Drug susceptibility prediction against a panel of drugs using kernelized Bayesian multitask learning-Reference-Cited by-同舟云学术

Drug susceptibility prediction against a panel of drugs using kernelized Bayesian multitask learning

Published:2014-08-22 Issue:17 Volume:30 Page:i556-i563
ISSN:1460-2059
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Gönen Mehmet,Margolin Adam A.

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/30/17/i556/17150268/btu464.pdf

Reference24 articles.

1. Bayesian analysis of binary and polychotomous response data;Albert;J. Amer. Statist. Assoc.,1993

2. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity;Barretina;Nature,2012

3. Variational algorithms for approximate Bayesian inference;Beal,2003

4. Variational relevance vector machines;Bishop,2000

5. Multitask learning;Caruana;Mach. Learn.,1997

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