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Raziur Rahman

Showing results (1-10 of 16) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|November 1, 2018
Predictive Modeling of Anti-Cancer Drug Sensitivity from Genetic CharacterizationsRaziur Rahman, Ranadip Pal
Bioinformatics (Oxford, England)|March 24, 2017
IntegratedMRF: random forest-based framework for integrating prediction from different data typesRaziur Rahman, John Otridge, Ranadip Pal
Scientific Reports|September 14, 2017
Heterogeneity Aware Random Forest for Drug Sensitivity PredictionRaziur Rahman, Kevin Matlock, Souparno Ghosh, et al.
Cancer Informatics|April 16, 2016
Design of Probabilistic Random Forests with Applications to Anticancer Drug Sensitivity PredictionRaziur Rahman, Saad Haider, Souparno Ghosh, et al.
Bioinformatics (Oxford, England)|December 22, 2017
Sequential feature selection and inference using multi-variate random forestsJoshua Mayer, Raziur Rahman, Souparno Ghosh, et al.
Plos One|December 15, 2015
A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity PredictionSaad Haider, Raziur Rahman, Souparno Ghosh, et al.
Bioinformatics (Oxford, England)|January 17, 2019
Sstack: an R package for stacking with applications to scenarios involving sequential addition of samples and featuresKevin Matlock, Raziur Rahman, Souparno Ghosh, et al.
Scientific Reports|February 9, 2019
Functional random forest with applications in dose-response predictionsRaziur Rahman, Saugato Rahman Dhruba, Souparno Ghosh, et al.
BMC Bioinformatics|March 29, 2018
Investigation of model stacking for drug sensitivity predictionKevin Matlock, Carlos De Niz, Raziur Rahman, et al.
BMC Bioinformatics|December 29, 2018
Application of transfer learning for cancer drug sensitivity predictionSaugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, et al.
Pageof 2

Showing results (1-10 of 16) with videos related to

Sort By:
Pageof 2
Methods in Molecular Biology (Clifton, N.J.)|November 1, 2018
Predictive Modeling of Anti-Cancer Drug Sensitivity from Genetic CharacterizationsRaziur Rahman, Ranadip Pal
Bioinformatics (Oxford, England)|March 24, 2017
IntegratedMRF: random forest-based framework for integrating prediction from different data typesRaziur Rahman, John Otridge, Ranadip Pal
Scientific Reports|September 14, 2017
Heterogeneity Aware Random Forest for Drug Sensitivity PredictionRaziur Rahman, Kevin Matlock, Souparno Ghosh, et al.
Cancer Informatics|April 16, 2016
Design of Probabilistic Random Forests with Applications to Anticancer Drug Sensitivity PredictionRaziur Rahman, Saad Haider, Souparno Ghosh, et al.
Bioinformatics (Oxford, England)|December 22, 2017
Sequential feature selection and inference using multi-variate random forestsJoshua Mayer, Raziur Rahman, Souparno Ghosh, et al.
Plos One|December 15, 2015
A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity PredictionSaad Haider, Raziur Rahman, Souparno Ghosh, et al.
Bioinformatics (Oxford, England)|January 17, 2019
Sstack: an R package for stacking with applications to scenarios involving sequential addition of samples and featuresKevin Matlock, Raziur Rahman, Souparno Ghosh, et al.
Scientific Reports|February 9, 2019
Functional random forest with applications in dose-response predictionsRaziur Rahman, Saugato Rahman Dhruba, Souparno Ghosh, et al.
BMC Bioinformatics|March 29, 2018
Investigation of model stacking for drug sensitivity predictionKevin Matlock, Carlos De Niz, Raziur Rahman, et al.
BMC Bioinformatics|December 29, 2018
Application of transfer learning for cancer drug sensitivity predictionSaugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, et al.
Pageof 2