Bayesian networks in R : with applications in systems biology
Bayesian Networks in R with Applications in Systems Biology 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 gradually increased across the chapters wit...
Guardat en:
| Autors principals: | , , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2013. |
| Col·lecció: | Use R!
48 |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Bayesian networks in R, with applications in systems biology, Radhakrishnan Nagarajan, Marco Scutari, Sophie Lèbre, New York [etc.], Springer, 2013, 1 vol. (XIII-157 p.), Use R!, 978-1-4614-6445-7 • Bayesian Networks in R, Texte imprimé, 9781461464471 • Bayesian networks in R, with applications in systems biology, Radhakrishnan Nagarajan, Marco Scutari, Sophie Lèbre, New York [etc.], Springer, 2013, 1 vol. (XIII-157 p.), Use R!, 978-1-4614-6445-7 |
| Sumari: | Bayesian Networks in R with Applications in Systems Biology 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 gradually increased across the chapters with exercises and solutions for enhanced understanding and hands-on experimentation of key concepts. Applications focus 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 regards as exemplified by their ability to discover new associations while validating known ones. It is also expected that the prevalence of publicly available high-throughput biological and healthcare data sets may encourage the audience to explore investigating novel paradigms using the approaches presented in the book |
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| Descripció de l’ítem: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9781461464464 |
| ISSN: | 2197-5744 |
| Accés: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |