotechnology companies are using this cell-biology driven approach to the development of [[therapeutics]]. However, these predictions rely upon our ability to understand and quantify the roles that specific genes possess in the context of human and pathogen physiologies. The ultimate goal of systems biology is to derive the prerequisite knowledge and tools. Even with today's resources and expertise, this goal is immeasurably distant.
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Systems biology finds its roots in:
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*the quantitative modelling of [[enzyme kinetics]], a discipline that flourished between 1900 and 1970,
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*the simulations developed to study neurophysiology, and
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*[[control theory]], and [[cybernetics]].
   
==Systems biology people and places==
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One of the theorists who can be seen as a precursor of systems biology is [[Ludwig von Bertalanffy]] with his [[general systems theory]]. One of the first numerical simulations in biology was published in 1952 by the British neurophysiologists and nobel prize winners [[Alan Lloyd Hodgkin]] and [[Andrew Fielding Huxley]], who constructed a mathematical model that explained the action potential propagating along the axon of a neuronal cell<ref>Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. ''J Physiol'', 117: 500-544.</ref>. Their model described a cellular function emerging from the interaction between two different molecular components, a potassium and a sodium channels, and can therefore be seen as the beginning of computational systems biology<ref>Le Novere (2007) The long journey to a Systems Biology of neuronal function. ''BMC Systems Biology'', 1: 28</ref>. In 1960, [[Denis Noble]] developed the first computer model of the heart pacemacker <ref>Noble D (1960) Cardiac action and pacemaker potentials based on the Hodgkin-Huxley equations. ''Nature'', 188: 495-497.</ref>.
A large number of organizations have been created to further the study of systems biology. Of note in the United States include the [[Institute for Systems Biology]] (ISB), the [http://biox.stanford.edu/ BioX] program at [[Stanford University]], the [http://sysbio.med.harvard.edu/ Department of Systems Biology] at [[Harvard Medical School]], the [http://www.sysbio.org/ Systems Biology Research Group] at the [[Pacific Northwest National Laboratory]], and the [http://www.vcu.edu/csbc/ Center for the Study of Biological Complexity]. The ISB is headed by [[Leroy Hood]] and is a non-profit research institute with a goal to identify strategies for predicting and preventing diseases such as [[cancer]], [[diabetes]] and [[AIDS]]. Work at PNNL is focused on a variety of research areas, including oxidative stress and radiation, cell signaling networks, and microbial communities. Internationally, some notable systems biology organizations include Japan's [http://www.sbi.jp/ Systems Biology Institute] headed by Hiroaki Kitano; UK's Biosystems Informatics Institute; Canada's [http://mededu.med.uottawa.ca/oisb/ Ottawa Institute of Systems Biology]; Swizerland's [http://www.imsb.ethz.ch Institute for Molecular Systems Biology] and [http://www.systemsx.ch SystemsX], Ireland's [http://www.systemsbiologyireland.org/ Systems Biology Ireland], and Russia's Institute for Systems Biology.
 
   
=== Systems biology societies and projects ===
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The 1960s and 1970s saw the development of several approaches to study complex molecular systems, such as the [[Metabolic Control Analysis]] and the [[biochemical systems theory]]. The successes of [[molecular biology]] throughout the [[1980]]s, coupled with a skepticism toward [[theoretical biology]], that then promised more than it achieved, caused the quantitative modelling of biological processes to become a somewhat minor field.
<!--Please do not place any ads in this section-->
 
* [http://www.issb.org International Society for Systems Biology] - the international systems biology society
 
* [http://www.msbf.mpg.de/ Munich Systems Biology Forum] - systems biology collaboration portal
 
* [http://www.ysbn.org Yeast Systems Biology Network] - systems biology researchers working in yeast
 
* [http://www.e-cell.org/ E-Cell Project] - international effort to model the cell in silico
 
* [http://www.physiome.org/ National Simulation Research Physiome Project] - international effort to model biology administered by the [[University of Washington]]
 
* [http://www.interaction-proteome.org/index.html Proteome Interaction Project]
 
   
=== Independent systems biology research centers ===
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However the birth of [[functional genomics]] in the [[1990]]s meant that large quantities of high quality data became available, while the computing power exploded, making more realistic models possible. In 1997, the group of [[Masaru Tomita]] published the first quantitative model of the metabolism of a whole (hypothetical) cell.
<!--Ordered by institute name -->
 
* [http://www.biiuk.com Biosystems Informatics Institute] (United Kingdom)
 
* [http://www.systemsbiology.org/ Institute for Systems Biology] (United States)
 
* [http://www.oisb.ca Ottawa Institute for Systems Biology] (Canada)
 
* [http://www.sbi.jp/ Systems Biology Institute] (Japan)
 
* [http://www.systemsx.ch/ SystemsX] (Switzerland)
 
* [http://www.vcell.org/ Virtual Cell Group] (United States)
 
