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| By: Richard Durbin, Sean R. Eddy, Anders Krogh, Graeme Mitchison ISBN: 0521629713 Publisher: Cambridge University Press Release Date: 01 July, 1999 Bioscience book rank: 353990 | This book gives an excellent introduction into sequence analysis for a person who is already somewhat familiar with the basics of Bayesian techniques. The authors illustrate concepts, as and when they are introduced, via carefully selected examples; comprehension is made much easier because of this. A great reference and a good introduction to many important concepts in sequence analysis. However, if you don't have a reasonable grounding in math you may struggle with the terse notation. <br /> <br />Borodovsky's companion book is an excellent partner for this book. Get both. Although this book is based primarily on work that was completed in 1998, and therefore somewhat out of date, it is the best book I have found for teaching bioinformatics. I selected this as the best of the available books on the subject for use in my bioinformatics and numerical methods course which is to be taught in the fall of 2007 at Univ. of Conn. This course is an upper division undergraduate and first year graduate course. That is roughly the level of this text and the comparative advantage of this book is the excellent presentation and thorough discussion of the algorithms. A student armed with Matlab or MathScriptor can take this book and start writing algorithms for sequence alignment and Hidden Markov Method (HMM) analysis after only the first three or four chapters. This book is in its 11th printing and is nearly error free (I found only a few in the figures). This book is strongly recommended for both students and researchers, particularly those interested in protein alignment, phylogenic analysis or an introduction to Hidden Markov Methods. | |
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| By: Mark Borodovsky, Svetlana Ekisheva ISBN: 0521612306 Publisher: Cambridge University Press Release Date: 11 September, 2006 Bioscience book rank: 183344 | Biological Sequence Analysis (BSA) by Durbin et al has become almost the defacto standard textbooy for teaching bioinformatics. And like most texts it presents a series of problems for the student to solve. <br /> <br />Because of the rapid growth of bioinformatics, the schools have attracted a large number of students that have come from a wide variety of educational backgrounds. As a result, the presumptions made by the authors on the mathematical ability of the students studying BSA is at variance from the students now using the book. <br /> <br />This book is intended to provide these students with a 'cram course' in the mathematics they will need to tackle the BSA problems. It starts by providing detailed solutions to the problems presented in BSA, it then extends the set of workable problems to further develop the problem solving skills of the students. <br /> <br />This book might be viewed as a 360 page supplement to BSA. It's mathematics is not trivial, but is necessary for the student to succeed in the bioinformatics field. It is a book that the unprepared student will spend many hours studying. | |
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| By: David W. Mount ISBN: 0879697121 Publisher: Cold Spring Harbor Laboratory Press Release Date: July, 2004 Bioscience book rank: 141022 | I used this book in an introduction level class to bioinformatics and it was worse then useless. The book is much more a survey of literature then anything else and so if you are not already very familiar with the topics the book does not provide enough details for you to get very far at all. Although to be fair most of the books on bioinformatics out at the time and the two years after were not much better, but I felt this was near the bottom of the pile. "Fundamental Concepts of Bioinformatics", ISBN: 0-8053-4633-3 when it came out was miles better, although even that book had tons of warts. If you are looking for a reference then this book is okay, but by the time I am writing this review you assuredly can find a more modern book.
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<br />Part of the problem with books on bioinformatics is that, every book makes very different assumptions on your base level of knowledge of the various critical subjects needed: biology, chemistry, computer science and math. Most strike a pretty poor balance on the assumptions made and vary from way too basic to useless to anyone who is not already familiar with the field. My suggestion is to check out any book you are considering because how good the book is will vary greatly on your background. 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. I took Dr. Mount's class at the U. or Arizona, and he's a really smart guy, but the man can't explain anything. It's not just his book either; his lectures are just as cryptic. I went to class thinking I understood the concepts, but then I got totally confused when he lectured. I would try to clarify things with the book, and again, I'd get even more confused. Someone who reviewed this book earlier said that he tends to use 10 words where he should use 1; I couldn't agree more. The figures in this book also need a major overhaul, and he should definitely include more examples of the many complex concepts he talks about. While I have no doubt that there is plenty of useful information in there, getting anything out of it is a chore. I would only recommend this book to someone who already had a strong knowledge of bioinformatics concepts. | |
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| By: Emanuel A. Schegloff ISBN: 0521532795 Publisher: Cambridge University Press Release Date: 15 January, 2007 Bioscience book rank: 247327 | ||
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| By: W. J. Kaczor, M. T. Nowak ISBN: 0821820508 Publisher: American Mathematical Society Release Date: March, 2000 Bioscience book rank: 211624 | In your undergrad math career or maybe early grad, you only need two books for the subject analysis. These two volume book is one. Contains many challenging problems that will satisfy your ambitious Putnam apetite.
