Cellular model: Difference between revisions

Revision as of 09:13, 3 December 2017

Revision as of 05:25, 29 December 2017

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==Molecular level simulations==

[http://cellcollective.org/ Cell Collective] is a modeling software that enables one to house dynamical biological data, build computational models, stimulate, break and recreate models. The development is led by [http://helikarlab.org/members.html Tomas Helikar, PhD Bioformatics], a researcher within the field of computational biology. It is designed for biologists, students learning about computational biology, teachers focused on teaching life sciences, and researchers within the field of life science. The complexities of math and computer science are built into the backend and one can learn about the methods used for modeling biological species, but complex math equations, algorithms, programming are not required and hence won't impede model building.

The mathematical framework behind Cell Collective is based on a common qualitative (discrete) modeling technique where the regulatory mechanism of each node is described with a logical function [for more comprehensive information on logical modeling, see <ref>Morris MK, Saez-Rodriguez J, Sorger PK, Lauffenburger DA.. Logic-based models for the analysis of cell signaling networks. Biochemistry (2010) 49(15):3216–24.10.1021/bi902202q

</ref> <ref>Helikar T, Kowal B, Madrahimov A, Shrestha M, Pedersen J, Limbu K, et al. Bio-Logic Builder: a nontechnical tool for building dynamical, qualitative models. PLoS One (2012) 7(10):e46417.10.1371/journal.pone.0046417</ref>].

Model validation

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The [http://www.e-cell.org/ E-Cell Project] aims "to make precise whole cell simulation at the molecular level possible".<ref>http://www.e-cell.org/ecell/</ref>

[[CytoSolve]] - developed by [[Shiva Ayyadurai|V. A. Shiva Ayyadurai]] and C. Forbes Dewey, Jr. of Department of Biological Engineering at the [[Massachusetts Institute of Technology]] - provided a method to model the whole cell by dynamically integrating multiple molecular pathway models. ."<ref>{{cite journal |last1=Al-Lazikani |first1=Bissan|last2=Banerji |first2=Udai | last3=Workman |first3=Paul |year=2012 |title= Combinatorial drug therapy for cancer in the post-genomic era|journal=Nature Biotechnology |volume=30 |issue= 7|pages=679–692 |publisher=Nature |doi= 10.1038/nbt.2284|url= |pmid=22781697}}<!--|accessdate=14 February 2013 --></ref><ref>{{Cite journal| last1=Ayyadurai| first1=VA Shiva|first2=C. Forbes|last2=Dewey|accessdate=22 March 2013|journal=Cell Mol Bioeng.|date=March 2011|volume=4|issue=1|pages=28–45|doi=10.1007/s12195-010-0143-x|title=CytoSolve: A Scalable Computational Method for Dynamic Integration of Multiple Molecular Pathway Models|publisher=Springer|pmid=21423324|pmc=3032229}}</ref>

In the July 2012 issue of [[Cell (journal)|''Cell'']], a team led by [[Markus W. Covert|Markus Covert]] at Stanford published the most complete computational model of a cell to date. The model of the roughly 500-gene ''[[Mycoplasma genitalium]]'' contains 28 algorithmically-independent components incorporating work from over 900 sources. It accounts for interactions of the complete genome, transcriptome, proteome, and metabolome of the organism, marking a significant advancement for the field.<ref>http://covertlab.stanford.edu/publicationpdfs/mgenitalium_whole_cell_2012_07_20.pdf{{dead link|date=November 2016 |bot=InternetArchiveBot |fix-attempted=yes }}</ref><ref>http://news.stanford.edu/news/2012/july/computer-model-organism-071812.html</ref>

Most attempts at modeling cell cycle processes have focused on the broad, complicated molecular interactions of many different chemicals, including several [[cyclin]] and [[cyclin-dependent kinase]] molecules as they correspond to the [[S phase|S]], [[M phase|M]], [[G1 phase|G1]] and [[G2 phase|G2]] phases of the [[cell cycle]]. In a 2014 published article in PLOS computational biology, collaborators at [[University of Oxford]], [[Virginia Tech]] and Institut de Génétique et Développement de Rennes produced a simplified model of the cell cycle using only one cyclin/CDK interaction. This model showed the ability to control totally functional [[cell division]] through regulation and manipulation only the one interaction, and even allowed researchers to skip phases through varying the concentration of CDK. <ref>{{Cite journal|title = Cell Cycle Control by a Minimal Cdk Network|url = https://dx.doi.org/10.1371/journal.pcbi.1004056|journal = PLoS Comput Biol|date = 2015-02-06|pmc = 4319789|pmid = 25658582|pages = e1004056|volume = 11|issue = 2|doi = 10.1371/journal.pcbi.1004056|first = Claude|last = Gérard|first2 = John J.|last2 = Tyson|first3 = Damien|last3 = Coudreuse|first4 = Béla|last4 = Novák}}</ref> This model could help understand how the relatively simple interactions of one chemical translate to a cellular level model of cell division.

==Projects==