   
=== Systems biology research groups ===
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Around the year 2000, when Institutes of Systems Biology were established in Seattle and Tokyo, systems biology emerged as a movement in its own right, spurred on by the completion of various [[genome projects]], the large increase in data from the [[omics]] (e.g. [[genomics]] and [[proteomics]]) and the accompanying advances in high-throughput experiments and [[bioinformatics]]. Since then, various research institutes dedicated to systems biology have been developed. As of summer 2006, due to a shortage of people in systems biology<ref name="careers">{{cite web
<!--Ordered by country then university -->
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| url = http://sciencecareers.sciencemag.org/career_development/previous_issues/articles/2006_03_03/working_the_systems/(parent)/158
* [http://www.sysbiolab.uottawa.ca/ Kaern Dynamical Systems Biology Lab] at [[University of Ottawa]] (Canada)
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| title = Working the Systems }}</ref> several doctoral training centres in systems biology have been established in many parts of the world.
* [http://www.systemsbiology.ie/ Systems Biology] at Hamilton Institute in the [[National University of Ireland, Maynooth]] (Ireland)
 
* [http://www.systemsbiologyireland.org/ Systems Biology Ireland] at [[Trinity College, Dublin]] (Ireland)
 
* [http://www.imsb.ethz.ch Institute for Molecular Systems Biology] at [[ETH Zürich]] (Switzerland)
 
* [http://cssb.icmb.utexas.edu Center for Systems and Synthetic Biology] at [[University of Texas at Austin]] (United States)
 
* [http://www.ebi.ac.uk/compneur/ Computational Neurobiology Group] at [[European Bioinformatics Institute]] (United Kingdom)
 
* [http://www.bioinformatics.ed.ac.uk/csb Computational Systems Biology] at [[University of Edinburgh]] (United Kingdom)
 
* [http://www.mcisb.org/ Manchester Centre for Integrative Systems Biology] at [[University of Manchester]] (United Kingdom)
 
* [http://www.shef.ac.uk/dcs/research/groups/compbio/ Computational Systems Biology] at [[University of Sheffield]] (United Kingdom)
 
* [http://www.cellnomica.netfirms.com/ Multicellular Systems Research at Cellnomica] (United States)
 
* [http://www.cellnomica.netfirms.com/ Cancer Modeling Project at Cellnomica] (United States)
 
* [http://www.phil.cmu.edu/projects/genegroup/ Computational Systems Biology Group] at [[Carnegie Mellon University]]
 
* [http://sysbio.med.harvard.edu/ Department of Systems Biology] at [[Harvard Medical School]] (United States)
 
* [http://vcp.med.harvard.edu/ Virtual Cell Program] at [[Harvard University]] (United States)
 
* [http://www.sys-bio.org Computational Systems Biology] at the Keck Institute (United States)
 
* [http://bionetgen.lanl.gov/ Cell Signaling Team] at [[Los Alamos National Laboratory]] (United States)
 
* [http://csbi.mit.edu/ Computational and Systems Biology Initiative] at [[MIT]] (United States)
 
* [http://www.sysbio.org/ Systems Biology] at [[Pacific Northwest National Laboratory]] (United States)
 
* [http://systemsbiology.ucsd.edu/ Systems Biology Research Group] at [[UCSD]] (United States)
 
* [http://bme.virginia.edu/csbl/ Computational Systems Biology Lab] at [[University of Virginia]] (United States)
 
* [http://www.vcu.edu/csbc/ Center for the Study of Biological Complexity] at [[Virginia Commonwealth University]] (United States)
 
* [http://www.genomedynamics.org Center for Genome Dynamics] at [[The Jackson Laboratory]] (United States)
 
   
=== Systems biology researchers ===
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== Techniques associated with systems biology ==
<!-- organized by researcher last name -->
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According to the interpretation of System Biology as the ability to obtain, integrate and analyze complex data from multiple experimental sources using interdisciplinary tools, some typical technology platforms are:
* [http://www.weizmann.ac.il/mcb/UriAlon/ Alon, Uri] at [[Weizmann Institute of Science]]
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* [[Transcriptomics]]: whole cell or tissue gene expression measurements by [[DNA microarray]]s or [[Serial analysis of gene expression|SAGE]]
* [http://genomics.lbl.gov/ Arkin, Adam] at [[Lawrence Berkeley National Laboratory]]
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* [[Proteomics]]: complete identification of proteins and protein expression patterns of a cell or tissue through [[two-dimensional gel electrophoresis]] and [[mass spectrometry]] or multi-dimensional protein identification techniques (advanced [[HPLC]] systems coupled with [[mass spectrometry]]). Sub disciplines include [[phosphoproteomics]], [[glycoproteomics]] and other methods to detect chemically modified proteins.
* [http://www.phys.huji.ac.il/bio_physics/nathalie/ Balaban, Nathalie Questembert] at [[Hebrew University of Jerusalem]]
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* [[Metabolomics]]: identification and measurement of all small-molecules [[metabolites]] within a cell or tissue
* [http://www.public.asu.edu/~cbaral/ Baral, Chatta] at [[Arizona State University]]
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* [[Glycomics]]: identification of the entirety of all carbohydrates in a cell or tissue.
* [http://www.utoronto.ca/boonelab/ Boone, Charlie] at [[University of Toronto]]
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In addition to the identification and quantification of the above given molecules further techniques analyze the dynamics and interactions within a cell. This includes:
* [http://cluzel.uchicago.edu/ Cluzel, Phillippe] at [[University of Chicago]]
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* [[Interactomics]] which is used mostly in the context of protein-protein interaction but in theory encompasses interactions between all molecules within a cell
* [http://www.bu.edu/abl Collins, Jim] at [[Boston University]]
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*[[Fluxomics]], which deals with the dynamic changes of molecules within a cell over time
* [http://www.molbio2.princeton.edu/index.php?option=content&task=view&id=206/ Cox, Edward] at [[Princeton University]]
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* [[Biomics]]: systems analysis of the [[biome]].
* [http://www.its.caltech.edu/~mirsky/ Davidson, Eric] at [[CalTech]]
 
