Last September, I gave a presentation on the DevoWorm project to the OpenWorm group. On May 20, I will be presenting another version of this talk to the Biocomplexity Institute at Indiana University.
Here is the abstract:
The nematode C. elegans provides a unique opportunity for developmental computational biology. The relatively small and invariant number of cells in the C. elegans adult (959 in males, 1031 in hermaphrodites) provides a means to build tractable representations of the entire organism. The deterministic nature of C. elegans embryogenesis itself allows for complete cell lineages to be constructed. This affords us an opportunity to approximate developmental processes without model underspecification. The unique biology of C. elegans also enables the discovery of fundamental statistical signatures that define non-regulative (mosaic) development and cellular differentiation more broadly. As the OpenWorm bioinformatics project (http://www.openworm.org/) is an attempt to emulate the whole organism (C. elegans), DevoWorm is an attempt to emulate developmental processes that lead to the adult C. elegans. Such a meta-emulation is useful in a number of ways, from providing crucial information about development itself to providing a combinatorial source of developmental outcomes for evaluating the potential functional roles of phenotypic variation.In this talk, we will discuss not only how emulation of C. elegans development can proceed, but also how this is relevant to a broader developmental perspective. The talk will also highlight a few examples of what can be extracted from secondary data and computational representations. One involves the extraction and characterization of uniquely informative parameters. Another is application of the differentiation tree approach for purposes of providing multi-axial resolution to the process of cell division and differentiation in mosaic development. When combined with models of development physics, our two examples could help clarify the relationships between regulative and mosaic development. These examples can be augmented through the use of both computational representation and multiple datatypes such as gene expression, microscopy, and semantic metadata. To conclude, we will consider the limitations of developmental simulations and how they can be useful heuristics for enabling better cell, molecular, and computational biology.
Alicea, B., McGrew, S., Gordon, R., Larson, S., Warrington, T., and Watts, M. DevoWorm: differentiation waves and computation in C. elegans embryogenesis. bioRxiv, http://dx.doi.org/10.1101/009993
Alicea, B. Now Announcing the DevoWorm project. Synthetic Daisies blog, June 3 (2014).http://syntheticdaisies.blogspot.com/2014/06/now-announcing-devoworm-project.html
Szigeti, B., Gleeson, P., Vella, M., Khayrulin, S., Palyanov, A., Hokanson, J., Currie, M., Cantrelli, M., Idili, G., and Larson, S. OpenWorm: an open-science approach to modelling Caenorhabditis elegans. Frontiers in Computational Neuroscience, 8, 137 (2014).