Title:  Statistical pattern discovery in ChIP-seq data

Asbtract:  Coupling deep sequencing with traditional chromatin immunoprecipitation (ChIP-seq) of transcription factors and histone proteins offers biologists unique new insights into how the cell regulates the expression of its many genes. Getting the most out of this data requires novel bioinformatics approaches and algorithms. In particular, pattern discovery algorithms tailored to finding sequence motifs in large sets of short DNA sequences are needed. Using these algorithms allows us to identify the genes bound and regulated by a given transcription factor and to predict which transcription factors (TFs) may physically interact and bind to DNA as protein complexes. This talk will provide a basic introduction to the biology of gene expression followed by a case study of ChIP-seq analysis. Two novel statistical pattern discovery algorithms will then be described.