* [http://www.elowitz.caltech.edu/ Elowitz, Michael] at [[CalTech]]
 
* [http://web.mit.edu/be/people/endy.htm Endy, Drew] at [[MIT]]
 
* [http://www.stanford.edu/group/ferrelllab/ Ferrell, Jim] at [[Stanford University]]
 
* [http://www.immunologia.unibo.it/ Franceschi, Claudio] at [[University of Bologna]]
 
* [http://hugheslab.med.utoronto.ca/ Hughes, Tim] at [[University of Toronto]]
 
* [http://chianti.ucsd.edu/idekerlab/index.html Ideker, Trey] at [[UCSD]]
 
* [http://www.mssm.edu/labs/iyengar/ Iyengar, Ravi] at [[Mount Sinai School of Medicine]]
 
* [http://microarray.icmb.utexas.edu/ Iyer, Vishwanath] at [[University of Texas]]
 
* [http://www.ee.kth.se/~jacobsen Jacobsen, Elling W.] at [[KTH]]
 
* [http://www.molgen.mpg.de/~ag_klipp/ Klipp, Edda] at [[Max Planck Institute]]
 
* [http://www.rockefeller.edu/labheads/leibler/leibler-lab.php/ Leibler, Stanislas] at [[Rockefeller University]]
 
* [http://polaris.icmb.utexas.edu/home.html Marcotte, Edward] at [[University of Texas]]
 
* [http://caulo.stanford.edu/usr/hm/ McAdams, Harley] at [[Stanford University]]
 
* [http://mendes.vbi.vt.edu/tiki-index.php Mendes, Pedro] at [[Virginia Tech]]
 
* [http://mcb.harvard.edu/o%27shea/ O'Shea, Erin] at [[Harvard]]
 
* [http://math.berkeley.edu/~lpachter/ Pachter, Lior] at [[UC Berkeley]]
 
* [http://systemsbiology.ucsd.edu/ Palsson, Bernhard Ø.] at [[UCSD]]
 
* [http://thebigone.stanford.edu/ Quake, Stephen] at [[Stanford University]]
 
* [http://www.cubic.uni-koeln.de/ Schomburg, Dietmar] at [[Cologne University]]
 
* [http://mendel.stanford.edu/SidowLab/ Sidow, Arend] at [[Stanford University]]
 
* [http://www.ornl.gov/ment/ Simpson, Michael] at [[Oak Ridge National Laboratory]]
 
* [http://www.yale.edu/snyder/ Snyder, Michael] at [[Yale University]]
 
* [http://biology.caltech.edu/Members/Stathopoulos Stathopoulos, Angelike] at [[CalTech]]
 
* [http://www.ncbs.res.in/mukund/groups_mukund.htm Thattai, Mukund] at [[Tata Institute of Fundamental Research]]
 
* [http://mit.edu/tidor/ Tidor, Bruce] at [[MIT]]
 
* [http://mpf.biol.vt.edu/ Tyson, John] at [[Virginia Tech]]
 
* [http://web.mit.edu/biophysics van Oudenaarden, Alexander] at [[MIT]]
 
* [http://vidal.dfci.harvard.edu/ Vidal, Marc] at [[Dana Farber Cancer Institute]]
 
* [http://www.ucsf.edu/jswlab/ Weissman, Jonathan] at [[UCSF]]
 
* [http://www.cellnomica.netfirms.com/ Werner, Eric] at [http://cellnomica.netfirms.com/ Cellnomica]
 
* [http://web.wi.mit.edu/young/ Young, Richard] at [[MIT]]
 
   
=== Systems biology companies ===
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The investigations are frequently combined with large scale perturbation methods, including gene-based ([[RNAi]], mis-expression of wild type and mutant genes) and chemical approaches using small molecule libraries. Robots and automated sensors enable such large-scale experimentation and data acquisition. These technologies are still emerging and many face problems that the larger the quantity of data produced, the lower the quality. A wide variety of quantitative scientists (computational biologists, statisticians, mathematicians, computer scientists, engineers, and physicists) are working to improve the quality of these approaches and to create, refine, and retest the models to accurately reflect observations.
<!--Please do not place any ads in this section-->
 
