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| By: Robert Gentleman, Vincent Carey, Wolfgang Huber, Rafael Irizarry, Sandrine Dudoit ISBN: 0387251464 Publisher: Springer Release Date: 31 August, 2005 Bioscience book rank: 182834 | I find this book is not so good for people without any gene or microarray experiment background. It didn't even give clear definition of the basic concepts.
<br />Another problem is that it's not well organized because every chapter is written by different authors who have different interest and preference and use slightly different terms for the same thing. If you're like me, you came upon this book because you decided to use R for analysis of microarray data, but you're mired in its gory and frustrating details. <br /> <br />Yes, you need a reference book. But not this one, and certainly not this edition. Better documentation can be found elsewhere (dare I say online?). <br /> <br />The code examples given are technically accurate and run as advertised, but they are of the "monkey see, monkey do" variety. They provide little intuition for how to use R for oneself, outside the covers of this text. For example, Chapter 23 discusses linear models for microarray data (using the "limma" package), and several code examples contain the parameter 'adjust = "fdr"'. The reader is never enlightened that this refers to a "false discovery rate" adjustment. <br /> <br />In other cases, example code is simply missing. Chapter 21 covers the Rgraphviz graphing library, with a figure showing the three common graphical layouts -- but no example code for producing these graphs is given (I had to find it outside the book). <br /> <br />For those trying to use R for computational biology, I recommend getting an overview of the R programming language first (Venables and Ripley's book "Modern Applied Statistics with S" is a great text), and only then wading into references such as this one, if at all. I purchased this book to learn specific details and look at applications for the functions present in bioconductor. I have had trouble applying some of the chapters to custom data because they are written for specific microarray/data formats. Overall, this book is a good value because it contains examples of how bioconductor can be used to aid in hypothesis testing, but I struggle to apply what I have read to the different types of data I have. The section on Statistical analysis for genomic experiments and the section on gaphs and networks should be the reason you purchase this book. They are very helpful and interesting. The case studies were not very helpful in my opinion. | |
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| By: Jean-Michel, Ph. D. Claverie, Cedric, Ph.D. Notredame ISBN: 0470089857 Publisher: For Dummies Release Date: 18 December, 2006 Bioscience book rank: 14276 | The first chapter is a short review of DNA and RNA sequences, amino acids, and protein. The other chapters teach you to use the free software found on the Internet to work with your research. Information is also given which helps explain some biochemicals. My skills are in Software Development using C++ language, and I need more information on biochemicals to understand the problems and to develop algorithms to solve them.
<br />My only criticism is that I would like the book to give more biochemical theory before taking up the subject of Internet software.
<br />Overall, this is a good beginner's book on biochemistry.
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<br /> I am a couple years into a PhD in bioinformatics, but this is the book I started with. I knew some biology and some computer science, but I still found a lot of the databases, etc. confusing and the field has a decided lack of simplified documentation (though it is getting better). <br /> <br />Of course, bioinformatics is a pretty broad topic and no book could possibly cover everything. <br /> <br />If you do not know any biology at all you probably should also get a basic text on genetics/molecular biology (or read thema at the NCBI web site books section for free). You don't need anything in depth to read the dummies book, just at the level of an introductory biology book. Hint: DNA to RNA, RNA to Protein. And you want to know why proteins are similar because proteins with similar amino acid sequences often have similar chemical properties and therefore similar functions, so if you know what one protein does you can guess what a protein like it probably does. <br />:-) <br /> <br />And despite the name of the book the authors are REAL bioinformaticists (T-Coffee rocks!) <br /> This book kind of blew me away. Bioinformatics is such a big word. <br /> <br />Then in the second chapter they tell you 'How Most People Use Bioinformatics.' And all of a sudden they have you on line to the National Library of Medicine at the National Institute of Health. They have you looking at protein sequences, and you even understand what they are saying. <br /> <br />This is a 'For Dummies' book. It is written in their traditional style, assuming that you know very little -- well to be sure they say they are making the assumption that 'You likely have a background in molecular biology. If you don't - or if you need to brush up on your molecular biology - Chapter 1 gives you a brief overview of the basics.' <br /> <br />I found that the first few chapters went down pretty easily. By part IV it had gone further than I wanted to go, and I quit reading. <br /> <br />BUT if I were going to be taking a course in bioinformatics, or even thinking about taking such a course, or just looking at a degree in biology, I'd spend a week or two getting around this book. It's written a hell of a lot better than any text you're likely to get assigned, and at its price it's quite a deal. | |
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| By: James Tisdall ISBN: 0596000804 Publisher: O'Reilly Media, Inc. Release Date: 15 October, 2001 Bioscience book rank: 129457 | Although this book was written for biologists with no previous programming experience who have decided they need to learn to program in PERL, it is also useful for programmers entering the field of bioinformatics who need to learn the language. However, you should have some background in biology or else you'll be lost as to the purpose of the examples. That's because almost all of the examples and exercises are based on real biological problems, and this book will give you a good introduction to the most common bioinformatics programming problems and the most common computer-based biological data. This book is over five years old, but it still stands alone in that what it does it does better than any other book I've run across. The follow-on to this book is "Mastering Perl for Bioinformatics", and I recommend that book for both CS and biologist types that want to get into the more advanced parts of PERL and yet stay in the realm of learning the language via real biological problems. The following is a short run down of each chapter:
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<br />1. Biology and Computer Science - Covers some key concepts in molecular biology, as well as how biology and computer science fit together.
