Bayesian Methods for Genomics, Molecular and Systems Biology

Abstract

Inference for high throughput genomic data has emerged as a major source of challenges for statistical inference in general, and Bayesian analysis in particular. This chapter discusses some related current research frontiers. The chapter highlights how specific strengths of the Bayesian approach are important to model such data. Bayesian inference provides a natural paradigm to exploit the considerable prior information that is available about important biological pathways. Another strength of Bayesian inference that leads to research opportunities with phylogenomic data is the natural ease of simultaneous modeling and inference on multiple related processes.