* [http://www.bgmedicine.com BG Medicine]
 
* [http://cellnomica.netfirms.com/ Cellnomica]
 
* [http://www.entelos.com Entelos]
 
* [http://www.genego.com GeneGo]
 
* [http://www.genstruct.com Genstruct] ([[Genstruct|wiki entry]])
 
* [http://www.ingenuity.com Ingenuity Systems]
 
   
=== International conferences ===
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The investigations of a single level of biological organization (such as those listed above) are usually referred to as Systematic Systems Biology. Other areas of Systems Biology includes Integrative Systems Biology, which seeks to integrate different types of information to advance the understanding the biological whole, and Dynamic Systems Biology, which aims to uncover how the biological whole changes over time (during evolution, for example, the onset of disease or in response to a perturbation). Functional Genomics may also be considered a sub-field of Systems Biology.
* [http://necsi.org/events/iccs6/ ICCS 2006 - 6th International Conference on Complex Systems]
 
* [http://necsi.org/events/iccs/iccscover.html ICCS 2004 - 5th International Conference on Complex Systems]
 
* [http://necsi.org/events/iccs/iccs4cover.html ICCS 2002 - 4th International Conference on Complex Systems]
 
* [http://necsi.org/events/iccs/iccs3.html ICCS 2000 - 3rd International Conference on Complex Systems]
 
* [http://necsi.org/html/iccs2.html ICCS 1998 - 2nd International Conference on Complex Systems]
 
* [http://necsi.org/html/iccs.html ICCS 1997 - 1st International Conference on Complex Systems]
 
   
* [http://www.icsb-2006.org/ ICSB 2006 - 7th International Conference on Systems Biology]
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The systems biology approach often involves the development of mechanistic models, such as the reconstruction of dynamic systems from the quantitative properties of their elementary building blocks<ref>{{cite journal | last=Gardner | first=TS | coauthors=di Bernardo D, Lorenz D and Collins JJ | date=04 Jul 2003 | title=Inferring genetic networks and identifying compound of action via expression profiling
* [http://www.icsb-2005.org/ ICSB 2005 - 6th International Conference on Systems Biology]
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| journal=Science | volume=301 | pages=102-1005 | pmid=12843395}}</ref><ref>{{cite journal | last=di Bernardo | first=D | coauthors=Thompson MJ, Gardner TS, Chobot SE, Eastwood EL, Wojtovich AP, Elliot SJ, Schaus SE and Collins JJ | date=Mar 2005 | title=Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks
* [http://www.icsb2004.org/ ICSB 2004 - 5th International Conference on Systems Biology]
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| journal=Nature Biotechnology | volume=23 | pages=377-383 | pmid=15765094}}</ref>. For instance, a cellular network can be modelled mathematically using methods coming from chemical kinetics and control theory. Due to the large number of parameters, variables and constraints in cellular networks, numerical and computational techniques are often used. Other aspects of computer science and informatics are also used in systems biology. These include new forms of computational model, such as the use of [[process calculi]] to model biological processes, the integration of information from the literature, using techniques of [[information extraction]] and [[text mining]], the development of online databases and repositories for sharing data and models (such as [[BioModels Database]]), approaches to database integration and software interoperability via loose coupling of software, websites and databases (such as Gaggle [http://gaggle.systemsbiology.net]), and the development of syntactically and semantically sound ways of representing biological models, such as the [[Systems Biology Markup Language]].
* [http://icsb2003.molecool.wustl.edu/ ICSB 2003 - 4th International Conference on Systems Biology]
 
* [http://www.icsb2001.org/ ICSB 2001 - 2nd International Conference on Systems Biology]
 
* [http://www.symbio.jst.go.jp/systemsbiology/news/icsb/ ICSB 2000 - 1st International Conference on Systems Biology]
 
   
== Tools for systems biology ==
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== See also ==
* [http://www.sbml.org/ Systems Biology Markup Language] - developed by the Computational Neurobiology group at the European Bioinformatics Institute
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*[[Artificial life]]
* [http://psimap.kaist.ac.kr/ PSIbase Database] structural interactome map of all proteins
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*[[Biological systems engineering]]
* [http://simtk.org/xml/index.xml SimTK]
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*[[Biomedical cybernetics]]
* [http://gaggle.systemsbiology.net Gaggle]
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*[[Biostatistics]]
* [http://www.sys-bio.org Systems Biology Workbench]
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*[[Computational Biology]]
* [http://www.sbml.org Systems Biology Markup Language]
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*[[Computational systems biology]]
* [http://www.cellml.org The CellML language]
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*[[Computer simulation]]
* [http://www.littleb.org The little b Modeling Language]
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*[[Gene regulatory network]]
* [http://www.copasi.org Copasi (Version 4 of Gepasi)]
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*[[List of omics topics in biology]]
* [http://ecell.sourceforge.net/ E-Cell System]
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*[[List of publications in biology#Systems biology]]
* [http://www.pdn.cam.ac.uk/groups/comp-cell/StochSim.html StochSim]
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*[[List of Systems Biology Research Groups]]
* [http://www.vcell.org Virtual Cell]
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*[[Metabolic network modelling]]
* [http://jigcell.biol.vt.edu/ JigCell (John Tyson Lab)]
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*[[Model (abstract)|Model]]
* [http://pysces.sourceforge.net/ Python Simulator for Cellular Systems]
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*[[Model checking and systems biology]]
* [http://www.ingenuity.com/ Ingenuity Pathways Analysis]
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*[[Network Theory of Aging]]
* [http://www.mssm.edu/labs/iyengar/resources/software/SAVI/ SAVI Signaling Analysis and Visualization]
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*[[Regulome]]
* [http://physiome.org/jsim.html JSim]
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*[[Synthetic biology]]
* [http://bionetgen.lanl.gov BioNetGen]
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*[[Systems Biology Markup Language]]
* [http://sysbio.molgen.mpg.de/SBML-PET/ SBML-PET] Systems Biology Markup Language based Parameter Estimation Tool
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*[[SBO]]
* [http://mips.gsf.de/proj/biorel/ BIOREL] web-based resource for quantitative estimation of the gene network bias in relation to available database information about gene activity/function/properties/associations/interactions
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*[[Systems ecology]]
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*[[Systems immunology]]
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*[[Systems theory]]
   
==Bibliography==
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== Bibliography ==
===Books===
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=== Books ===
*H Kitano (editor). ''Foundations of Systems Biology.'' MIT Press: 2001. ISBN 0-262-11266-3
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* H Kitano (editor). ''Foundations of Systems Biology.'' MIT Press: 2001. ISBN 0-262-11266-3
*G Bock and JA Goode (eds).''In Silico" Simulation of Biological Processes'', Novartis Foundation Symposium 247. John Wiley & Sons: 2002. ISBN 0-470-84480-9
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* CP Fall, E Marland, J Wagner and JJ Tyson (Editors). "Computational Cell Biology." Springer Verlag: 2002 ISBN 0-387-95369-8
*E Klipp, R Herwig, A Kowald, C Wierling, and H Lehrach. ''Systems Biology in Practice.'' Wiley-VCH: 2005. ISBN 3-527-31078-9
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* G Bock and JA Goode (eds).''In Silico" Simulation of Biological Processes'', Novartis Foundation Symposium 247. John Wiley & Sons: 2002. ISBN 0-470-84480-9
*B Palsson. ''Systems Biology - Properties of Reconstructed Networks.'' Cambridge University Press: 2006. ISBN 9780521859035
+
* E Klipp, R Herwig, A Kowald, C Wierling, and H Lehrach. ''Systems Biology in Practice.'' Wiley-VCH: 2005. ISBN 3-527-31078-9
+
* L. Alberghina and H. Westerhoff (Editors) – ''Systems Biology: Definitions and Perspectives'', Topics in Current Genetics 13, Springer Verlag (2005), ISBN 13: 978-3540229681
===Articles===
+
* A Kriete, R Eils. ''Computational Systems Biology.'', Elsevier - Academic Press: 2005. ISBN 0-12-088786-X
*Marc Vidal and Eileen E. M. Furlong. Nature Reviews Genetics 2004 [http://www.nature.com/nrg/journal/v5/n10/poster/omics/index.html From OMICS to systems biology]
+
* K. Sneppen and G. Zocchi, (2005) ''Physics in Molecular Biology'', [[Cambridge University Press]], ISBN 0-521-84419-3
+
* D. Noble, [http://www.musicoflife.co.uk/ ''The Music of life. Biology beyond the genome'' Oxford University Press] 2006. ISBN-10: 0199295735, ISBN-13: 978-0199295739
*Werner, E., "The Future and Limits of Systems Biology", [http://stke.sciencemag.org/content/vol2005/issue278/ Science STKE] 2005, pe16 (2005).
+
* Z. Szallasi, J. Stelling, and V.Periwal (eds.) System Modeling in Cellular Biology: From Concepts to Nuts and Bolts (Hardcover), MIT Press: 2006, ISBN 0-262-19548-8
  +
* B Palsson, [http://gcrg.ucsd.edu/book/index.html ''Systems Biology - Properties of Reconstructed Networks.'' Cambridge University Press: 2006.] ISBN 978-0-521-85903-5
  +
* K Kaneko. ''Life: An Introduction to Complex Systems Biology.'' Springer: 2006. ISBN 3540326669
  +
* U Alon. ''An Introduction to Systems Biology: Design Principles of Biological Circuits.'' CRC Press: 2006. ISBN 1-58488-642-0 - emphasis on Network Biology (For a comparative review of Alon, Kaneko and Palsson see<ref name="Review">Werner, E., {{cite web
  +
| url = http://www.nature.com/nature/journal/v446/n7135/pdf/446493a.pdf
  +
| title = "All systems go"}}, [http://www.nature.com/nature/journal/v446/n7135/index.html Nature]vol 446, pp 493-494, March 29, 2007. </ref> )
   
  +
=== Articles ===
  +
* M. Tomita, Hashimoto K, Takahashi K, Shimizu T, Matsuzaki Y, Miyoshi F, Saito K, Tanida S, Yugi K, Venter JC, Hutchison CA. E-CELL: Software Environment for Whole Cell Simulation. Genome Inform Ser Workshop Genome Inform. 1997;8:147-155. [http://web.sfc.keio.ac.jp/~mt/mt-lab/publications/Paper/ecell/bioinfo99/btc007_gml.html]
 
* [http://www.sciencemag.org/content/vol295/issue5560/ ScienceMag.org] - Special Issue: Systems Biology, ''[[Science (journal)|Science]]'', Vol 295, No 5560, March 1, 2002
 
* [http://www.sciencemag.org/content/vol295/issue5560/ ScienceMag.org] - Special Issue: Systems Biology, ''[[Science (journal)|Science]]'', Vol 295, No 5560, March 1, 2002
* ''[http://www.nature.com/msb/index.html Nature]'' - Molecular Systems Biology
+
* Marc Vidal and Eileen E. M. Furlong. Nature Reviews Genetics 2004 [http://www.nature.com/nrg/journal/v5/n10/poster/omics/index.html From OMICS to systems biology]
* [http://www.scq.ubc.ca/?p=253 Systems Biology: An Overview] - a review from the Science Creative Quarterly
+
* Marc Facciotti, Richard Bonneau, Leroy Hood and Nitin Baliga. Current Genomics 2004 [http://www.ingentaconnect.com/content/ben/cg/2004/00000005/00000007/art00002 Systems Biology Experimental Design - Considerations for Building Predictive Gene Regulatory Network Models for Prokaryotic Systems]
* [http://www.guardian.co.uk/life/science/story/0,12996,1477776,00.html Guardian.co.uk] - 'The unselfish gene: The new biology is reasserting the primacy of the whole organism - the individual - over the behaviour of isolated genes', Johnjoe McFadden, ''[[The Guardian]]'' (May 6, 2005)
+
* Katia Basso, Adam A Margolin, Gustavo Stolovitzky, Ulf Klein, Riccardo Dalla-Favera, Andrea Califano, (2005) [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15778709&query_hl=7 "Reverse engineering of regulatory networks in human B cells"]. Nat Genet;37(4):382-90
  +
* Mario Jardon [http://www.scq.ubc.ca/?p=253 Systems Biology: An Overview] - a review from the Science Creative Quarterly, 2005
  +
* Johnjoe McFadden, [http://www.guardian.co.uk/life/science/story/0,12996,1477776,00.html Guardian.co.uk] - 'The unselfish gene: The new biology is reasserting the primacy of the whole organism - the individual - over the behaviour of isolated genes', ''[[The Guardian]]'' (May 6, 2005)
  +
* WTEC Panel Report on [http://www.wtec.org/sysbio/welcome.htm International Research and Development in Systems Biology] (2005)
  +
* E. Werner, "The Future and Limits of Systems Biology", [http://stke.sciencemag.org/content/vol2005/issue278/ Science STKE] 2005, pe16 (2005).
  +
* Francis J. Doyle and Jörg Stelling, [http://www.journals.royalsoc.ac.uk/openurl.asp?genre=article&id=doi:10.1098/rsif.2006.0143 "Systems interface biology"] ''J. R. Soc. Interface'' Vol 3, No 10 2006
  +
* Kahlem, P. and Birney E. (2006). "Dry work in a wet world: computation in systems biology." [http://www.nature.com/doifinder/10.1038/msb4100080 Mol Syst Biol 2: 40.]
  +
* E. Werner, [http://www.nature.com/nature/journal/v446/n7135/pdf/446493a.pdf "All systems go"], [http://www.nature.com/nature/journal/v446/n7135/index.html "Nature"] vol 446, pp 493-494, March 29, 2007. (Review of three books (Alon, Kaneko, and Palsson) on systems biology.)
  +
* Santiago Schnell, Ramon Grima, Philip K. Maini, [http://www.americanscientist.org/template/AssetDetail/assetid/54784 "Multiscale Modeling in Biology"], American Scientist, Vol 95, pages 134-142, March-April 2007.
  +
* TS Gardner, D di Bernardo, D Lorenz and JJ Collins. [http://www.bu.edu/abl/publications.html "Inferring genetic networks and identifying compound of action via expression profiling."] Science 301: 102-105 (2003).
   