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<br />2. Getting Started with Perl - Shows you how to get Perl running on your computer and also talks about Perl's benefits.
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<br />3. The Art of Programming - Provides an overview as to how programmers accomplish their jobs. Some of the most important practical strategies good programmers use are explained, and where to find answers to questions that arise while you are programming is carefully laid out. These ideas are made concrete by brief narrative case studies that show how programmers, given a problem, find its solution.
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<br />4. Sequences and Strings - You start writing Perl programs with DNA and proteins. The programs transcribe DNA to RNA, concatenate sequences, make the reverse complement of DNA, and read sequence data from files. This is the first chapter to conclude with exercises.
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<br />5. Motifs and Loops - Continues demonstrating the basics of the Perl language with programs that search for motifs in DNA or protein, interact with users at the keyboard, write data to files, use loops and conditional tests, use regular expressions, and operate on strings and arrays.
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<br />6. Subroutines and Bugs -Extends the basic knowledge of Perl in two main directions: subroutines, which are an important way to structure programs, and the use of the Perl debugger, which can examine in detail a running Perl program.
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<br />7. Mutations and Randomizations - Genetic mutations, fundamental to biology, are modelled as random events using the random number generator in Perl. This chapter uses random numbers to generate DNA sequence data sets, and to repeatedly mutate DNA sequence. Loops, subroutines, and lexical scoping are also discussed.
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<br />8. The Genetic Code - How to translate DNA to proteins, using the genetic code. It also covers a good bit more of the Perl programming language, such as the hash data type, sorted and unsorted arrays, binary search, relational databases, and DBM, and how to handle FASTA formatted sequence data.
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<br />9. Restriction Maps and Regular Expressions - An introduction to Perl regular expressions. The main focus of the chapter is the development of a program to calculate a restriction map for a DNA sequence.
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<br />10. GenBank - The Genetic Sequence Data Bank (GenBank) is central to modern biology and bioinformatics. In this chapter, you learn how to write programs to extract information from GenBank files and libraries. You will also make a database to create your own rapid access lookups on a GenBank library.
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<br />11. Protein Data Bank - Develops a program that can parse Protein Data Bank (PDB) files. Some interesting Perl techniques are encountered while doing so, such as finding and iterating over lots of files and controlling other bioinformatics programs from a Perl program.
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<br />12. BLAST - Develops some code to parse a BLAST output file. Also mentioned are the Bioperl project and its BLAST parser, and some additional ways to format output in Perl.
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<br />13. Further Topics - Looks at topics beyond the scope of this book. These topics include sequence alignment methods like the Smith-Waterman algorithm and microarray techniques that enable the measurement of the relative levels of thousands of gene transcripts at a time. These topics are only briefly mentioned, and you are shown places outside of the book to get further information.
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<br />Appendix A - Resources for Perl and for bioinformatics programming, such as books and Internet sites.
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<br />Appendix B - Summary of those parts of the Perl language that will be most useful as you read this book. For the students of molecular biology and genetics, and also other bioinformatics-related departments, this book is an above-average supply to study Perl. People come to Bioinformatics from either the bio side or the CS side, with a few from various other disciplines. This book is best for the bio person who is getting into programming, not the programmer who is getting into bio. <br /> <br />For you CS types, I attended a tutorial by Tisdall on this material some years ago. One of the attendees asked why you needed an editor to code in Perl. That is the level that we are dealing with here! <br /> <br />It is a crime that biology and biochem students are not taught any perl- this is a very useful tool that will be more important as time goes on. <br /> <br />Perhaps someone could write a book on bioinformatics Perl for programmers someday, but that is not the goal of this book. | |
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| By: James D. Tisdall ISBN: 0596003072 Publisher: O'Reilly Media, Inc. Release Date: June, 2003 Bioscience book rank: 295688 | This book is definitely written for the biologist that knows some perl and not the experienced perl programmer. To the biologists who have some experience, this book will open up many new possibilities, but to a person with a few years of perl experience, many sections are skimpy and wasteful on topics better covered by other Perl books.
