4.3 Article Proceedings Paper

GemCell: A generic platform for modeling multi-cellular biological systems

期刊

THEORETICAL COMPUTER SCIENCE
卷 391, 期 3, 页码 276-290

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.tcs.2007.11.014

关键词

biological modeling; intercellular behavior; executable modeling; complex systems; statecharts

资金

  1. Engineering and Physical Sciences Research Council [EP/E031161/1] Funding Source: researchfish
  2. EPSRC [EP/E031161/1] Funding Source: UKRI

向作者/读者索取更多资源

The mass and complexity of biological information requires computer-aided simulation and analysis to help scientists achieve understanding and guide experimentation. Although living organisms are composed of cells, actual genomic and proteomic data have not yet led to a satisfactory model of working cell in silico. We have set out to devise a user-friendly generic platform, GemCell, for Generic Executable Modeling of Cells, based on whole, functioning cells. Starting with the cell simplifies life, because all cells expresses essentially five generic types of behavior: replication, death, movement (including change of shape and adherence), export (secretion, signaling, etc.) and import (receiving signals, metabolites, phagocytosis, etc.). The details of these behaviors are specified in GemCell for particular kinds of cells as part of a database of biological specifics (the DBS), which specifies the cell properties and functions that depend on the cell's history, state, environment, etc. The DBS is designed in an intuitive fashion, so users are able to easily insert their data of interest. The generic part of GemCell, built using Statecharts, is a fully dynamic model of a cell, its interactions with the environment and its resulting behavior, individually and collectively. Model specificity emerges from the DBS, so that model execution is carried out by the statecharts executing with the aid of specific data extracted from the DBS dynamically. Our long term goal is for GemCell to serve as a broadly applicable platform for biological modeling and analysis, supporting user-friendly in silico experimentation, animation, discovery of emergent properties, and hypothesis testing, for a wide variety of biological systems. (C) 2007 Elsevier B.V. All rights reserved.

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