Computational Methods in Molecular Biology

This volume first provides an overview of the main challenges facing computational biology and presents a tutorial on computation for molecular biologists (the volume's primary intended audience) and a tutorial for computer scientists on the biology underlying the research problems in later chapters. Next, contributions addressing DNA and RNA sequence analysis are presented, including a tutorial introduction to hidden Markov models, a case-based reasoning approach to sequence annotation, description of how to use sequence similarity as the basis for sequence classification, details about the latest version of GRAIL, discussion of how to model RNA splicing signals using statistical patterns, and tutorial material on genetic algorithms and decision trees. Remaining contributions address proteins, including treatment of statistical methods for protein structure analysis, the THREADER system, a novel application of geometric hashing, and a probabilistic modeling approach similar to HMMs. An appendix briefly describes software and databases for computational biology on the Internet and offers suggestions for further reading.

Odkazy:

• http://www.cs.jhu.edu/~salzberg/compbio-book.html