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<br />For example, for anyone with truely massive datasets, it might have been worth the mention of the performance cost/benefits of using BerkleyDBs and hash joins (180-3500 times). With improvements of 2-3 orders of magnitude for large sets, it would have been worth a complementary example in chapter 6 so that readers can weigh the alternatives for certain situations.
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<br />The book, however, is well worth the price just for chapters 4, 5 and 9.
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<br />4) Sequence Formats and Inheritance
<br />5) A Class for Restriction Enzymes
<br />9) Introduction to Bioperl
<br /> This book is a continuation of Tisdall's "Beginning Perl for Bioinformatics" and thus illustrates more advanced Perl programming techniques. This book not only talks about Perl programming, but it goes into some detail on the subject of bioinformatics itself. It is assumed that the CS-type reader has a good understanding of biology and the goals of bioinformatic programming. Otherwise, the examples and projects within the book will not make sense. The following is a description of the book's contents: <br /> <br />Part I: OBJECT-ORIENTED PROGRAMMING IN PERL <br />Chapter 1. Modular Programming with Perl - Talks about using modules so that other people can reuse your programs and you can reuse other people's modules in your own programs. <br /> <br />Chapter 2. Data Structures and String Algorithms - Talks about all of the different data structures available through Perl and how to build up special structures in Perl that you might need to describe complex data. Also mentions various string algorithms that are used in analyzing biological data and implements them in Perl. <br /> <br />Chapter 3. Object-Oriented Programming in Perl - Introduces object-orientation in Perl via a module that includes a class that keeps track of genes. <br /> <br />Chapter 4. Sequence Formats and Inheritance - How to convert sequence files into alternate formats such as FASTA and GCG. The object-oriented concept of inheritance is also introduced. <br /> <br />Chapter 5. A Class for Restriction Enzymes - By writing a more complex class, you get a bigger dose of object-orientated programming in biology. <br /> <br />Part II: PERL AND BIOINFORMATICS <br />Chapter 6. Perl and Relational Databases - Talks about SQL and the design of relational databases. MySQL is examined specifically. <br /> <br />Chapter 7. Perl and the Web - You learn about web programming in Perl by seeing how to put a laboratory on the Web via Perl and CGI. <br /> <br />Chapter 8. Perl and Graphics - Graphics programming in Perl is demonstrated when you learn to write a program that displays changing data to the Web. The graphical Perl module PD is discussed and demonstrated in a program. <br /> <br />Chapter 9. Introduction to Bioperl - Introduces the reader to Bioperl, which is a group of open source Perl modules used for bioinformatics programming. They provide many basic facilities so you don't have to worry about them. <br /> <br />Part III: Appendixes <br />Appendix A. Perl Summary <br />Appendix B. Installing Perl <br /> <br />I really thought this was a 5-star book. However, it is not obvious from the title that this is really volume two of a two volume set of books on Perl programming for the biologist, so I can see where the lower ratings might have come from. This is the sequel to his earlier beginner's book on Perl. Now, he goes further into usages of Perl. While experienced programmers will not find these terribly challenging, they are not the intended audience. <br /> <br />Of the topics, the most important is where he shows you how to interface with a SQL database. Given the sheer mass of sequence data generated these days, it is inevitable that efficient database usage be done. So he gives a quick tour of relational database design. With examples of how Perl has modules to submit and query the database. The treatment is somewhat cursory, since he has other, non-database topics to cover. <br /> <br />Of those, he includes CGI programming. This might be questionable. CGI code has proved incredibly hard to scale. Maybe he felt the necessity to include code for handling web servers. Unfortunately, a typical reader won't have enough experience to be aware of CGI's problems. The danger is that she actually starts coding CGI Perl. The true debugging and maintenance costs will not show up till later. | |
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| By: Neil C. Jones, Pavel A. Pevzner ISBN: 0262101068 Publisher: The MIT Press Release Date: 01 August, 2004 Bioscience book rank: 252901 | Este livro é excelente por várias razões. Entre elas posso citar o fato de estar totalmente voltado ao aprendizado por exemplos, sempre de forma a relacionar um problema computacional com um problema em bioinformática. É um livro muito abrangente, cobre muito bem os tópicos relacionados a alinhamentos e comparações de sequências. Seu capítulo sobre Algoritmos com Grafos é o meu preferido. O autor consegue passar as noções fundamentais com muita simplicidade, de forma que qualquer pessoa possa aprender num ritmo bem rápido. This is the first book that I've read regarding bioinformatics, so Im updating this as my class moves along. You better have a grasp of basic