Barah pankaj (30 risultati)
Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
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Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: California Books, Miami, FL, U.S.A.California Books
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Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 84,45
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Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. First edition Includes bibliographical references and index.
Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 82,93
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Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 82,30
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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 82,94
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Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Condizione: New. In.
Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Brossura
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 96,19
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Condizione: New.
Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 111,59
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Condizione: As New. Unread book in perfect condition.
Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
Barah, Pankaj/ Bhattacharyya, Dhruba Kumar/ Kalita, Jugal Kumar
- Brossura
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 111,41
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Paperback. Condizione: Brand New. 378 pages. 9.18x6.12x9.21 inches. In Stock.
Altre immagini- Brossura
Da: preigu, Osnabrück, Germaniapreigu
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EUR 69,15
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Taschenbuch. Condizione: Neu. Gene Expression Data Analysis | A Statistical and Machine Learning Perspective | Pankaj Barah (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | Chapman and Hall/CRC | EAN 9781032055756 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 Mün…chen, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu.
Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
Barah, Pankaj Pankaj Barah, Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita,
- Rilegato
Da: Chiron Media, Wallingford, Regno UnitoChiron Media
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EUR 167,15
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hardcover. Condizione: New.
Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 188,49
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Condizione: New.
Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 192,49
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Condizione: New.
- Rilegato
Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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EUR 214,43
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Condizione: New. In.
Gene Expression Data Analysis : A Statistical and Machine Learning Perspective
Barah, Pankaj; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 214,60
EUR 17,59 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: As New. Unread book in perfect condition.
- Rilegato
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 225,08
EUR 7,62 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 3 disponibili
Condizione: New.
- Rilegato
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 238,81
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Condizione: New.
- Rilegato
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 249,51
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Condizione: New.
- Rilegato
Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 255,72
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
Barah, Pankaj/ Bhattacharyya, Dhruba Kumar/ Kalita, Jugal Kumar
- Rilegato
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 281,52
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Hardcover. Condizione: Brand New. 392 pages. 9.25x6.00x1.00 inches. In Stock.
- Brossura
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 72,00
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput te…chnologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge.Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data.Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systemsA systematic overview of the methods for generating gene expression dataBackground knowledge on statistical modeling and machine learning techniquesDetailed methodology of analyzing gene expression data with an example case studyClustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA dataA large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patternsSuitable for multidisciplinary researchers and practitioners in computer science and biological sciences 380 pp. Englisch.
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- Print on Demand
Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 101,87
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Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 82,59
EUR 62,88 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technol…ogies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge.Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data.Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systemsA systematic overview of the methods for generating gene expression dataBackground knowledge on statistical modeling and machine learning techniquesDetailed methodology of analyzing gene expression data with an example case studyClustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA dataA large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patternsSuitable for multidisciplinary researchers and practitioners in computer science and biological sciences.
- Rilegato
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Da: moluna, Greven, Germaniamoluna
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EUR 157,19
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Pankaj Barah is an Assistant professor in Molecular Biology and Biotechnology at Tezpur University. He has received his M.Sc. degree in Bioinformatics (2006) from University of Madras in India and PhD in Co…mputational Systems Biology (20.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 218,28
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HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 223,78
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HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 265,56
EUR 63,67 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies f…or simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge.Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data.Key Features:¿An introduction to the Central Dogma of molecular biology and information flow in biological systemsA systematic overview of the methods for generating gene expression dataBackground knowledge on statistical modeling and machine learning techniquesDetailed methodology of analyzing gene expression data with an example case studyClustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA dataA large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patternsSuitable for multidisciplinary researchers and practitioners in computer science and biological sciences.