 
== External links ==
 
== External links ==
* [http://www.biochemweb.org/systems.shtml BioChemWeb.org] - The Virtual Library of Biochemistry and Cell Biology: A Guide to Biochemistry, Molecular Biology & Cell Biology on the Web
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{{Commonscat|Systems biology}}
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{{Wiktionary}}
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<!-- Please use the talk page to propose any additions to this section. Feel free to add research groups and labs to the List_of_Systems_Biology_Research_Groups article -->
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* [http://www.nature.com/msb Molecular Systems Biology] - open access journal on systems biology
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* [http://www.biomedcentral.com/bmcsystbiol BMC Systems Biology] - open access journal on systems biology
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* [http://www.iee.org/Publish/Journals/ProfJourn/Proc/SYB/ IET Systems Biology] - not open access journal on systems biology
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* [http://mips.gsf.de/proj/biorel/ BIOREL resource for quantitative estimation of the gene network bias in relation to available database information]
  +
* [http://www.biochemweb.org/systems.shtml Systems Biology - BioChemWeb.org]
 
* [http://www.systems-biology.org/ Systems Biology Portal] - administered by the Systems Biology Institute
 
* [http://www.systems-biology.org/ Systems Biology Portal] - administered by the Systems Biology Institute
* [http://interactomics.org Community for Interactomics] - Systems Biology Wiki
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* [http://www.systembiologie.de/en/index.html Systems Biology Portal of Germany] - administered by HepatoSys, the German competence network for Systems Biology of liver cells
  +
* [http://www.mathworks.com/company/newsletters/news_notes/june07/simbiology.html Studying the World's Most Complex Dynamic Systems] By Ricardo Paxson and Kristen Zannell, The MathWorks website.
  +
* [http://www2.warwick.ac.uk/fac/sci/sbdtc/ Warwick University Systems Biology Doctoral Training Centre] - offering EPSRC grants for select individuals to study Systems Biology at MSc and then PhD level.
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* [http://www.bu.edu/abl Systems Biology at Boston University]
   
==See also==
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== References ==
*[[Gene regulatory network]]
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<references/>
*[[Model (abstract)|Model]]
 
*[[Computer simulation]]
 
*[[List of publications in biology#Systems biology|Important publications in systems biology]]
 
*[[Systems ecology]]
 
*[[Regulome]]
 
*[[Biomedical cybernetics]]
 
*[[Artificial life]]
 
   
 
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{{enWP| Systems biology}}

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Systems biology, a field of study in the biosciences, focuses on the systematic study of complex interactions in biological systems. Particularly from 2000 onwards, the term is used widely in the biosciences, and in a variety of contexts.

Overview Edit

Systems biology can be considered from a number of different aspects:

  • Some sources discuss systems biology as a field of study, particularly, the study of the interactions between the components of biological systems, and how these interactions give rise to the function and behavior of that system (for example, the enzymes and metabolites in a metabolic pathway)[1][2].
  • Other sources consider systems biology as a paradigm, usually defined in antithesis to the so-called reductionist paradigm, although fully consistent with the scientific method. The distinction between the two paradigms is referred to in these quotations:
"The reductionist approach has successfully identified most of the components and many of the interactions but, unfortunately, offers no convincing concepts or methods to understand how system properties emerge...the pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration with mathematical models" Science[3]
"Systems biology...is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different....It means changing our philosophy, in the full sense of the term" Denis Noble[4]
  • Still other sources view systems biology in terms of the operational protocols used for performing research, namely a cycle composed of theory, computational modelling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory.[5][6]. Since the objective is a model of the interactions in a system, the experimental techniques that most suit systems biology are those that are system-wide and attempt to be as complete as possible. Therefore, transcriptomics, metabolomics, proteomics and high-throughput techniques are used to collect quantitative data for the construction and validation of models.
  • Finally, some sources see it as a socioscientific phenomenon defined by the strategy of pursuing integration of complex data about the interactions in biological systems from diverse experimental sources using interdisciplinary tools and personnel.

This variety of viewpoints is illustrative of the fact that systems biology refers to a cluster of peripherally overlapping concepts rather than a single well-delineated field. However the term has widespread currency and popularity as of 2007, with chairs and institutes of systems biology proliferating worldwide.

HistoryEdit

Systems biology finds its roots in:

One of the theorists who can be seen as a precursor of systems biology is Ludwig von Bertalanffy with his general systems theory. One of the first numerical simulations in biology was published in 1952 by the British neurophysiologists and nobel prize winners Alan Lloyd Hodgkin and Andrew Fielding Huxley, who constructed a mathematical model that explained the action potential propagating along the axon of a neuronal cell[7]. Their model described a cellular function emerging from the interaction between two different molecular components, a potassium and a sodium channels, and can therefore be seen as the beginning of computational systems biology[8]. In 1960, Denis Noble developed the first computer model of the heart pacemacker [9].

The 1960s and 1970s saw the development of several approaches to study complex molecular systems, such as the Metabolic Control Analysis and the biochemical systems theory. The successes of molecular biology throughout the 1980s, coupled with a skepticism toward theoretical biology, that then promised more than it achieved, caused the quantitative modelling of biological processes to become a somewhat minor field.

However the birth of functional genomics in the 1990s meant that large quantities of high quality data became available, while the computing power exploded, making more realistic models possible. In 1997, the group of Masaru Tomita published the first quantitative model of the metabolism of a whole (hypothetical) cell.

