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kbmtl specifications

Information


Unique identifier OMICS_13767
Name kbmtl
Alternative name Kernelized Bayesian Multitask Learning
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages MATLAB, R
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Mehmet Gönen

Publication for Kernelized Bayesian Multitask Learning

kbmtl citations

 (3)
library_books

Drug Response Prediction as a Link Prediction Problem

2017
Sci Rep
PMCID: 5220354
PMID: 28067293
DOI: 10.1038/srep40321

[…] In order to better understand the accuracy of our method, we compare it against the top performing approach in the DREAM Drug Sensitivity Prediction Challenge, Gonen and Margolin’s kernelized Bayesian multitask learning (KBMTL) algorithm. This approach attempts to predict the susceptibility of each cell line to a panel of drugs simultaneously, which is comparable with our method […]

library_books

Multitask learning improves prediction of cancer drug sensitivity

2016
Sci Rep
PMCID: 4994023
PMID: 27550087
DOI: 10.1038/srep31619

[…] We implemented the kbmtl R package provided in the paper by Gonen et al. on the CCLE, NCI60 and CTD2 dataset. Following instructions in the paper, we applied a Gaussian on the training set with all the default parameter […]

library_books

A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction

2015
PLoS One
PMCID: 4684346
PMID: 26658256
DOI: 10.1371/journal.pone.0144490

[…] on is shown for GDSC dataset in Table A in .For performance comparison purposes, we report results of Copula based MRF (CMRF) along with univariate RF (denoted by RF), Covariance based MRF (VMRF) and Kernelized Bayesian Multitask Learning (KBMTL) [] approaches. KBMTL is Bayesian formulation that combines kernel based non-linear dimensionality reduction and regression in a multitask learning framew […]

Citations

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kbmtl institution(s)
Sage Bionetworks, Seattle, WA, USA
kbmtl funding source(s)
The Integrative Cancer Biology Program (ICBP) of the National Cancer Institute (1U54CA149237); Cancer Target Discovery and Development (CTDD) Network of the National Cancer Institute (1U01CA176303)

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