Editing Modelling biological systems (section)

==Particular tasks==

===Cellular model===
{{Main|Cellular model}}
[[File:Signal transduction pathways.svg|thumb|right|200px|Part of the [[cell cycle]]]]
[[File:EltonFW.jpg|right|thumb|200px|Summerhayes and Elton's 1923 food web of Bear Island (''Arrows represent an organism being consumed by another organism'').]]
[[File:Lotka Volterra dynamics.svg|thumb|300px|right|A sample [[Time series|time-series]] of the [[Lotka–Volterra equation|Lotka–Volterra model]].  Note that the two populations exhibit [[Limit cycle|cyclic behaviour]].]]
Creating a cellular model has been a particularly challenging task of [[systems biology]] and [[mathematical biology]]. It involves the use of [[computer simulation]]s of the many [[cell (biology)|cellular]] subsystems such as the [[metabolic network|networks of metabolites]], [[enzyme]]s which comprise [[metabolism]] and [[Transcription (biology)|transcription]], [[Translation (biology)|translation]], regulation and induction of gene regulatory networks.<ref>{{cite journal | vauthors = Carbonell-Ballestero M, Duran-Nebreda S, Montañez R, Solé R, Macía J, Rodríguez-Caso C | title = A bottom-up characterization of transfer functions for synthetic biology designs: lessons from enzymology | journal = Nucleic Acids Research | volume = 42 | issue = 22 | pages = 14060–14069 | date = December 2014 | pmid = 25404136 | pmc = 4267673 | doi = 10.1093/nar/gku964 }}</ref>

The complex network of biochemical reaction/transport processes and their spatial organization make the development of a [[predictive modelling|predictive model]] of a living cell a grand challenge for the 21st century, listed as such by the [[National Science Foundation]] (NSF) in 2006.<ref>[https://www.science.org/doi/full/10.1126/science.1135003 American Association for the Advancement of Science]</ref>

A whole cell computational model for the bacterium ''[[Mycoplasma genitalium]]'', including all its 525 genes, gene products, and their interactions, was built by scientists from Stanford University and the J. Craig Venter Institute and published on 20 July 2012 in Cell.<ref>[http://www.cell.com/abstract/S0092-8674%2812%2900776-3 Karr, J. (2012) A Whole-Cell Computational Model Predicts Phenotype from Genotype Cell]</ref>

A dynamic computer model of intracellular signaling was the basis for Merrimack Pharmaceuticals to discover the target for their cancer medicine MM-111.<ref>[http://mct.aacrjournals.org/content/early/2012/02/17/1535-7163.MCT-11-0820.short McDonagh, CF (2012) Antitumor Activity of a Novel Bispecific Antibody That Targets the ErbB2/ErbB3 Oncogenic Unit and Inhibits Heregulin-Induced Activation of ErbB3. Molecular Cancer Therapeutics ]</ref>

[[Membrane computing]] is the task of modelling specifically a [[cell membrane]].

===Multi-cellular organism simulation===
An open source simulation of C. elegans at the cellular level is being pursued by the [[OpenWorm]] community. So far the physics engine [https://github.com/openworm/OpenWorm/wiki/Geppetto--Overview Gepetto] has been built and models of the neural connectome and a muscle cell have been created in the NeuroML format.<ref>[http://www.openworm.org/downloads.html OpenWorm Downloads<!-- Bot generated title -->]</ref>

===Protein folding===
{{Main|Protein folding problem}}
Protein structure prediction is the prediction of the three-dimensional structure of a [[protein]] from its [[amino acid]] sequence—that is, the prediction of a protein's [[tertiary structure]] from its [[primary structure]].  It is one of the most important goals pursued by [[bioinformatics]] and [[theoretical chemistry]]. [[Protein structure prediction]] is of high importance in [[medicine]] (for example, in [[drug design]]) and [[biotechnology]] (for example, in the design of novel [[enzymes]]). Every two years, the performance of current methods is assessed in the [[CASP]] experiment.