data structures prior to beginning this book and background with a programming language as there is very little hand-holding in this text. A bio background makes it all more interesting but certainly is not critical. There are no sample code or sources printed with the book nor is there an included CD nor answers to exercises. There is an associated web site where some ideas may be had and errata found/reported, but its not very active that I have seen. The pseudo code in the book is very python-like so easy to make use of. I personally transfer the book's concepts to C/C++ (habit) without much problem, except sometimes my results differ from the book. Apparently these are book bugs, so be sure to check the web site out if unexpected things pop up. <br />Presently my class is in chapter 8 (of 12) and looking back I would like to caution that some data processing algorithms will drive a computer's CPU quite hard so be aware of battery-munching & heat. My only bones with this book so far are the alphabet soup of variables and lack of answers to exercises. It would be nice if variable definitions were refreshed at the beginning of pseudo code samples. <br />I like this book as an algorithms text over traditional texts because the applications are much more fascinating. Imagine searching for something and you don't know where that something is. On top of that add not even knowing exactly what it is you are looking for. And when you do find it, its not even in the data searched! This may sound unlikely or even impossible, but it is neither. Rather, its very cool. <br />4-stars I knew most of the stuff before I opened the first page. It's basically teaching data structures 101 using a few watered down bioinformatic problems for motivation. The lack of applied problems involving real data was most disappointing. It does have a lot of the type questions that some nerd (me one day :P) might ask you on a job interview. The questions are also a good way to kill time if you have nothing better to do. I give the book credit for stressing dynamic programming. I believe that this is one of the most important concepts in problem solving. <br /> <br />3 stars because I think it is a fairly good introduction for fledgling computer scientists BUT not a good reference for comptuer scientists trying to apply their skills to solve bioinformatic problems. <br /> <br /> | |
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| By: Cynthia Gibas, Per Jambeck ISBN: 1565926641 Publisher: O'Reilly Media, Inc. Release Date: 15 April, 2001 Bioscience book rank: 147252 | This book is the worst I've ever purchased. It has been no help whatsoever. It had a couple examples of PERL programming...big deal.<p>The 5-star ratings are obvious shills (one reviewer wrote a very long review and has never reviewed anything else) This book is a good introduction to Bioinformatics and to what it takes to get started in the field. Some reviewers deride it as too superficial or as too Unix-centric, but I think those are two of its strengths. The authors lay no claim to having written the definitive work on the subject of Bioinformatics, and they freely admit that they come in with a certain bias. If you are serious about Bioinformatics this won't be your last book anyway, but it'll get you started.<p>That said, I found the material a bit uneven. The authors tend to jump from almost trivial stuff to very complex in a heartbeat, and they sometimes use a concept or command before it can be properly understood One example: Introducing the Unix commands head and tail, then moving on to split and csplit. The introduction to regular expressions as needed by csplit follows a few pages later.<p>Nevertheless, I plan to use this book as a companion text to my own sequence of computer classes for biologists, and I think it will serve that purpose very well. We are all well aware that it is impossible to write a book on bioinformatics satisfying all types of readers. That is the reason why we are spending much time on finding a book that we can say "This book is just for me!"<p>Well, this book is not a self-teaching book by itself. Don't expect that things will become clear to understand after reading this book.<p>If your expectation is just to taste flavor of bioinformatics and to use it as a reference book, then this book is right for you. | |
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| By: David W. Mount ISBN: 0879697121 Publisher: Cold Spring Harbor Laboratory Press Release Date: July, 2004 Bioscience book rank: 154021 | 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: Andreas D. Baxevanis, B. F. Francis Ouellette ISBN: 0471478784 Publisher: Wiley-Interscience Release Date: 29 October, 2004 Bioscience book rank: 151537 | Book came quickly but edges were bent, not like a new book. Returned it and got full refund. The book is a collection of chapters by different authors addressing software tools for various problems: database search, multiple sequence alignment, gene prediction, protein structure prediction, etc. A big flaw is that all of the authors assume a different level of prior background and have rather different emphases.<p>I'd have to agree with the other reviewer that Chapters 1 & 17, which constitute 10% of the book, are wasted paper. No one in 2001 (when the book was published), let alone 2004, needs Chapter 1's lengthy explanation of what e-mail and web browsers are. And the perl program at the anticlimax of Chapter 17 was ... anticlimactic.