Computational Genetics And Genomics

This book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementation in R and SAS. The methods are applied to a range of testing problems in biomedical and genomic research, including the identification of differentially expressed and co-expressed genes in high-throughput gene expression experiments, such as microarray experiments; tests of association between gene expression measures and biological annotation metadata (e.g., Gene Ontology); sequence analysis; and the genetic mapping of complex traits using single nucleotide polymorphisms.

The completion of the first draft of the human genome has led to an explosion of interest in genetics and molecular biology. The view of the genome as a network of interacting computational components is well-established, but researchers are now trying to reverse the analogy, by using living organisms to construct logic circuits.

An up-to-date introduction for the uninitiated into the various "flavors" of chemical genomics with a series of readily reproducible techniques for applications in organic chemistry, protein chemistry, and computer science, emphasizing the high-throughput approaches that are the essence of chemical genomics.