Ranadip Pal - RankMe

79 papers B 3C 5Misc 2Journal 41Unranked 28

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Benchmarking community drug response prediction models: datasets, models, tools, and metrics for cross-dataset generalization analysis. Briefings Bioinform. Alexander Partin, Priyanka Vasanthakumari, Oleksandr Narykov, Andreas Wilke, Natasha Koussa, Sara E. Jones, Yitan Zhu, Jamie C. Overbeek, Rajeev Jain, Gayara Demini Fernando, Cesar Sanchez-Villalobos, Cristina Garcia-Cardona, Jamaludin Mohd-Yusof, Nicholas Chia, Justin M. Wozniak, Souparno Ghosh, Ranadip Pal, Thomas S. Brettin, M. Ryan Weil, Rick L. Stevens
2025	J	`jnl`	AdapTor: Adaptive Topological Regression for quantitative structure-activity relationship modeling. J. Cheminformatics Yixiang Mao, Souparno Ghosh, Ranadip Pal
2025	J	`jnl`	Benchmarking community drug response prediction models: datasets, models, tools, and metrics for cross-dataset generalization analysis. CoRR Alexander Partin, Priyanka Vasanthakumari, Oleksandr Narykov, Andreas Wilke, Natasha Koussa, Sara E. Jones, Yitan Zhu, Jamie C. Overbeek, Rajeev Jain, Gayara Demini Fernando, Cesar Sanchez-Villalobos, Cristina Garcia-Cardona, Jamaludin Mohd-Yusof, Nicholas Chia, Justin M. Wozniak, Souparno Ghosh, Ranadip Pal, Thomas S. Brettin, M. Ryan Weil, Rick L. Stevens
2024	J	`jnl`	Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data. CoRR Jamie C. Overbeek, Alexander Partin, Thomas S. Brettin, Nicholas Chia, Oleksandr Narykov, Priyanka Vasanthakumari, Andreas Wilke, Yitan Zhu, Austin Clyde, Sara Jones, Rohan Gnanaolivu, Yuanhang Liu, Jun Jiang, Chen Wang, Carter Knutson, Andrew D. McNaughton, Neeraj Kumar, Gayara Demini Fernando, Souparno Ghosh, Cesar Sanchez-Villalobos, Ruibo Zhang, Ranadip Pal, M. Ryan Weil, Rick L. Stevens
2024	—	`conf`	Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests. EMBC Daniel Nolte, Souparno Ghosh, Ranadip Pal
2024	J	`jnl`	Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests. CoRR Daniel Nolte, Souparno Ghosh, Ranadip Pal
2022	J	`jnl`	Predicting binding affinities of emerging variants of SARS-CoV-2 using spike protein sequencing data: observations, caveats and recommendations. Briefings Bioinform. Ruibo Zhang, Souparno Ghosh, Ranadip Pal
2021	J	`jnl`	Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction. Bioinform. Omid Bazgir, Souparno Ghosh, Ranadip Pal
2020	J	`jnl`	Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction. CoRR Omid Bazgir, Souparno Ghosh, Ranadip Pal
2019	J	`jnl`	Evaluating the consistency of large-scale pharmacogenomic studies. Briefings Bioinform. Raziur Rahman, Saugato Rahman Dhruba, Kevin Matlock, Carlos De Niz, Souparno Ghosh, Ranadip Pal
2019	J	`jnl`	REFINED (REpresentation of Features as Images with NEighborhood Dependencies): A novel feature representation for Convolutional Neural Networks. CoRR Omid Bazgir, Ruibo Zhang, Saugato Rahman Dhruba, Raziur Rahman, Souparno Ghosh, Ranadip Pal
2019	J	`jnl`	Recursive model for dose-time responses in pharmacological studies. BMC Bioinform. Saugato Rahman Dhruba, Aminur Rahman, Raziur Rahman, Souparno Ghosh, Ranadip Pal
2019	J	`jnl`	Selected research articles from the 2018 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci, Ranadip Pal
2019	J	`jnl`	Sstack: an R package for stacking with applications to scenarios involving sequential addition of samples and features. Bioinform. Kevin Matlock, Raziur Rahman, Souparno Ghosh, Ranadip Pal