<p>The book is to a great extent a catalog of available software tools. With the exception of the chapters on multiple alignment and phylogeny, the emphasis is on not on how the tools work but how to operate them -- to the of saying "at this URL there is a web page where you can either paste in your sequence or upload a file". The idea of invoking a program through a Unix command line is more than once presented as a truly daunting prospect. The authors generally do a good job of emphasizing that the programs are the beginning of analysis and not the end; the results must always be viewed somewhat skeptically with an expert eye.<p>If you're coming at the book as a biologist, you will probably find it to be a useful catalog of software, though undoubtedly dated by now. If you're coming at it from the informatics side, you're going to need some background... a book like Dwyer's, Setubal and Meidanis's, or Mount's will get you up to speed on the algorithm aspects of the field with simplified versions of many of the big problems. Then you can look at this book to find good pointers to the ways the real-world versions have been addressed.<p>The book was published three years ago and, being to a large extent an index of the work of others, is necessarily no longer up to date in a fast-moving field. It needs a revision and, in the meantime, it would make more sense to snag a used copy than to pay full price for a new book. Like any survey, it seems to touch the major features only. And, as others have pointed out, the tools change but the book doesn't. <br /> <br />I think this is a good, brief introduction to the wide variety of bioinformatic tools and databases on the internet. It describes the major features of each, and the kinds of results that each tool is good for. After that, the serious user will go to the sources of each tool or database, to learn more about the specifics as of the moment. No book can hope to keep up with the weekly enhancements at the major repositories. <br /> <br />I emphasize that this is for tools users, not tool makers. It addresses the working scientists who already know their subjects and their needs. This skips over the algorithms in favor of higher level descriptions, and skips over many of the biological reasons for the tools described. Better-informed tool users get better answers from the tools, true. At some point, though, the biologists want to skip the theory, skip the introduction to subjects in which they're experts, and get on with their science. I don't think this book was ever meant for people - and I'm one - who want full details of the algorithms. <br /> <br />I agree, the book treats its many subjects in a shallow way. I think that is by intent, since the book's real goal is breadth and its target is a reader who knows the basic science. It's a bit off the center of my interests, but I've found it helpful. | |
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| By: Warren J. Ewens, Gregory Grant ISBN: 0387400826 Publisher: Springer Release Date: 30 September, 2005 Bioscience book rank: 202936 | I'm a Statistics PhD student so you can condition on my prior to get at what's really going on with this book.
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<br />Bioinformatics is a departure from "regular" statistics and looks awfully messy at first pass. The sorts of assumptions one typically makes in other areas of statistical inference are patently false, so new techniques and intuitions have to be built up in order to attack these kinds of problems. This book does an excellent job of balancing the technical details with the necessary intuitions so one can really get a firm grasp on what's going on.
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<br />I wouldn't recommend this book to someone who hasn't done statistics at at least an advanced undergrad level (e.g., comfortable with Probability at the Ross-level and Statistical Inference at the Casella/Berger-level). But for people really interested in the material and coming from a solid statistical background the book is an excellent resource.
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<br />I would also strongly recommend it to teach out of. I was impressed with the 1st edition of this book for its most comprehensive and elegant of statistical techniques in bioinformatics. The book is slightly below the level of the now classic M S Waterman (1995)book:[[ASIN:0412993910 Introduction to Computational Biology: Maps, Sequences and Genomes (Interdisciplinary Statistics)]]. But this book is more update in some areas and has much more background materials on probability and statistics, which should provide a solid basis for understanding bioinformatics. Its pedagorical sense is unparalleled. It would make a very good choice for a stat/math oriented introduction to bioinformatics (as opposed to algorithimc/database oriented approach in cs). | |
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| By: Marketa Zvelebil, Jeremy Baum ISBN: 0815340249 Publisher: Garland Science Release Date: 29 August, 2007 Bioscience book rank: 74708 | The book I ordered was old but the one I received appeared as brand new. And also it reached unexpectedly sooner during Christmas holidays!! | |
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