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Fundamentals of Data Mining in Genomics and Proteomics.
Published by Springer, 2006
Language: English
Seller: Antiquariat Thomas Haker GmbH & Co. KG, Berlin, Germany
Association Member: GIAQ
Seller rating 5 out of 5 stars
£ 6.55
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Add to basketHardcover. Condition: Wie neu. 303 S., Like new. Shrink wrapped. / Wie neu. In Folie verschweißt. Sprache: Englisch Gewicht in Gramm: 780.
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Fundamentals of Data Mining In Genomics And Proteomics
Published by Springer Nature (Sie), 2009
ISBN 10: 8184891911 ISBN 13: 9788184891911
Language: English
£ 12.96
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International Edition£ 24.52
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Add to basketCondition: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
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Condition: New. pp. 306 Illus.
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - As natural phenomena are being probed and mapped in ever-greater detail, scientists in genomics and proteomics are facing an exponentially growing vol ume of increasingly complex-structured data, information, and knowledge. Ex amples include data from microarray gene expression experiments, bead-based and microfluidic technologies, and advanced high-throughput mass spectrom etry. A fundamental challenge for life scientists is to explore, analyze, and interpret this information effectively and efficiently. To address this challenge, traditional statistical methods are being complemented by methods from data mining, machine learning and artificial intelligence, visualization techniques, and emerging technologies such as Web services and grid computing. There exists a broad consensus that sophisticated methods and tools from statistics and data mining are required to address the growing data analysis and interpretation needs in the life sciences. However, there is also a 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 different disciplines.
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Fundamentals of Data Mining In Genomics And Proteomics
Published by Springer, 2007
Language: English
£ 103.10
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Add to basketHardcover. Condition: New. ISBN:9780387475080.
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£ 103.47
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Add to basketGebunden. Condition: New. This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniqu.
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Fundamentals of Data Mining in Genomics and Proteomics
Published by Springer Us Dez 2006, 2006
ISBN 10: 0387475087 ISBN 13: 9780387475080
Language: English
£ 142.10
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Add to basketBuch. Condition: Neu. Neuware - As natural phenomena are being probed and mapped in ever-greater detail, scientists in genomics and proteomics are facing an exponentially growing vol ume of increasingly complex-structured data, information, and knowledge. Ex amples include data from microarray gene expression experiments, bead-based and microfluidic technologies, and advanced high-throughput mass spectrom etry. A fundamental challenge for life scientists is to explore, analyze, and interpret this information effectively and efficiently. To address this challenge, traditional statistical methods are being complemented by methods from data mining, machine learning and artificial intelligence, visualization techniques, and emerging technologies such as Web services and grid computing. There exists a broad consensus that sophisticated methods and tools from statistics and data mining are required to address the growing data analysis and interpretation needs in the life sciences. However, there is also a 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 different disciplines.
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£ 157.04
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Add to basketHardcover. Condition: Brand New. Brand New! Fast Delivery, Delivery With In 8-14 working Day Only , USA Edition Original Edition. Excellent Quality, Printing In English Language, Quick delivery by FEDEX & DHL. USPS & UPS Act. Our courier service is not available at PO BOX& APO BOX. Ship from India & United States.
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Hardcover. Condition: NEW. Brand New! Fast Delivery USA Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-14 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Hardcover. Condition: Like New. Like New. book.
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£ 123
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Add to basketHardcover. Condition: New. ISBN:9780387475080.
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£ 80.48
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniqu.
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Fundamentals of Data Mining in Genomics and Proteomics
Published by Springer US Nov 2010, 2010
ISBN 10: 1441942912 ISBN 13: 9781441942913
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
£ 93.31
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations. 304 pp. Englisch.
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Fundamentals of Data Mining in Genomics and Proteomics
Published by Springer-Verlag New York Inc., 2006
ISBN 10: 0387475087 ISBN 13: 9780387475080
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 113.44
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Add to basketHardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 636.
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Fundamentals of Data Mining in Genomics and Proteomics
Published by Springer-Verlag New York Inc., 2010
ISBN 10: 1441942912 ISBN 13: 9781441942913
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 113.44
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 460.
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Fundamentals of Data Mining in Genomics and Proteomics
Published by Springer US, Springer US Nov 2010, 2010
ISBN 10: 1441942912 ISBN 13: 9781441942913
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
£ 93.31
Convert currency£ 29.64 shipping from Germany to United KingdomQuantity: 1 available
Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As natural phenomena are being probed and mapped in ever-greater detail, scientists in genomics and proteomics are facing an exponentially growing vol ume of increasingly complex-structured data, information, and knowledge. Ex amples include data from microarray gene expression experiments, bead-based and microfluidic technologies, and advanced high-throughput mass spectrom etry. A fundamental challenge for life scientists is to explore, analyze, and interpret this information effectively and efficiently. To address this challenge, traditional statistical methods are being complemented by methods from data mining, machine learning and artificial intelligence, visualization techniques, and emerging technologies such as Web services and grid computing. There exists a broad consensus that sophisticated methods and tools from statistics and data mining are required to address the growing data analysis and interpretation needs in the life sciences. However, there is also a 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 different disciplines.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 304 pp. Englisch.
