| Representation of features as images with neighborhood dependencies for compatibility with convolutional neural networks O Bazgir, R Zhang, SR Dhruba, R Rahman, S Ghosh, R Pal Nature communications 11 (1), 4391, 2020 | 99 | 2020 |
| IntegratedMRF: random forest-based framework for integrating prediction from different data types R Rahman, J Otridge, R Pal Bioinformatics 33 (9), 1407-1410, 2017 | 70 | 2017 |
| Heterogeneity aware random forest for drug sensitivity prediction R Rahman, K Matlock, S Ghosh, R Pal Scientific reports 7 (1), 11347, 2017 | 65 | 2017 |
| Functional random forest with applications in dose-response predictions R Rahman, SR Dhruba, S Ghosh, R Pal Scientific reports 9 (1), 1628, 2019 | 59 | 2019 |
| Algorithms for drug sensitivity prediction C De Niz, R Rahman, X Zhao, R Pal Algorithms 9 (4), 77, 2016 | 54 | 2016 |
| Investigation of model stacking for drug sensitivity prediction K Matlock, C De Niz, R Rahman, S Ghosh, R Pal BMC bioinformatics 19, 21-33, 2018 | 47 | 2018 |
| A copula based approach for design of multivariate random forests for drug densitivity prediction S Haider, R Rahman, S Ghosh, R Pal PLoS One 10 (12), e0144490, 2015 | 44 | 2015 |
| Application of transfer learning for cancer drug sensitivity prediction SR Dhruba, R Rahman, K Matlock, S Ghosh, R Pal BMC bioinformatics 19, 51-63, 2018 | 33 | 2018 |
| Design of probabilistic random forests with applications to anticancer drug sensitivity prediction R Rahman, S Haider, S Ghosh, R Pal Cancer informatics 14, CIN. S30794, 2015 | 21 | 2015 |
| Sequential feature selection and inference using multi-variate random forests J Mayer, R Rahman, S Ghosh, R Pal Bioinformatics 34 (8), 1336-1344, 2018 | 17 | 2018 |
| Evaluating the consistency of large-scale pharmacogenomic studies R Rahman, SR Dhruba, K Matlock, C De-Niz, S Ghosh, R Pal Briefings in Bioinformatics 20 (5), 1734-1753, 2019 | 13 | 2019 |
| Analyzing drug sensitivity prediction based on dose response curve characteristics R Rahman, R Pal 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics …, 2016 | 12 | 2016 |
| Predicting power electronics device reliability under extreme conditions with machine learning algorithms C Olivares, R Rahman, C Stankus, J Hampton, A Zedwick, M Ahmed arXiv preprint arXiv:2107.10292, 2021 | 8 | 2021 |
| MultivariateRandomForest: models multivariate cases using random forests R Rahman R package version 1 (5), 2017 | 8 | 2017 |
| Dimensionality Reduction based Transfer Learning applied to Pharmacogenomics Databases SR Dhruba, R Rahman, K Matlock, S Ghosh, R Pal 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 7 | 2018 |
| Adaptive Multi-task Elastic Net based feature selection from Pharmacogenomics Databases R Rahman, C Perera, S Ghosh, R Pal 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 7 | 2018 |
| Recursive model for dose-time responses in pharmacological studies SR Dhruba, A Rahman, R Rahman, S Ghosh, R Pal BMC bioinformatics 20, 1-12, 2019 | 6 | 2019 |
| Predictive modeling of anti-cancer drug sensitivity from genetic characterizations R Rahman, R Pal Cancer Bioinformatics, 227-241, 2019 | 4 | 2019 |
| A mathematical framework for analyzing drug combination toxicity for personalized medicine applications R Rahman, R Pal 2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI …, 2016 | 4 | 2016 |
| Sstack: an R package for stacking with applications to scenarios involving sequential addition of samples and features K Matlock, R Rahman, S Ghosh, R Pal Bioinformatics 35 (17), 3143-3145, 2019 | 1 | 2019 |
Ranadip PalTexas Tech UniversityVerified email at ttu.edu
