data mining bioinformatics books

	Data Mining in Bioinformatics (Advanced Information and Knowledge Processing)
	By: Jason T. L. Wang, Mohammed J. Zaki, Hannu T.T. Toivonen, Dennis E. Shasha ISBN: 1852336714 Publisher: Springer Release Date: 17 September, 2004 Bioscience book rank: 953441
	Visualization and data mining software extend Bioinformatic capabilities.: An article from: Instrument Business Outlook
	By: UNKNOWN ISBN: Publisher: Strategic Directions International Inc. (SDI) Release Date: 30 July, 2005 Bioscience book rank:
	Data Mining for Bioinformatics
	By: Sumeet Dua ISBN: 0849328012 Publisher: CRC Release Date: 15 July, 2009 Bioscience book rank: 5613833
	Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 6th European Conference, EvoBIO 2008, Naples, Italy, March 26-28, 2008, Proceedings (Lecture Notes in Computer Science)
	By: Elena Marchiori, Jason H. Moore ISBN: 3540787569 Publisher: Springer Release Date: 01 April, 2008 Bioscience book rank:
	Advanced Data Mining Technologies in Bioinformatics
	By: Hui-Huang Hsu ISBN: 1591408644 Publisher: Idea Group Publishing Release Date: 25 May, 2006 Bioscience book rank: 2416910
	Data Mining and Bioinformatics: First International Workshop, VDMB 2006, Seoul, Korea, September 11, 2006, Revised Selected Papers (Lecture Notes in Computer Science)
	By: Mehmet M Dalkilic, Sun Kim, Jiong Yang ISBN: 3540689702 Publisher: Springer Release Date: 13 February, 2007 Bioscience book rank: 3737046
	Data Mining: Multimedia, Soft Computing, and Bioinformatics
	By: Sushmita Mitra, Tinku Acharya ISBN: 0471460540 Publisher: Wiley-Interscience Release Date: 25 September, 2003 Bioscience book rank: 1529935	Although (necessarily) brief, this is a good overview of data mining techniques that can be applied to bioinformatics. Some of the text could have benefited from a bit more review by an editor, but the book is highly readable and usable. As there are few such books as far as I know, Mitra and Acharya are to be commended for doing a nice job. This book is a distinct addition to the field of data mining in its coverage of topics and ideas.<br>The good point about this book is that it explains the central concepts in great details with the required rigour and also puts in examples to make them understandable. Its not a typical Theorem , Lemma book , but also do not shy away from the mathematical complexities.<br>There is adequate coverage of all the standard topics and additionally there are interesting sections on Rough sets and Fuzzy sets, which are generally not available everywhere.<br>The most important point about this book is that it gives a thorough coverage of Multimedia data and web data and biological data, which is very dificult to get in one place in any book.<br>A researcher or anyone with adequate background in Mathematics will find this book very helpful in their research.<br>References are also pretty much exhaustive.<br>I would have liked to see some more coverage on datawarehouse and complexity analysis of the algorithms mentioned, also some language level implementation examples at least in some appendix to the book. Also a paperback edition is needed as the price is quite high.
	Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 5th European Conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007, Proceedings (Lecture Notes in Computer Science)
	By: Elena Marchiori, Jason H. Moore, Jagath C. Rajapakse ISBN: 354071782X Publisher: Springer Release Date: 03 May, 2007 Bioscience book rank: