Network inference in molecular biology : a hands-on framework

Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for ever...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Lingeman, Jesse M., Shasha, Dennis Elliott, 1955-...., chercheur en informatique, biomathématiques (Auteur)
Format: Livre numérique
Langue:Anglais
Publié: New York, NY : Springer New York 2012.
Cham : Springer Nature
Collection:SpringerBriefs in Electrical and Computer Engineering
Sujets:
Accès en ligne:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Note: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Network Inference in Molecular Biology, Texte imprimé, 9781461431145
• Network Inference in Molecular Biology, Texte imprimé, 9781461431121
Description
Résumé:Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for every data set. Network Inference in Molecular Biology examines the current techniques used by researchers, and provides key insights into which algorithms best fit a collection of data. Through a series of in-depth examples, the book also outlines how to mix-and-match algorithms, in order to create one tailored to a specific data situation. Network Inference in Molecular Biology is intended for advanced-level students and researchers as a reference guide. Practitioners and professionals working in a related field will also find this book valuable.
Description:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9781461431138
ISSN:2191-8120
Accès: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. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017