Abstract
OpenWorm is an international collaboration with the aim of understanding how the behavior of Caenorhabditis elegans (C. elegans) emerges from its underlying physiological processes. The project has developed a modular simulation engine to create computational models of the worm. The modularity of the engine makes it possible to easily modify the model, incorporate new experimental data and test hypotheses. The modeling framework incorporates both biophysical neuronal simulations and a novel fluid-dynamics-based soft-tissue simulation for physical environment-body interactions. The project's open-science approach is aimed at overcoming the difficulties of integrative modeling within a traditional academic environment. In this article the rationale is presented for creating the OpenWorm collaboration, the tools and resources developed thus far are outlined and the unique challenges associated with the project are discussed.
Highlights
OpenWorm is an open science project dedicated to providing a flexible tool for C. elegans researchers to explore hypotheses of biological function in silico
The aim is not to produce a single model of C. elegans, but rather to construct a general simulation framework that enables the creation of a family of worm models
C. elegans is a nematode that lives in soil environments where it searches for and consumes bacteria
Summary
OpenWorm is an open science project dedicated to providing a flexible tool for C. elegans researchers to explore hypotheses of biological function in silico. Studies from experimental neuroscience have called for such computational tools (Wen et al, 2012). Despite the copious amounts of data being obtained, modeling efforts and advanced experimental techniques, a comprehensive understanding of how the behavior of the worm emerges from the underlying physiological processes has not yet been achieved (Cohen and Sanders, 2014; Gjorgjieva et al, 2014). The OpenWorm project aims to help this cause by developing a common simulation platform for creating computational models of the organism. Exploring a family of models using different levels of abstraction could help to identify critical biophysical processes and advance a mechanistic understanding of how the behavior of C. elegans is generated
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