Mapping the genomic landscapes is one of the most exciting frontiers of science. We have the opportunity to reverse engineer the blueprints and the control systems of living organisms. Computational tools are key enablers in the deciphering process. This book provides an in-depth presentation of some of the important computational biology approaches to genomic sequence analysis. The first section of the book discusses methods for discovering patterns in DNA and RNA. This is followed by the second section that reflects on methods in various ways, including performance, usage and paradigms.
Pattern Discovery Methods: Large-Scale Gene Regulatory Motif Discovery with NestedMICA (M Piipari et al.); R'MES: A Tool to Find Motifs with a Significantly Unexpected Frequency in Biological Sequences (S Schbath & M Hoebeke); An Intricate Mosaic of Genomic Patterns at Mid-range Scale (A Fedorov & L Fedorova); Motif Finding from Chips to ChIPs (G Pavesi); A New Approach to the Discovery of RNA Structural Elements in the Human Genome (L Hua et al.); Performance and Paradigms: Benchmarking of Methods for Motif Discovery in DNA (K Klepper et al.); Encyclopedias of DNA elements for Plant Genomes (J Lichtenberg et al.); Manycore High-Performance Computing in Bioinformatics (J-S Varre et al.); Natural Selection and the Genome (A L Hughes).