Predictive Modeling of Drug Sensitivity

Informationen zum Autor Ranadip Pal is an associate professor in the Electrical and Computer Engineering Department, at the Texas Tech University, USA. His research areas are stochastic modeling and control, genomic signal processing, and computational biology. He is the author of more than 60 peer-reviewed articles including publications in high impact journals such as Nature Medicine and Cancer Cell. He has contributed extensively to robustness analysis of genetic regulatory networks and predictive modeling of drug sensitivity. His research group was a top performer in NCI supported drug sensitivity prediction challenge.

Table des matières

1: Introduction2: Data characterization3: Feature selection and extraction from heterogeneous genomic characterizations4: Validation methodologies5: Tumor growth models6: Overview of predictive modeling based on genomic characterizations7: Predictive modeling based on random forests8: Predictive modeling based on multivariate random forests9: Predictive modeling based on functional and genomic characterizations10: Inference of dynamic biological networks based on perturbation data11: Combination therapeutics12: Online resources13: Challenges

Détails du produit

• Auteurs: Ranadip Pal, Ranadip (Texas Tech University Pal, Pal Ranadip
• Edition: Academic Press London
• Langues: Anglais
• Format d'édition: Livre de poche
• Sortie: 30.11.2016
• EAN: 9780128052747
• ISBN: 978-0-12-805274-7
• Pages: 290
• Catégories: Livres de conseils; Sciences naturelles, médecine, informatique, technique > Médecine > Pharmacie; MEDICAL / Pharmacology, COMPUTERS / Computer Simulation, Pharmacology, Computer modelling & simulation, Computer modelling and simulation