2018	—	`conf`	Adaptive Multi-task Elastic Net based feature selection from Pharmacogenomics Databases. EMBC Raziur Rahman, Chamila Perera, Souparno Ghosh, Ranadip Pal
2018	—	`conf`	An investigation of proteomic data for application in precision medicine. BHI Kevin Matlock, Saugato Rahman Dhruba, Moazzam Nazir, Ranadip Pal
2018	J	`jnl`	Application of transfer learning for cancer drug sensitivity prediction. BMC Bioinform. Saugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, Souparno Ghosh, Ranadip Pal
2018	J	`jnl`	Deep Sequencing Data Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. Bijoy K. Ghosh, Aniruddha Datta, Ranadip Pal
2018	—	`conf`	Dimensionality Reduction based Transfer Learning applied to Pharmacogenomics Databases. EMBC Saugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, Souparno Ghosh, Ranadip Pal
2018	J	`jnl`	Investigation of model stacking for drug sensitivity prediction. BMC Bioinform. Kevin Matlock, Carlos De Niz, Raziur Rahman, Souparno Ghosh, Ranadip Pal
2018	—	`conf`	Recursive Model for Dose-time Responses in Pharmacological Studies. BCB Aminur Rahman, Saugato Rahman Dhruba, Souparno Ghosh, Ranadip Pal
2018	J	`jnl`	Selected research articles from the 2017 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci, Ranadip Pal
2018	J	`jnl`	Sequential feature selection and inference using multi-variate random forests. Bioinform. Joshua Mayer, Raziur Rahman, Souparno Ghosh, Ranadip Pal
2017	J	`jnl`	Combination therapy design for maximizing sensitivity and minimizing toxicity. BMC Bioinform. Kevin Matlock, Noah Berlow, Charles Keller, Ranadip Pal
2017	J	`jnl`	IntegratedMRF: random forest-based framework for integrating prediction from different data types. Bioinform. Raziur Rahman, John Otridge, Ranadip Pal
2017	—	`conf`	Investigation of Model Stacking for Drug Sensitivity Prediction. BCB Kevin Matlock, Carlos De Niz, Raziur Rahman, Souparno Ghosh, Ranadip Pal
2016	—	`conf`	A descriptive model of resting-state networks using Markov chains. EMBC Hua Xie, Ranadip Pal, Sunanda Mitra
2016	J	`jnl`	Algorithms for Drug Sensitivity Prediction. Algorithms Carlos De Niz, Raziur Rahman, Xiangyuan Zhao, Ranadip Pal
2016	—	`conf`	Analyzing drug sensitivity prediction based on dose response curve characteristics. BHI Raziur Rahman, Ranadip Pal
2016	B	`conf`	Automated segmentation of MS lesions in FLAIR, DIR and T2-w MR images via an information theoretic approach. Image Processing Jason E. Hill, Kevin Matlock, Ranadip Pal, Brian Nutter, Sunanda Mitra
2016	—	`conf`	Combination therapy design for maximizing sensitivity and minimizing toxicity. BCB Kevin Matlock, Noah Berlow, Charles Keller, Ranadip Pal
2014	J	`jnl`	An Integrated Approach to Anti-Cancer Drug Sensitivity Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. Noah Berlow, Saad Haider, Qian Wan, Mathew Geltzeiler, Lara E. Davis, Charles Keller, Ranadip Pal
2014	—	`conf`	Analysis of multivariate drug sensitivity dependence structure using copulas. GlobalSIP Saad Haider, Ranadip Pal
2014	—	`conf`	Gesture recognition for smart home applications using portable radar sensors. EMBC Qian Wan, Yiran Li, Changzhi Li, Ranadip Pal
2014	J	`jnl`	Inference of dynamic biological networks based on responses to drug perturbations. EURASIP J. Bioinform. Syst. Biol. Noah Berlow, Lara E. Davis, Charles Keller, Ranadip Pal
2014	—	`conf`	Multi-objective optimization of ensemble of regression trees using genetic algorithms. GlobalSIP Qian Wan, Ranadip Pal
2014	—	`conf`	Non-contact multi-radar smart probing of body orientation based on micro-Doppler signatures. EMBC Yiran Li, Ranadip Pal, Changzhi Li
2013	—	`conf`	A multivariate random forest based framework for drug sensitivity prediction. GENSiPS Qian Wan, Ranadip Pal
2013	J	`jnl`	A new approach for prediction of tumor sensitivity to targeted drugs based on functional data. BMC Bioinform. Noah Berlow, Lara E. Davis, Emma L. Cantor, Bernard Séguin, Charles Keller, Ranadip Pal
2013	—	`conf`	Inference of tumor inhibition pathways from drug perturbation data. GlobalSIP Saad Haider, Ranadip Pal
2013	J	`jnl`	Modeling and inference of genetic interactions. WIREs Data Mining Knowl. Discov. Ranadip Pal
2013	—	`conf`	Quantifying the inference power of a drug screen for predictive analysis. GENSiPS Noah Berlow, Saad Haider, Ranadip Pal, Charles Keller
2013	J	`jnl`	Stochastic Model Simulation Using Kronecker Product Analysis and Zassenhaus Formula Approximation. IEEE ACM Trans. Comput. Biol. Bioinform. Mehmet Umut Caglar, Ranadip Pal
2012	Misc	`conf`	A Kinase Inhibition Map Approach for Tumor Sensitivity Prediction and Combination Therapy Design for Targeted Drugs. Pacific Symposium on Biocomputing Ranadip Pal, Noah Berlow
2012	—	`conf`	Analyzing pathway design from drug perturbation experiments. SSP Noah Berlow, Ranadip Pal, Lara E. Davis, Charles Keller
2012	—	`conf`	Anticancer drug sensitivity analysis: An integrated approach applied to Erlotinib sensitivity prediction in the CCLE database. GENSiPS Ranadip Pal, Noah Berlow, Saad Haider
2012	—	`conf`	Combination therapy design for targeted therapeutics from a drug-protein interaction perspective. GENSiPS Saad Haider, Noah Berlow, Ranadip Pal, Lara E. Davis, Charles Keller
2012	—	`conf`	Complexity reduction of stochastic master equation simulation based on Kronecker product analysis. BCB Mehmet Umut Caglar, Ranadip Pal
2012	J	`jnl`	Robust Approaches for Genetic Regulatory Network Modeling and Intervention: A review of recent advances. IEEE Signal Process. Mag. Ranadip Pal, Sonal Bhattacharya, Mehmet Umut Caglar
2012	J	`jnl`	Transient Dynamics of Reduced-Order Models of Genetic Regulatory Networks. IEEE ACM Trans. Comput. Biol. Bioinform. Ranadip Pal, Sonal Bhattacharya
2011	—	`conf`	A novel approach for tumor sensitivity prediction and combination therapy design for targeted drugs. GENSiPS Noah Berlow, Ranadip Pal
2011	—	`conf`	A novel critical time analysis approach for genetic regulatory networks. GENSiPS Sonal Bhattacharya, Ranadip Pal
2011	—	`conf`	Generation of intervention strategy for a Genetic Regulatory Network represented by a family of Markov Chains. EMBC Noah Berlow, Ranadip Pal
2011	—	`conf`	Inference of a genetic regulatory network model from limited time series data. GENSiPS Saad Haider, Ranadip Pal
2010	J	`jnl`	Characterizing the effect of coarse-scale PBN modeling on dynamics and intervention performance of genetic regulatory networks represented by stochastic master equation models. IEEE Trans. Signal Process. Ranadip Pal, Sonal Bhattacharya
2010	Misc	`conf`	Classification of Alzheimer's disease and mild cognitive impairment by pattern recognition of EEG power and coherence. ICASSP Kwaku Akrofi, Ranadip Pal, Mary C. Baker, Brian Nutter, Randolph W. Schiffer
2010	B	`conf`	Classification of cognitive states using functional MRI data. Image Processing Ye Yang, Ranadip Pal, Michael O'Boyle
2010	J	`jnl`	Context-sensitive probabilistic Boolean networks: steady-state properties, reduction, and steady-state approximation. IEEE Trans. Signal Process. Ranadip Pal
