Articles liés à Bayesian Networks in R: with Applications in Systems...
Synopsis
Bayesian Networks in R with Applications in Systems Biology is unique as it introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is also gradually increased across the chapters with exercises and solutions for enhanced understanding for hands-on experimentation of the theory and concepts. The application focuses on systems biology with emphasis on modeling pathways and signaling mechanisms from high-throughput molecular data. Bayesian networks have proven to be especially useful abstractions in this regard. Their usefulness is especially exemplified by their ability to discover new associations in addition to validating known ones across the molecules of interest. It is also expected that the prevalence of publicly available high-throughput biological data sets may encourage the audience to explore investigating novel paradigms using theapproaches presented in the book.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Radhakrishnan Nagarajan, Ph.D.
Dr. Nagarajan is an Associate Professor in the Division of Biomedical Informatics, Department of Biostatistics at the College of Public Health, University of Kentucky, Lexington, USA. His areas of research falls under evidence-based science that demands knowledge discovery from high-dimensional molecular and observational healthcare data sets using a combination of statistical algorithms, machine learning and network science approaches.
Contact: Division of Biomedical Informatics/Department of Biostatistics, College of Public Health, University of Kentucky, 725 Rose Street, MDS 230F, Lexington, KY 40536-0082.
Marco Scutari, Ph.D.
Dr. Scutari studied Statistics and Computer Science at the University of Padova, Italy. He earned his Ph.D. in Statistics in Padova under the guidance of Prof. A. Brogini, studying graphical model learning. He is now Research Associate at the Genetics Institute, University College London (UCL). His research focuses on the theoretical properties of Bayesian networks and their applications to biological data, and he is the author and maintainer of the bnlearn R package.
Contact: Genetics Institute, University College London Darwin Building, Room 212 London, WC1E 6BT United Kingdom.
Sophie Lèbre, Ph.D.
Dr. Lèbre is a Lecturer in the Department of Computer Science at the University of Strasbourg, France.
She originally earned her Ph.D. in Applied Mathematics at the University of Evry-val-d'Essone (France) under the guidance of Prof. B. Prum. Her research focuses on graphical modeling and dynamic Bayesian network inference, devoted to recovering genetic interaction networks from post genomic data. She is the author and maintainer of the G1DBN and the ARTIVA R packages for dynamic Bayesian network inference.
Contact: LSIIT, Equipe BFO, Pôle API, Bd Sébastien Brant - BP 10413, F -67412 Illkirch CEDEX, France.
Contact: Division of Biomedical Informatics/Department of Biostatistics, College of Public Health, University of Kentucky, 725 Rose Street, MDS 230F, Lexington, KY 40536-0082.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer
- Date d'édition2013
- ISBN 10 1461464455
- ISBN 13 9781461464457
- ReliureBroché
- Langueanglais
- Nombre de pages172
- Coordonnées du fabricantnon disponible
Acheter neuf
Afficher cet article
EUR 75,30
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délais
Résultats de recherche pour Bayesian Networks in R: with Applications in Systems...
Image d'archives
Bayesian Networks in R: with Applications in Systems Biology (Use R!, 48)
Edité par
Springer, 2013
ISBN 10 : 1461464455
ISBN 13 : 9781461464457
Ancien ou d'occasion
Couverture souple
Vendeur : Powell's Bookstores Chicago, ABAA, Chicago, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : Used - Very Good. Pap. Minor shelf wear. Top corner of front wrap creased. Else a bright, clean copy. Very Good. N° de réf. du vendeur Sact00404
Quantité disponible : 1 disponible(s)
Image d'archives
Bayesian Networks in R: with Applications in Systems Biology (Use R! (48))
Edité par
Springer, 2013
ISBN 10 : 1461464455
ISBN 13 : 9781461464457
Ancien ou d'occasion
Couverture souple
Vendeur : SecondSale, Montgomery, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc. N° de réf. du vendeur 00083174488
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Bayesian Networks in R
Edité par
Springer New York, 2013
ISBN 10 : 1461464455
ISBN 13 : 9781461464457
Neuf
Kartoniert / Broschiert
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Represents a unique combination of introduction to concepts and examples from open-source R softwareEach chapter is accompanied by examples and exercises with solutions for enhanced understanding and experimentationUseful for students and r. N° de réf. du vendeur 4199067
Quantité disponible : Plus de 20 disponibles
Image d'archives
Bayesian Networks in R : with Applications in Systems Biology
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
PF. Etat : New. N° de réf. du vendeur 6666-IUK-9781461464457
Quantité disponible : 10 disponible(s)
Image d'archives
Bayesian Networks in R: with Applications in Systems Biology (Use R!, 48)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In English. N° de réf. du vendeur ria9781461464457_new
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Bayesian Networks in R : With Applications in Systems Biology
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 19194701-n
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Bayesian Networks in R
Edité par
Springer New York, Springer US Apr 2013, 2013
ISBN 10 : 1461464455
ISBN 13 : 9781461464457
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bayesian Networks in R with Applications in Systems Biology is unique as it introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is also gradually increased across the chapters with exercises and solutions for enhanced understanding for hands-on experimentation of the theory and concepts. The application focuses on systems biology with emphasis on modeling pathways and signaling mechanisms from high-throughput molecular data. Bayesian networks have proven to be especially useful abstractions in this regard. Their usefulness is especially exemplified by their ability to discover new associations in addition to validating known ones across the molecules of interest. It is also expected that the prevalence of publicly available high-throughput biological data sets may encourage the audience to explore investigating novel paradigms using theapproaches presented in the book. 172 pp. Englisch. N° de réf. du vendeur 9781461464457
Quantité disponible : 2 disponible(s)
Image d'archives
Bayesian Networks in R: with Applications in Systems Biology
Edité par
Springer-Verlag New York Inc., 2013
ISBN 10 : 1461464455
ISBN 13 : 9781461464457
Neuf
Paperback / softback
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 280. N° de réf. du vendeur C9781461464457
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Bayesian Networks in R : with Applications in Systems Biology
Edité par
Springer New York, Springer US, 2013
ISBN 10 : 1461464455
ISBN 13 : 9781461464457
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Bayesian Networks in R with Applications in Systems Biology is unique as it introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is also gradually increased across the chapters with exercises and solutions for enhanced understanding for hands-on experimentation of the theory and concepts. The application focuses on systems biology with emphasis on modeling pathways and signaling mechanisms from high-throughput molecular data. Bayesian networks have proven to be especially useful abstractions in this regard. Their usefulness is especially exemplified by their ability to discover new associations in addition to validating known ones across the molecules of interest. It is also expected that the prevalence of publicly available high-throughput biological data sets may encourage the audience to explore investigating novel paradigms using theapproaches presented in the book. N° de réf. du vendeur 9781461464457
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Bayesian Networks in R
Edité par
Springer New York, Springer US Apr 2013, 2013
ISBN 10 : 1461464455
ISBN 13 : 9781461464457
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -Bayesian Networks in R with Applications in Systems Biology is unique as it introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is also gradually increased across the chapters with exercises and solutions for enhanced understanding for hands-on experimentation of the theory and concepts. The application focuses on systems biology with emphasis on modeling pathways and signaling mechanisms from high-throughput molecular data. Bayesian networks have proven to be especially useful abstractions in this regard. Their usefulness is especially exemplified by their ability to discover new associations in addition to validating known ones across the molecules of interest. It is also expected that the prevalence of publicly available high-throughput biological data sets may encourage the audience to explore investigating novel paradigms using theapproaches presented in the book.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch. N° de réf. du vendeur 9781461464457
Quantité disponible : 2 disponible(s)