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<br />While the other one is, I will say, Problems in Mathematical Analysis by Berman ASIN: B0007AL4WG. This book contains tons of problems with little overlapping. It's comprehensive and collective! Should be called a comprehensive collection of problems in mathematical analysis (at undergraduate level). It's theeee most comprehensive one out there. While Kazac and Nowak's books Problems in Mathematical Analysis have more hard problems (Putnam type), this one helps you build up the knowledge you need to understand advanced graduate level Real Analysis. Highly recommended for econ/math/physics majors.
<br /> contains a lot of examples and problems; maths can't just be learnt out of textbooks; you need this kind of book in order to go face to face with classic and sometime weird material as you can find there; very useful to set up exercices and tests when you teach this kind of things too... | |
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| By: Darryl Leon, Scott Markel, Lorrie LeJeune ISBN: 059600494X Publisher: O'Reilly Media, Inc. Release Date: 01 February, 2003 Bioscience book rank: 583655 | The O'Reilly Press is normally the gold standard when it comes to very well-written and very well-edited hard science documents. That is why I purchased this one. Sadly, this falls very far below the norm. The first 73 pages of the text may be skipped. Most of the rest is EMBOSS. Sadly, you can get this directly, and freely, from the original authors. Just use a normal search and type "EMBOSS". Nothing else pertains.<p>Wayne I picked this book up at BioCon 2003 and, to be honest, I wasn't sure at first how useful it was going to be. Flipping through a few of the sections, it seemed to be little more than an assemblage of man pages for each of the tools and programs it covered. So I put it on a shelf above my monitor at work for a while and as the days went by I found myself grabbing it more and more often to look something up. <p>For example, I found myself needing reminding of the option for tabular output when doing a psi-blast. Grab the book ... a ha! ... -m 8. You can use the man pages or tutorials for many of things like this but sometimes there is a lot to wade through to find what you were looking for. Also, if you're like me you like the feel of a book sometimes and the ability to scrawl notes in the margins. It's just nice having all the options right there on the page.<p>To be fair to the authors, I don't think that Chia-hsiu Tu was very accurate in his review by saying that "this books focus on EMBOSS only" (sic). EMBOSS coverage does make up about 58% of the book, but it is a suite of 150 useful programs. Unless you want only a sentence or two about each one you're going to have to use up a few pages. You get just enough info to learn about each and a quick guide to their usage. If you want to know more, there are links to their full documentation online.<p>Some sections are stronger than others. The MEME/MAST chapter, for instance, doesn't just list out options but has great command line examples and a paragraph for each explaining what is going on. On the other hand, I wanted to use stretcher (in the EMBOSS package) and there was only a quick example (the syntax of which didn't work for me) and a listing of six options. I needed to find out how to make it work in a non-interactive way and write its output to STDOUT, neither of which were illustrated (-auto and -stdout, by the way).<p>Ok, let's get to what this book covers. The first section goes really in depth to cover the data-exchange formats that we nerds find ourselves writing parsing scripts for all the time. (yes, yes, bioperl, biojava, etc. are great, but they aren't in this book. Hopefully one will cover them soon.) What I found most useful were the example files for each format (EMBL, DDBJ, Genbank, FASTA, SWISS-PROT, PFAM, & PROSITE) and the tables that were laid out for them. For example, there are nice little tables listing every feature (62 at my count) and feature qualifier (74!) that you can expect to find in a DDBJ/EMBL/Genbank file. And for each of those there is a little descripton of what they represent. Very nice.<p>The second part of the book covers these specific tools: ReadSeq, the BLAST suite (7 progs), BLAT, CLUSTALW, HMMER (10 progs), MEME, MAST, and the EMBOSS suite (~150 progs). These sections are pretty decent and while you won't find much info on how the algorithms behind the programs work, you will have everything you need to run the programs and fine-tune their options to control their behavior.<p>Lastly, the third part of the book has a really valuable quick reference of a variety of things such as a listing of the amino acids, their 1 and 3-letter abbreviations, structures and properties. In the genetic codes section you'll be able to quickly remind yourself that the transcriptional product for AUA in invertebrate mitochondriates differs from the norm, coding for methionine instead of isoleucine. (you knew that right?)<p>On the whole, I think this reference is a great review of the most common tools out there for sequence analysis and a quick guide to their use. While at times examples and verbose explanations are lacking, one must keep in mind that this is a book in the "nutshell" series, not in the "definitive guide" one. If you find yourself scouring for online docs and searching man pages for special options often, you should definitely get this book. This books focus on EMBOSS only, a high quality open source bioinformatic toolkit. It can be a useful reference book when write web interface of those programs in this book. Also it provides the urls where we can download from? where the original idea come from? | |