2010	—	`conf`	Control of stochastic master equation models of genetic regulatory networks by approximating their average behavior. GENSiPS Ranadip Pal, Mehmet Umut Caglar
2010	C	`conf`	Effect of coarse-scale modeling on control outcome of genetic regulatory networks. ACC Ranadip Pal, Sonal Bhattacharya
2010	J	`jnl`	Stationary and structural control in gene regulatory networks: basic concepts. Int. J. Syst. Sci. Edward R. Dougherty, Ranadip Pal, Xiaoning Qian, Michael L. Bittner, Aniruddha Datta
2009	C	`conf`	Adaptive intervention in Probabilistic Boolean Networks. ACC Ritwik Layek, Aniruddha Datta, Ranadip Pal, Edward R. Dougherty
2009	J	`jnl`	Adaptive intervention in probabilistic boolean networks. Bioinform. Ritwik Layek, Aniruddha Datta, Ranadip Pal, Edward R. Dougherty
2009	—	`conf`	Analyzing steady state probability distributions of Context-sensitive Probabilistic Boolean Networks. GENSiPS Ranadip Pal
2009	J	`jnl`	Bayesian robustness in the control of gene regulatory networks. IEEE Trans. Signal Process. Ranadip Pal, Aniruddha Datta, Edward R. Dougherty
2009	—	`conf`	Quantification of data extraction noise in probabilistic Boolean Network modeling. GENSiPS Ranadip Pal, Aniruddha Datta, Edward R. Dougherty
2009	B	`conf`	Steady-state preserving reduction for genetic regulatory network models. CBMS Ranadip Pal, Sonal Bhattacharya
2008	—	`conf`	Generating structure-function correlations by ICA- based mapping of activation patterns on co-registered fMRI and FA-DTI data. ACSCC Sunanda Mitra, M. O'Boyle, Enrique Corona, Bian Li, Farhat Afrin, Brian Nutter, M. Baker, Ranadip Pal, Bijoy K. Ghosh, Tanja Karp
2008	J	`jnl`	Robust Intervention in Probabilistic Boolean Networks. IEEE Trans. Signal Process. Ranadip Pal, Aniruddha Datta, Edward R. Dougherty
2007	J	`jnl`	Control approaches for probabilistic gene regulatory networks - What approaches have been developed for addreassinig the issue of intervention? IEEE Signal Process. Mag. Anirulddlha Datta, Ranadip Pal, Ashish Choudhary, Edward R. Dougherty
2007	J	`jnl`	Dynamics Preserving Size Reduction Mappings for Probabilistic Boolean Networks. IEEE Trans. Signal Process. Ivan Ivanov, Ranadip Pal, Edward R. Dougherty
2007	C	`conf`	Robust Intervention in Probabilistic Boolean Networks. ACC Ranadip Pal, Aniruddha Datta, Edward R. Dougherty
2006	C	`conf`	Optimal infinite horizon control for probabilistic Boolean networks. ACC Ranadip Pal, Aniruddha Datta, Edward R. Dougherty
2006	J	`jnl`	Optimal infinite-horizon control for probabilistic Boolean networks. IEEE Trans. Signal Process. Ranadip Pal, Aniruddha Datta, Edward R. Dougherty
2005	J	`jnl`	Boolean relationships among genes responsive to ionizing radiation in the NCI 60 ACDS. Bioinform. Ranadip Pal, Aniruddha Datta, Albert J. Fornace Jr., Michael L. Bittner, Edward R. Dougherty
2005	C	`conf`	External control in a special class of probabilistic Boolean networks. ACC Ranadip Pal, Aniruddha Datta, Michael L. Bittner, Edward R. Dougherty
2005	J	`jnl`	Generating Boolean networks with a prescribed attractor structure. Bioinform. Ranadip Pal, Ivan Ivanov, Aniruddha Datta, Michael L. Bittner, Edward R. Dougherty
2005	J	`jnl`	Intervention in context-sensitive probabilistic Boolean networks. Bioinform. Ranadip Pal, Aniruddha Datta, Michael L. Bittner, Edward R. Dougherty
2004	J	`jnl`	A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks. Bioinform. Xiaobo Zhou, Xiaodong Wang, Ranadip Pal, Ivan Ivanov, Michael L. Bittner, Edward R. Dougherty