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29 January 2008

978 0 52161 230 2
Cambridge University Press (2006)
GBP23.99

Problems and Solutions in Biological Sequence Analysis

Mark Borodovsky and Svetlana Ekisheva

This book is devoted to teaching bioinformatics in a comprehensive university course assuming the students have already got acquainted with the knowledge in computer programming and statistics. It will also be a useful tool for bioinformatics-oriented researchers with the above-mentioned skills.

The book could also – as the authors point out –be considered as an addition to one of the most famous and widely used textbooks for teaching bioinformatics at universities throughout the world, the Biological Sequence Analysis (BSA)1. It is worth mentioning that it is a very appropriate addition that was moreover eagerly awaited since the present book delivers the problems along with their solutions helping thus the students and researchers to gain the problem-solving abilities. So the book represents a valuable source of information regardless a qualified reader is able to attend a university course or not.

It is divided into 11 chapters. After the introductory chapter, the authors deal with the pair-wise alignments using hidden Markov models (three chapters), then go through protein families (one chapter) to multiple sequence alignment methods (one chapter). The next two chapters are focused on phylogenies; first using the conventional algorithms and second describing the probabilistic algorithms. The chapter 9 is oriented to transformational grammars useful for subsequent structure modelling, whereas the chapter 10 offers the problems and solutions for the RNA structure analysis. Finally the last chapter gives an overview of some basic concepts of probability.

I especially liked the Further Reading arranged at the end of every chapter and indicating the key references focused on the specific examples and problems discussed more generally within a chapter. The authors also explain the limitations of obtaining the unambiguous solutions in bioinformatics, e.g., in getting the only right multiple sequence alignment. This is due to the impossibility to verify experimentally both the alignments and phylogenies. The readers should take into account that the standard dynamic programming algorithm, which should deliver the multiple alignment of only ten protein sequences of average length with the best score, would take the time comparable with the age of our planet. The goal therefore is to achieve as optimal alignment as possible within a reasonable time.

Despite the close relatedness between the ‘original’ above-mentioned BSA book and the present one is obvious, there may also be some differences in terminology used that should not be overlooked, for example the term “independence model” vs. the “random sequence model”.

The book is suitably completed by the list of almost 300 references and a typical alphabetical subject index. Overall it can really be recommended to complement the other well-established university textbooks on bioinformatics or it can equally be used alone. It is, however, necessary to know that this book absolutely requires the readers are not novices in the field of bioinformatics. On the other hand, those who are already familiar with computer programming and statistics will surely be satisfied.

Reference:
1 Durbin R., Krogh A., Eddy S.R. & Mitchinson G. (1998) Biological Sequence Analysis Cambridge University Press, Cambridge

Stefan Janecek, Institute of Molecular Biology, Slovak Academy of Sciences, Slovakia



 
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