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Dr. Eric Werner

Contact: eric.werner@dpag.ox.ac.uk

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In silico multicellular systems biology

Eric Werner

Abstract of talk given in Edinburgh at the IBM Blue Gene Conference in March 2002.


Because modeling a single cell gives little insight into multicellular processes and in particular multicellular diseases, it is inevitable that single cell simulations must be complemented by in silico multicellular systems. Cellnomica, Inc. is a company that has software that models many interesting and useful multicellular processes including cell division, cell differentiation, cell signaling, chemical gradients, bilateral symmetry, tissue development, tissue interactions, mutations including homeotic mutations, and multicellular diseases such as some types of cancer. At the level of the cell the software models the cell at minimal but sufficient level of detail to include, for example, cell signaling networks. At the level of the genome, genome networks are not only modeled but also integrated with the rest of the cellular and multicellular model so that changes in the network can be observed in the developing, dynamic 4-dimensional structure. What is significant is that a balance is reached between sufficient detail to model such phenomena, but not so much detail as to make the system incomprehensible. The software is extensible and has the potential to be integrated with software packages that have more detailed models of single cells. Perhaps the greatest strength of such a system level view of the function of the genome in the context of the cell and its multicellular environment is the insight and global understanding it gives the scientist attempting to unlock the meaning of the genome and the proteome. The ability to mutate the genome and see the effects immediately in the developing in silico multicellular system gives the researcher an unprecedented tool to test his hypotheses and models. Given that a normal in vivo or in vitro mutation can take months to perform in the lab, reducing the time to two or three seconds can be a significant benefit to the researcher attempting to understand and design his experiment.

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in silico Mulicellular Development( Eric Werner)

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