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| By: Allen G. Rodrigo, Gerald H. Learn Jr. ISBN: 0792379942 Publisher: Springer Release Date: 31 October, 2000 Bioscience book rank: 1002844 | ||
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| By: Ingvar Eidhammer, Inge Jonassen, William R. Taylor ISBN: 0470848391 Publisher: Wiley Release Date: 01 March, 2004 Bioscience book rank: 877064 | The book 'Protein Bioinformatics' tries to cover all aspects of proteins, from sequence to structure. This is of course a very wide field and the difficulty of the algorithms involved in this analysis increases from sequence to structure investigations. From the preface of the book one can read, that this is still not enough for the authors because additionally they are trying to write this book for a broad audience, for researchers and students.
<br />After reading this book I think it could be used by undergraduate students in Bioinformatics or related fields or as reference. It does not give deep and clear explanations but rather provides short summaries of articles. The good thing is after reading this book you know of the existence of these articles and can consult them to understand the working mechanism of the algorithms in detail.
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<br />There is certainly a lack in good books about proteins and especially about protein structure analysis which can partly filled by this book. This book gives good, basic coverage of the concepts important in understanding protein sequence and structure. <br /> <br />There are three major sections in this book: sequence, structure, and the relatinship between the two. The sequence section covers all the basics: dynamic programming for string matching, scoring matrices, trees and classification, and profiles of various sorts. The sequence discussion is a bit shorter, but goes over substructures, similarity searching and scoring, and kinds of structures and domains. The third section is even shorter and unites the two areas: predicting structure from sequence, with a good introduction to threading. <br /> <br />The book's strength is its breadth. It sacrifices depth to get that breadth, though. A few analytic techniques are sketched in the text or presented in psuedocode. Most often, however, a programmer will have a hard time gleaning enough detail from this to implement any of the algorithms described. <br /> <br />The authors aim at readers who already understand the significance of protein structure and who are comfortable with ideas like hydrogen bonding. Lots of programmers will have a hard time understanding why problems are important or what the driving phenomena are. Biologists won't be put off by an excessively mathematical treatment, but won't get a detailed understanding of the algorithms or mathematical foundations either. This book comes close to under-serving both kinds of reader. <br /> <br />This book is good for conceptual understanding of the algorithms, where implementable details don't matter, and gives good coverage to protein-specific issues. It's decidedly for someone who wants more than just the how-to of running BLAST or strucuture analysis tools. I think this book will help most if you want more understanding of what goes on inside the tools, or if you want an easy start to a deep and complex topic. Advanced readers may not like it, though - detail and real understanding just aren't there. I give this one four stars, but I had to round up to four. <br /> <br />//wiredwerid | |
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| By: Wojciech Szpankowski ISBN: 047124063X Publisher: Wiley-Interscience Release Date: 16 April, 2001 Bioscience book rank: 1006054 | If you have ever been curious to know what is the mathematics behind the fancy formulas describing the average-case behavior of algorithms -- this book is for you. An excellent addition to the classic "The Art of Computer Programming" by D.Knuth, "Introduction to Analysis of Algorithms" by R.Sedgewick and P.Flajolet, and "Analysis of Algorithms" by M.Hofri, this book walks reader through a beautiful, and at the same time very diverse (not to say complex) world of mathematical tools and techniques needed to obtain precise answers to questions like "what is the average depth of a digital tree built over $n$ strings?", or "what is the average number of comparisons performed by a Knuth-Morris-Pratt algorithm when it searches for a given pattern of length $m$ in a random text of length $n$?". <p>Being well organized, the book present these (sometimes very sophisticated) techniques in a simple step-by-step