9780691117621 - Genomic Signal Processing: 18 (princeton Series in Applied Mathematics) by Ilya Shmulevich; Edward R. Dougherty (12 results)
Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
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Language: English
Published by Princeton University Press, US, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Hardback. Condition: New. Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, b…iology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine.Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.
Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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hardcover. Condition: New. In shrink wrap. Looks like an interesting title.
Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Language: English
Published by Princeton University Press, US, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Hardback. Condition: New. Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, b…iology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine.Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.
Language: English
Published by Princeton Univ Pr, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Hardcover. Condition: Brand New. 298 pages. 9.50x6.25x1.00 inches. In Stock.
Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Genomic signal processing (GSP) requires the development of both nonlinear dynamical models that represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these de…velopments by providing mathematical def.
Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
- Print on Demand
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Buch. Condition: Neu. Genomic Signal Processing | Ilya Shmulevich (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2007 | Princeton University Press | EAN 9780691117621 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Language: English
Published by Princeton University Press, 2007
Series: Book 21 of 33 - Princeton Series in Applied Mathematics
- Hardcover
- Print on Demand
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat ge…netic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.
