четверг, 14 апреля 2011 г.

Executable Biology: Computer Science Sheds Light On Animal Development

By applying the techniques of computer engineering to a mechanistic diagram describing the development of the Nematode C. elegans, a group of
researchers in Switzerland has been able to tease out what laboratory experiments have not - how and when the crucial cross-talk between cellular
signaling pathways takes place in order to determine the fates of individual cells. The novel in silico model is described in a paper appearing May
18, 2007 in the open-access journal PLoS Computational Biology.



During C. elegans development, uncommitted precursor cells differentiate into two distinct cell types in response to a series of complex biochemical
signaling events. Cancer cells respond to the same cellular signals, so understanding the dynamic orchestration in the cellular environment has
important implications in our understanding of cancer metastasis as well as normal development.



Traditional biological models give a fairly static picture of cellular processes, and this limits understanding of the details involved. Biologists
and computer scientists from the EPFL (Ecole Polytechnique Federale de Lausanne) and the University of Zurich have taken a new approach, using formal
methods of computer science to translate this picture into a dynamic representation that can capture time-dependent processes. Results from the model
can then be compared to data from the lab, revealing gaps in our understanding of the processes taking place. Researchers can use the model to test
hypotheses that would fill in the missing pieces in silico before performing actual lab experiments.



By running their model with a wide variety of gene mutation scenarios and comparing results with available laboratory data, they found that the fate
of C. elegans vulval precursor cells depends upon the time-sequence of two cellular signaling pathways, as well as a negative feedback loop that had
not been described before.



These kinds of models hold great promise for future exploration of a variety of biological systems, explains lead EPFL researcher and biologist Dr.
Jasmin Fisher. "Once a robust model has been built of a particular system, it can be used to get a global, dynamic picture of how the system
responds to a variation - such as a drug or a genetic mutation. Preliminary studies could be quickly done using the model, saving valuable
laboratory time and resources for only the most promising research avenues. We call this Executable Biology."



Link Here



Fisher J, Piterman N, Hajnal A, Henzinger TA (2007)

Predictive modeling of signaling crosstalk during C. elegans vulval development

PLoS Comput Biol 3(5): e92. doi:10.1371/journal.pcbi.0030092



About PLoS Computational Biology


PLoS Computational Biology features works of exceptional significance that further our understanding of living systems at all
scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately
available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained by the authors. The
Public Library of Science uses the Creative Commons Attribution License.



About the Public Library of Science


The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical
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