Da: Goodwill of Colorado, COLORADO SPRINGS, CO, U.S.A.
Condizione: very_good. Item may have minor cosmetic defects marks, wears, cuts, bends, crushes on the cover, spine, pages or dust cover. Shrink wrap, dust covers, or boxed set case may be missing. Item may contain remainder marks on outside edges, which should be noted in Product Details. Item may be missing bundled media.
Da: Your Online Bookstore, Houston, TX, U.S.A.
hardcover. Condizione: Very Good.
Da: Anybook.com, Lincoln, Regno Unito
EUR 25,15
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,950grams, ISBN:9780123704764.
Lingua: Inglese
Editore: Morgan Kaufmann 2009-05-12, 2009
ISBN 10: 0123704766 ISBN 13: 9780123704764
Da: Chiron Media, Wallingford, Regno Unito
EUR 55,04
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New.
EUR 66,26
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. xii + 406 150 Illus.
Condizione: New. pp. xii + 406.
Lingua: Inglese
Editore: Morgan Kaufmann Publishers, 2009
ISBN 10: 0123704766 ISBN 13: 9780123704764
Da: Revaluation Books, Exeter, Regno Unito
EUR 62,23
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 1st edition. 424 pages. 9.30x7.50x1.10 inches. In Stock.
EUR 76,31
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. xii + 406.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 56,55
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 150,00
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis. 424 pp. Englisch.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 156,09
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis.