Bioinformatics: Sequence and Genome Analysis, Second Edition (Mount, Bioinformatics) Revised ed. Edition

The books gives some general idea of Bioinformatics and numbers various available programs. That is good and useful. However where this book tries to explain something in grater detail, it becomes incomprehensible. It uses some words, meaning of which is not explained and is unclear, so all explanation is meaningless to the reader.

I'm a graduate student in bioinformatics with an extensive background in software development. I am currently taking a class that uses this book as its primary text. I will receive an A for the class, but this text was completely unhelpful in achieving that goal.This book is extremely frustrating. First, it has a lot of editing errors, some of which are critical to the descriptions of computational methods. This is really unacceptable in a second edition!More to the point, bioinformatics is fundamentally a computational pursuit, and discussion of the pertinent algorithms is inescapable. The author spends a great deal of text describing algorithms, in excruciating detail, in English. This is... I can't even describe how bad an idea this is. It can take several pages of text to describe an algorithm that could be succinctly coded in 100 lines of Python, which makes the text unnecessarily lengthy. Furthermore, the author's English descriptions of the algorithms are often ambiguous or misleading (sometimes due to the above-mentioned typographical errors, and sometimes due to the fact that English is much more ambiguous than any programming language). I cite specifically the description of the "expectation maximization" algorithm for sequence motif discovery in chapter 5, but that is only one of many examples.The result is that the author's descriptions are sufficiently detailed to be confusing, but NOT sufficiently clear to allow the algorithms to be implemented correctly. This approach does not serve students well: those who haven't yet been exposed to programming end up merely mystified, while those of us who have programming backgrounds end up dreadfully confused, or simply frustrated enough to go out and write 1-star reviews on Amazon.If you are an instructor looking for a bioinformatics text, please do your students a favor and choose a different one.

I used this book to teach a bioinformatics course in a foreign language because it was only one of two available in both english and chinese. I'm not sure it wouldn't have been less confusing to simply use a english textbook and let the students translate the text for themselves. To give the author credit, he has compiled an enormous quantity of information and made it available in a single location and that is no mean feat. At the very least, it is a valuable starting point to find both useful references to better explanations and software appropriate to almost any analysis you might want to do. On the downside, the prose is a tangled mess and is beyond comprehension in places. there are points where, even though i understand the underlying theories used throughout the book, i still couldn't figure out some of the examples used to illustrate particular methods. For example, there are some figures which have captions which run for a page and a half. Finally, in the majority of cases, the figures are taken directly from key papers on each topic, and associated explanations consist of sentences copied verbatim from the text. I may be doing the author a gross injustice here, but in many of the explanations, i was left with the same impression i get when reading students papers when they have copied something out of a textbook, without really understanding what is going on. Having said all of the above, i would still recommend taking a look at this book, but be ready to access the excellent list of references if you want a more insightful understanding of many of the methods described throughout.

David W. Mount is a terrible writer. I can't believe how much of a chore this book is to read. His sentences, in my opinion, are ambiguous and I find myself backtracking unnecessarily.