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| By: Ralf Hofestädt, Thomas Lengauer, Markus Löffler, Dietmar Schomburg ISBN: 3540633707 Publisher: Springer Release Date: 12 September, 1997 Bioscience book rank: 4417068 | ||
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| By: D. Higgins, Willie Taylor ISBN: 0199637911 Publisher: Oxford University Press, USA Release Date: 15 October, 2000 Bioscience book rank: 5307962 | The title of this collection of texts is slightly misleading because the book is entirely devoted to proteins. It does not cover either DNA sequence analysis or nucleic acid structure prediction. Nor does it expose methods of "genome informatics" such as computer-assisted genome annotation or function-associated genome segmenting. Moreover the problematics of molecular evolution is covered only as much as protein phylogeny and homology is discussed. There is virtually no mention of methods for studying genome evolution.<p>Despite the above negatives the book provides a remarkable survey and tutorial of protein sequence and structure analysis. The editors introduction (Higgins and Taylor) is brief, precise and to the point. Chapter 1 (Jones and Hadley) and Chapter 2 (Johnson and Lehtonen) constitute a tutorial of protein structure analysis. Both chapters are likely to be informative for the beginners and enjoyable by the experts. Chapter 6 (Heringa) and Chapter 8 (Yona and Brenner) are real masterpieces and should be read by all practitioners of bioinformatics as well as by all individuals who want to learn methods of sequence analysis. These two chapters and the editor's introduction make the entire book a valuable desk reference for practitioners and a candidate textbook for students. Just to be completely fair I need to say that Chapter 5 (Henikoff and Henikoff) is potentially confusing and poorly written. The same - although to a lesser degree - applies to Chapter 9 (Harper.)<p>In summary: Higgins and Taylor have assembled a superb collection of short texts in protein sequence and structure analysis. Practitioners of both bioinformatics and protein biochemistry should use this book as a desk reference. Those who want to learn about bioinformatics will certainly benefit from reading selected chapters of this book as well. The book would not be harmed if it failed to contain confusing and poorly written Chapter 5 (Henikoff and Henikoff) and Chapter 9 (Harper.) Gives a great overview of bioinformatic techniques in "sequence analysis and searching" and "protein structure analysis and prediction." Then it gives an overview of gene databases online as do all other bioinformatics books. The best part about it is that it spends 70% talking about new biology techniques which greatly helps a computer scientist like me to get into the field. Recommended. | |
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| By: Paul Weston ISBN: 0470857722 Publisher: Wiley Release Date: 07 December, 2004 Bioscience book rank: 2032719 | I sat down and read through it at a recent bioinformatics conference in Detroit where Wiley had an exhibit. It's applicable for people who just learned how to code and have not had any formal software development training. In my experience, this type of scenario happens a lot: an amateur buys something such as Visual Basic and suddenly he or she is writing code. Someone in the office hears about it and things begin to explode. Suddenly, there is a ton of poorly tested, poorly engineered code, but the amateur is seen as an incredible genious because they can fix the mistakes they made - mistakes that probably should have never happened. So if you have someone in your office who got their hands on a compiler for the first time, you might want to read this to find out that there is more to programming than just writing code. I thought the text was well written for both managers and novice coders. <br /> <br />However, if you're an experienced developer (ie you have a four year degree in CS or are familiar with concepts of software testing, requirements gathering etc)you won't find any great insights in this one that makes it worth the price. It's basic software engineering information for software developers getting started. <br /> <br />As far as my comment on price, I'll add one more thing. If software development is completely new to you, this is a good start. After all, if it saves you from making some of those horrible mistakes I alluded to or opens your eyes so that it encourages you to take a formal course in software engineering and testing, then this is even more justification to encourage your boss to buy this text for you. <br /> <br />Again, this is a bit of a mixed bag for a review, and I'm a bit prejudiced about appropriate text books...again, maybe the easy read will encourage some beginners not to take the "cowboy" approach to software development. Get this book as a start...and then get some books with much more depth in critical subject areas such as those by Shari Pfleeger, Len Bass and Paul Jorgensen. <br /> <br />Part of me says give it two stars, part of me says give it five stars. It really depends on your background. Just don't expect this book to make you an expert in bioinformatics...it's basic software engineering with bioinformatics as the backround subject. | |
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| By: UNKNOWN ISBN: Publisher: Chapman & Hall/CRC Release Date: Bioscience book rank: 38842 | ||
| By: Elebeoba May, John Enderle ISBN: 1598292803 Publisher: Morgan & Claypool Publishers Release Date: 07 October, 2007 Bioscience book rank: | ||
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| By: Peter Markstein, Ying Xu ISBN: 1860948723 Publisher: Imperial College Press Release Date: 12 September, 2007 Bioscience book rank: 372005 | ||
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| By: Roderic Guigo, Dan Gusfield ISBN: 3540442111 Publisher: Springer Release Date: 07 May, 2004 Bioscience book rank: 5546385 | ||
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| By: Jeremy J. Ramsden ISBN: 1402021410 Publisher: Springer Release Date: 14 October, 2004 Bioscience book rank: 2189742 | ||
| By: W. Conard Holton ISBN: Publisher: Thomson Gale Release Date: 17 October, 2005 Bioscience book rank: | ||
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| By: Christoph W. Sensen ISBN: 3527305416 Publisher: Wiley-VCH Release Date: 10 June, 2002 Bioscience book rank: 2104549 | ||
Related books in this category:
bioinformatics, computational biology, sequence analysis, protein structure, data mining, biostatistics
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