Around the year 2000, when Institutes of Systems Biology were established in Seattle and Tokyo, systems biology emerged as a movement in its own right, spurred on by the completion of various genome projects, the large increase in data from the omics (e.g. genomics and proteomics) and the accompanying advances in high-throughput experiments and bioinformatics. Since then, various research institutes dedicated to systems biology have been developed. As of summer 2006, due to a shortage of people in systems biology[10] several doctoral training centres in systems biology have been established in many parts of the world.

Techniques associated with systems biology Edit

According to the interpretation of System Biology as the ability to obtain, integrate and analyze complex data from multiple experimental sources using interdisciplinary tools, some typical technology platforms are:

In addition to the identification and quantification of the above given molecules further techniques analyze the dynamics and interactions within a cell. This includes:

  • Interactomics which is used mostly in the context of protein-protein interaction but in theory encompasses interactions between all molecules within a cell
  • Fluxomics, which deals with the dynamic changes of molecules within a cell over time
  • Biomics: systems analysis of the biome.

The investigations are frequently combined with large scale perturbation methods, including gene-based (RNAi, mis-expression of wild type and mutant genes) and chemical approaches using small molecule libraries. Robots and automated sensors enable such large-scale experimentation and data acquisition. These technologies are still emerging and many face problems that the larger the quantity of data produced, the lower the quality. A wide variety of quantitative scientists (computational biologists, statisticians, mathematicians, computer scientists, engineers, and physicists) are working to improve the quality of these approaches and to create, refine, and retest the models to accurately reflect observations.

The investigations of a single level of biological organization (such as those listed above) are usually referred to as Systematic Systems Biology. Other areas of Systems Biology includes Integrative Systems Biology, which seeks to integrate different types of information to advance the understanding the biological whole, and Dynamic Systems Biology, which aims to uncover how the biological whole changes over time (during evolution, for example, the onset of disease or in response to a perturbation). Functional Genomics may also be considered a sub-field of Systems Biology.

The systems biology approach often involves the development of mechanistic models, such as the reconstruction of dynamic systems from the quantitative properties of their elementary building blocks[11][12]. For instance, a cellular network can be modelled mathematically using methods coming from chemical kinetics and control theory. Due to the large number of parameters, variables and constraints in cellular networks, numerical and computational techniques are often used. Other aspects of computer science and informatics are also used in systems biology. These include new forms of computational model, such as the use of process calculi to model biological processes, the integration of information from the literature, using techniques of information extraction and text mining, the development of online databases and repositories for sharing data and models (such as BioModels Database), approaches to database integration and software interoperability via loose coupling of software, websites and databases (such as Gaggle [1]), and the development of syntactically and semantically sound ways of representing biological models, such as the Systems Biology Markup Language.

See also Edit

Bibliography Edit

Books Edit

Articles Edit

External links Edit

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Wiktionary: Systems biology

References Edit

  1. Snoep J.L. and Westerhoff H.V.; Alberghina L. and Westerhoff H.V. (Eds.) (2005.). "From isolation to integration, a systems biology approach for building the Silicon Cell". Systems Biology: Definitions and Perspectives: p7, Springer-Verlag. 
  2. Systems Biology - the 21st Century Science.
  3. Sauer, U. et al. "Getting Closer to the Whole Picture" Science (journal) 316 550 17 April 2007
  4. Denis Noble The Music of Life Oxford University Press (2006) p21
  5. Systems Biology: Modelling, Simulation and Experimental Validation.
  6. Kholodenko B.N., Bruggeman F.J., Sauro H.M.; Alberghina L. and Westerhoff H.V.(Eds.) (2005.). "Mechanistic and modular approaches to modeling and inference of cellular regulatory networks". Systems Biology: Definitions and Perspectives: p143, Springer-Verlag. 
  7. Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol, 117: 500-544.
  8. Le Novere (2007) The long journey to a Systems Biology of neuronal function. BMC Systems Biology, 1: 28
  9. Noble D (1960) Cardiac action and pacemaker potentials based on the Hodgkin-Huxley equations. Nature, 188: 495-497.
  10. Working the Systems.
  11. Gardner, TS, di Bernardo D, Lorenz D and Collins JJ (04 Jul 2003). Inferring genetic networks and identifying compound of action via expression profiling. Science 301: 102-1005.
  12. di Bernardo, D, Thompson MJ, Gardner TS, Chobot SE, Eastwood EL, Wojtovich AP, Elliot SJ, Schaus SE and Collins JJ (Mar 2005). Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks. Nature Biotechnology 23: 377-383.
  13. Werner, E., "All systems go"., Naturevol 446, pp 493-494, March 29, 2007.
Genomics topics
Genome project | Glycomics | Human Genome Project | Proteomics
Chemogenomics | Structural genomics | Pharmacogenetics | Pharmacogenomics | Toxicogenomics
Bioinformatics | Cheminformatics | Systems biology


Category systems theory
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