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In den WarenkorbZustand: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
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In den WarenkorbZustand: Good. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages.
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In den WarenkorbZustand: New. pp. 306 Illus.
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In den WarenkorbZustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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In den WarenkorbZustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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In den WarenkorbZustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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In den WarenkorbZustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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In den WarenkorbPaperback. Zustand: Brand New. 384 pages. 9.25x6.10x0.88 inches. In Stock.
Verlag: Springer US, Springer US Dez 2002, 2002
ISBN 10: 1402072600 ISBN 13: 9781402072604
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 53,49
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In den WarenkorbBuch. Zustand: Neu. Neuware -In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 384 pp. Englisch.
Verlag: Springer US, Springer New York Mär 2013, 2013
ISBN 10: 1475778090 ISBN 13: 9781475778090
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 53,49
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 388 pp. Englisch.
EUR 49,55
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In den WarenkorbTaschenbuch. Zustand: Neu. A Practical Approach to Microarray Data Analysis | Daniel P Berrar (u. a.) | Taschenbuch | xvi | Englisch | 2009 | Springer New York | EAN 9781441912268 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Anbieter: preigu, Osnabrück, Deutschland
EUR 49,55
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In den WarenkorbTaschenbuch. Zustand: Neu. Knowledge Discovery in Life Science Literature | International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings | Eric G. Bremer (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2006 | Springer | EAN 9783540328094 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
EUR 50,10
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In den WarenkorbTaschenbuch. Zustand: Neu. A Practical Approach to Microarray Data Analysis | Daniel P. Berrar (u. a.) | Taschenbuch | xvi | Englisch | 2013 | Springer US | EAN 9781475778090 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Verlag: Springer, Berlin, Springer Berlin Heidelberg, Springer, 2006
ISBN 10: 3540328092 ISBN 13: 9783540328094
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 57,68
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 111,51
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In den WarenkorbZustand: New. In.
Verlag: Springer US, Springer New York, 2013
ISBN 10: 1475778090 ISBN 13: 9781475778090
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 58,56
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 111,51
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In den WarenkorbZustand: New. In.
EUR 59,27
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art and of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduate- or graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science.
EUR 59,97
Währung umrechnenAnzahl: 1 verfügbar
In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.
EUR 116,33
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In den WarenkorbZustand: 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.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 111,53
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In den WarenkorbTaschenbuch. Zustand: 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.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 159,90
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In den WarenkorbBuch. Zustand: 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.