===Human biological systems===

====Brain model====
The [[Blue Brain Project]] is an attempt to create a synthetic brain by [[Reverse engineering|reverse-engineering]] the [[mammalian brain]] down to the molecular level. The aim of this project, founded in May 2005 by the Brain and Mind Institute of the ''[[Ecole Polytechnique Fédérale de Lausanne|École Polytechnique]]'' in [[Lausanne]], Switzerland, is to study the brain's architectural and functional principles. The project is headed by the Institute's director, Henry Markram. Using a [[Blue Gene]] [[supercomputer]] running Michael Hines's [[Neuron (software)|NEURON software]], the simulation does not consist simply of an [[artificial neural network]], but involves a partially biologically realistic model of [[neuron]]s.<ref name="Brainsim">Graham-Rowe, Duncan. [https://www.newscientist.com/article/dn7470--mission-to-build-a-simulated-brain-begins.html "Mission to build a simulated brain begins"], ''NewScientist'', June 2005.</ref><ref>Palmer, Jason. [http://news.bbc.co.uk/2/hi/science/nature/8012496.stm Simulated brain closer to thought], BBC News.</ref> It is hoped by its proponents that it will eventually shed light on the nature of [[consciousness]].
There are a number of sub-projects, including the [[Cajal Blue Brain]], coordinated by the [[Supercomputing and Visualization Center of Madrid]] (CeSViMa), and others run by universities and independent laboratories in the UK, U.S., and Israel. The Human Brain Project builds on the work of the Blue Brain Project.<ref name="hbp_homepage">[http://www.humanbrainproject.eu/index.html The Human Brain Project.] {{webarchive |url=https://web.archive.org/web/20120705000755/http://www.humanbrainproject.eu/index.html |date=July 5, 2012 }}</ref><ref name="hbp_video">[https://www.youtube.com/watch?v=n4a-Om-1MrQ Video of Henry Markram presenting The Human Brain Project on 22 June 2012.]</ref> It is one of six pilot projects in the Future Emerging Technologies Research Program of the European Commission,<ref name="FET_flagships_homepage">[http://cordis.europa.eu/fp7/ict/programme/fet/flagship/home_en.html FET Flagships Initiative homepage.]</ref> competing for a billion euro funding.

====Model of the immune system====
The last decade has seen the emergence of a growing number of simulations of the immune system.<ref>{{cite book | chapter-url=https://doi.org/10.1007%2F978-3-540-24844-6_57 | doi=10.1007/978-3-540-24844-6_57 | chapter=Multi-criterion Evolutionary Algorithm with Model of the Immune System to Handle Constraints for Task Assignments | title=Artificial Intelligence and Soft Computing - ICAISC 2004 | series=Lecture Notes in Computer Science | year=2004 | last1=Balicki | first1=Jerzy | volume=3070 | pages=394–399 | isbn=978-3-540-22123-4 }}</ref><ref>{{cite web|url=https://www.sciencedaily.com/releases/2009/05/090518111729.htm|title=Computer Simulation Captures Immune Response To Flu|access-date=2009-08-19}}</ref>

====Virtual liver====
The [[virtual liver network|Virtual Liver]] project is a 43 million euro research program funded by the German Government, made up of seventy research group distributed across Germany. The goal is to produce a virtual liver, a dynamic mathematical model that represents human liver [[mathematical physiology|physiology]], morphology and function.<ref name="virtual liver">{{Cite web |url=http://www.virtual-liver.de/ |title=Virtual Liver Network. |access-date=2016-10-14 |archive-url=https://web.archive.org/web/20120930110342/http://www.virtual-liver.de/ |archive-date=2012-09-30 |url-status=dead }}</ref>

===Tree model===
{{Main|Simulated growth of plants}}
Electronic trees (e-trees) usually use [[L-system]]s to simulate growth. L-systems are very important in the field of [[complexity science]] and [[A-life]].
A universally accepted system for describing changes in plant morphology at the cellular or modular level has yet to be devised.<ref>{{cite web |url=http://www.acm.org/crossroads/xrds8-2/plantsim.html |title=Simulating plant growth |access-date=2009-10-18 |url-status=dead |archive-url=https://web.archive.org/web/20091209022645/http://www.acm.org/crossroads/xrds8-2/plantsim.html |archive-date=2009-12-09 }}</ref>
The most widely implemented tree generating algorithms are described in the papers [http://portal.acm.org/citation.cfm?id=218427 "Creation and Rendering of Realistic Trees"] and [https://doi.org/10.1007%2F978-3-540-25944-2_22 Real-Time Tree Rendering].

===Ecological models===
{{Main|Ecosystem model}}
Ecosystem models are [[mathematics|mathematical]] representations of [[ecosystem]]s.  Typically they simplify complex [[food web|foodwebs]] down to their major components or [[trophic level]]s, and quantify these as either numbers of [[organism]]s, [[biomass]] or the [[inventory]]/[[concentration]] of some pertinent [[chemical element]] (for instance, [[carbon]] or a [[nutrient]] [[chemical species|species]] such as [[nitrogen]] or [[phosphorus]]).

===Models in ecotoxicology===
The purpose of models in [[ecotoxicology]] is the understanding, simulation and prediction of effects caused by toxicants in the environment. Most current models describe effects on one of many different levels of biological organization (e.g. organisms or populations). A challenge is the development of models that predict effects across biological scales. [http://www.ecotoxmodels.org/ Ecotoxicology and models] discusses some types of ecotoxicological models and provides links to many others.

===Modelling of infectious disease===
{{Main|Mathematical modelling of infectious disease|Epidemic model}}
It is possible to model the progress of most infectious diseases mathematically to discover the likely outcome of an [[epidemic]] or to help manage them by [[vaccination]]. This field tries to find [[parameter]]s for various [[infectious disease]]s and to use those parameters to make useful calculations about the effects of a mass [[vaccination]] programme.