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Souparno Ghosh

Showing results (11-20 of 31) with videos related to

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Bioinformatics Advances|April 10, 2023
Federated learning framework integrating REFINED CNN and Deep Regression ForestsDaniel Nolte, Omid Bazgir, 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.
Scientific Reports|February 9, 2019
Functional random forest with applications in dose-response predictionsRaziur Rahman, Saugato Rahman Dhruba, Souparno Ghosh, et al.
Current Opinion in Neurobiology|April 13, 2018
Probing the brain with molecular fMRISouparno Ghosh, Peter Harvey, Jacob C Simon, et al.
Biometrics|February 22, 2012
The k-ZIG: flexible modeling for zero-inflated countsSouparno Ghosh, Alan E Gelfand, Kai Zhu, 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.
Nature Communications|June 13, 2024
Topological regression as an interpretable and efficient tool for quantitative structure-activity relationship modelingRuibo Zhang, Daniel Nolte, Cesar Sanchez-Villalobos, et al.
Pageof 4

Showing results (11-20 of 31) with videos related to

Sort By:
Pageof 4
Bioinformatics Advances|April 10, 2023
Federated learning framework integrating REFINED CNN and Deep Regression ForestsDaniel Nolte, Omid Bazgir, 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.
Scientific Reports|February 9, 2019
Functional random forest with applications in dose-response predictionsRaziur Rahman, Saugato Rahman Dhruba, Souparno Ghosh, et al.
Current Opinion in Neurobiology|April 13, 2018
Probing the brain with molecular fMRISouparno Ghosh, Peter Harvey, Jacob C Simon, et al.
Biometrics|February 22, 2012
The k-ZIG: flexible modeling for zero-inflated countsSouparno Ghosh, Alan E Gelfand, Kai Zhu, 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.
Nature Communications|June 13, 2024
Topological regression as an interpretable and efficient tool for quantitative structure-activity relationship modelingRuibo Zhang, Daniel Nolte, Cesar Sanchez-Villalobos, et al.
Pageof 4