IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19
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IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19
Fundamentals ofData Mining,-i.\ * inGenomics . and ProteomicsIfEdited byWerner DubitzkyR /1FUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICShttps IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19s: //k hot h u vien .comFUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICSEdited byWerner DubitzkyUniversity of Ulster, Coleraine, Northern IrelandMartin GranzowQuantiom Bioinformatics GmbH & Co. KG, Weingarten/Baden, GermanyDaniel BerrarUniversity of Ulster, Coleraine, Northern Ireland0 Springe IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19rLibrary of Congress Control Number: 2006934109ISBN-13: 978-0-387-47508-0e-ISBN-13: 978-0-387-47509-7ISBN-10: 0-387-47508-7e-ISBN-10: 0-387-47509-5PriIT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19
nted on acid-frcc paper.© 2ỒQ1 Springer Science+Business Media, LLCAll rights reserved. This work may not be translated or copied in whole or in part Fundamentals ofData Mining,-i.\ * inGenomics . and ProteomicsIfEdited byWerner DubitzkyR /1FUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICShttps IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19xcerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden.The use in this publication of trade names, IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19trademarks, service marks and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether orIT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19
not they are subject to proprietary' rights.987654321springer.comPrefaceAs natural phenomena are being probed and mapped in ever-greater detail, scienFundamentals ofData Mining,-i.\ * inGenomics . and ProteomicsIfEdited byWerner DubitzkyR /1FUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICShttps IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19les include data from microarray gene expression experiments, bead-based and microfluidic technologies, and advanced high-throughput mass spectrometry. A fundamental challenge for life scientists is to explore, analyze, and interpret this information effectively and efficiently. To address this chal IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19lenge, traditional statistical methods are being complemented by methods from data mining, machine learning and artificial intelligence, visualizationIT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19
techniques, and emerging technologies such as Web services and grid computing.There exists a broad consensus that sophisticated methods and tools froFundamentals ofData Mining,-i.\ * inGenomics . and ProteomicsIfEdited byWerner DubitzkyR /1FUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICShttps IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19 great deal of confusion about the arsenal of available techniques and how these should be used to solve concrete analysis problems. Partly this confusion is due to a lack of mutual understanding caused by the different concepts, languages, methodologies, and practices prevailing within the differen IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19t disciplines.A typical scenario from pharmaceutical research should illustrate some of the issues. A molecular biologist conducts nearly one hundredIT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19
experiments examining the toxic effect of certain compounds on cultured cells using a microarray gene expression platform. The experiments include difFundamentals ofData Mining,-i.\ * inGenomics . and ProteomicsIfEdited byWerner DubitzkyR /1FUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICShttps IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19s department and briefly explains what kind of questions the data is supposed to answer. Two days later the biologist receives the results which describe the output of a cluster analysis separating the genes into groups of activity and dose. While the groups seem to show interesting relationsilips, IT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19they do not directly address the questions the biologist has in mind. Also, the data sheet accompanying the results shows the original data but in a dIT training fundamentals of data mining in genomics and proteomics dubitzky, granzow berrar 2006 12 19
ifferent order and somehow transformed. Discussing this with the bioinformatician again it turns out that whatvi Prefacethe biologist wanted was not cFundamentals ofData Mining,-i.\ * inGenomics . and ProteomicsIfEdited byWerner DubitzkyR /1FUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICShttpsFundamentals ofData Mining,-i.\ * inGenomics . and ProteomicsIfEdited byWerner DubitzkyR /1FUNDAMENTALS OF DATA MINING IN GENOMICS AND PROTEOMICShttpsGọi ngay
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