This book is the first of its kind to provide a large collection of bioinformatics problems with accompanying solutions. Notably, the problem set includes all of the problems offered in Biological Sequence Analysis (BSA), by Durbin et al., widely adopted as a required text for bioinformatics courses at leading universities worldwide. Although many of the problems included in BSA as exercises for its readers have been repeatedly used for homework and tests, no detailed solutions for the problems were available. Bioinformatics instructors had therefore frequently expressed a need for fully worked solutions and a larger set of problems for use on courses. This book provides just that: following the same structure as BSA and significantly extending the set of workable problems, it will facilitate a better understanding of the contents of the chapters in BSA and will help its readers develop problem-solving skills that are vitally important for conducting successful research in the growing field of bioinformatics. All of the material has been class-tested by the authors at Georgia Tech, where the first ever M.Sc. degree program in Bioinformatics was held.
Preface; 1. Introduction; 2. Pairwise alignment; 3. Markov chains and hidden Markov models; 4. Pairwise alignment using HMMs; 5. Profile HMMs for sequence families; 6. Multiple sequence alignment methods; 7. Building phylogenetic trees; 8. Probabilistic approaches to phylogeny; 9. Transformational grammars; 10. RNA structure analysis; 11. Background on probability.
Mark Borodovsky is the Regents' Professor of Biology and Biomedical Engineering and Director of the Center for Bioinformatics and Computational Biology at Georgia Institute of Technology in Atlanta. He is the founder of the Georgia Tech M.Sc. and Ph.D. degree programs in Bioinformatics. His research interests are in bioinformatics and systems biology. He has taught Bioinformatics courses since 1994. Svetlana Ekisheva is a Research Scientist at the School of Biology, Georgia Institute of Technology, Atlanta. Her research interests are in bioinformatics, applied statistics and stochastic processes. Her expertise includes teaching probability theory and statistics at universities in Russia and in the USA.