LOGOS: a modular Bayesian model for de novo motif detection
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
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A major focus of functional genomics today is the discovery of the interactions between genes and proteins that regulate the transcription of genes and the responses of cells to external signals. The speaker will describe his recent efforts with several coworkers to solve pieces of this puzzle. The work divides into several parts: A new approach to the recognition of transcription-factor binding sites, based on the principle that transcription factors divide naturally into families such as the leucine zippers and the zinc fingers, and that the binding site motifs for transcription factors within the same family have common features. These features may be obscure at the sequence level, but can be characterized at a higher level of description. By discovering and modeling such meta-sequence features one can improve the sensitivity and specificity with which binding sites can be determined for transcription factors within a family. [5], [6] An algorithm and an associated web-based tool for finding recurrent cis-regulatory modules in the promoter regions of human genes. Each such module consists of a set of transcription factors that often bind to the same promoter regions and collectively enhance or inhibit the transcription of the corresponding genes. [4] An algorithm for minimizing the number of gene perturbation experiments required to reconstruct signal transduction pathways whose regulatory structures can be described within the mathematical framework of chain functions. [1] Algorithms for discovering protein complexes and regulatory pathways that are conserved in evolution, using protein sequence data and protein-protein interaction data for two or more organisms. [2], [3].