fashion, starting with brief reviews of several known (and necessary for future presentation) results from probability, complex analysis/special functions, and information theory. The presentation of the numerous specific techniques is split in two parts: explaining probabilistic and analytic approaches to the analysis of algorithms correspondingly. Probabilistic techniques (inequalities of moments, limit theorems, large deviations, etc.) are very useful in the analysis of complex random structures, as they often yield simple estimates of their asymptotic behavior, where more accurate techniques fail or become prohibitively laborious. Analytic techniques (generating functions, singularity analysis, saddle point techniques, Mellin transform, analytic poissonization and depoissonization) on the other hand, represent a toolbox for exact modelling of the characteristics of the algorithms, yielding estimates of unparalleled precision.<p>As indicated by its title, this book is mostly devoted to the analysis of a special class of combinatorial algorithms - ones that operate with sequences of symbols, or sequences. For example, it includes a detailed analysis of various algorithms for searching and sorting alphanumeric sequences based on digital trees (tries, digital search tries, Patricia-tries, etc.), redundancy expressions for popular Lempel-Ziv data compression schemes, average complexity estimates for text pattern-matching algorithms (such as Knuth-Morris-Pratt scheme), and so on. <p>Following the tradition of "The Art of Computer Programming", the author wraps many results in the form of exercises, so that active readers can have fun solving them. These excersises are grouped into several classes, ranging from simple routine calculations to serious research problems (including ones that are currently unsolved).<p>Overall, this is a very good graduate-level textbook and a valuable (and almost self-contained) source of information for everyone interested in the analysis of algorithms. If you have ever been curious to know what is the mathematics behind the fancy formulas describing the average-case behavior of algorithms -- this book is for you. An excellent addition to the classic "The Art of Computer Programming" by D.Knuth, "Introduction to Analysis of Algorithms" by R.Sedgewick and P.Flajolet, and "Analysis of Algorithms" by M.Hofri, this book walks reader through a beautiful, and at the same time very diverse (not to say complex) world of mathematic tools and techniques needed to obtain precise answers to questions like "what is the average depth of a digital tree built over $n$ strings?", or "what is the average number of comparisons performed by a Knuth-Morris-Pratt algorithm when it searches for a given pattern of length $m$ in a random text of length $n$?". <p>Being well organized, the book present these (sometimes very sophisticated) techniques in a simple step-by-step fashion, starting with brief reviews of several known (and necessary for future presentation) results from probability, complex analysis/special functions, and information theory. The presentation of the numerous specific techniques is split in two parts: explaining probabilistic and analytic approaches to the analysis of algorithms correspondingly. Probabilistic techniques (inequalities of moments, limit theorems, large deviations, etc.) are very useful in the analysis of complex random structures, as they often yield simple estimates of their asymptotic behavior, where more accurate techniques fail or become prohibitively laborious. Analytic techniques (generating functions, singularity analysis, saddle point techniques, Mellin transform, analytic poissonization and depoissonization) on the other hand, represent a toolbox for exact modelling of the characteristics of the algorithms, yielding estimates of unparalleled precision.<p>As indicated by its title, this book is mostly devoted to the analysis of a special class of combinatorial algorithms -- ones that operate with sequences of symbols, or sequences. For example, it includes a detailed analysis of various algorithms for searching and sorting alphanumeric sequences based on digital trees (tries, digital search tries, Patricia-tries, etc.), redundancy expressions for popular Lempel-Ziv data compression schemes, average complexity estimates for text pattern-matching algorithms (such as Knuth-Morris-Pratt scheme), and so on. <p>Following the famous tradition of "The Art of Computer Programming", the author wraps many (in some case very difficult to derive) results in the form of exercises, so that active readers can have fun solving them. As a special bonus, some of these "exercises" represent currently open research problems.<p>Overall, this is a very good graduate-level textbook and a valuable (and almost self-contained) source of information for everyone interested in the analysis of algorithms. | |
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| By: Jean-Louis Auget, N. Balakrishnan, Mounir Mesbah, Geert Molenberghs ISBN: 0817643680 Publisher: Birkhäuser Boston Release Date: 22 November, 2006 Bioscience book rank: 1547147 | ||
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