Meeting: Working Group
Synthesizing Computational Resources for Cis-regulatory Molecular Evolution.
| Date | 15-Mar-2007 ~ 17-Mar-2007 |
| Project | Synthesizing computational resources for cis-regulatory molecular evolution. |
| Summary | This working group will synthesize computational resources to study cis-regulatory evolution, an emerging discipline in molecular evolution that spans the evolution of development to the bioinformatics of gene regulation. In the absence of a known "genetic code" for gene regulation, few methods have been developed for the quantitative analysis of cis-regulatory evolution. Recent pioneering efforts have provided inroads into decoding the rules that govern cis-regulatory evolution (and therefore the cis-regulatory code itself), however the lack of community-endorsed standards for quantifying cis-regulatory evolution compounds inherent difficulties posed by these enigmatic sequences. This working group will redress this specific challenge, and establish a structured foundation for new generations of analytical tools to understand the evolution of gene regulation. The specific aims of this working group are: (1) to develop a set of XML exchange standards for molecular evolutionary analysis of cis-regulatory sequences (e.g. annotated alignments, phylogenetic trees, indels and repeats, transcription factor binding site models, metrics to quantify cis-regulatory polymorphism and divergence, (2) to synthesize available open-access resources for the computational study of cis-regulatory evolution (alignment methods, annotation methods, simulation platforms, quantitative models of cis-regulatory evolution, regulatory annotation databases, etc.) around these exchange standards which will be maintained as a distributable software list at NESCent, and (3) to write an article summarizing the logic behind the XML standard and issues of how to quantify cis-regulatory evolution (e.g. how to measure rates of cis-regulatory evolution? how to measure selection on cis-regulatory sequences?, how to quantify biases due to missing data?). |
