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ORCIDRanadip Pal
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2020 – today
- 2024
[c38]Daniel Nolte, Souparno Ghosh, Ranadip Pal:
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests. EMBC 2024: 1-6- [i4]Daniel Nolte, Souparno Ghosh, Ranadip Pal:
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests. CoRR abs/2402.14080 (2024) - [i3]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:
Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data. CoRR abs/2409.12215 (2024) - 2022
- [j34]Ruibo Zhang, Souparno Ghosh, Ranadip Pal:
Predicting binding affinities of emerging variants of SARS-CoV-2 using spike protein sequencing data: observations, caveats and recommendations. Briefings Bioinform. 23(3) (2022) - 2021
- [j33]Omid Bazgir, Souparno Ghosh, Ranadip Pal
:
Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction. Bioinform. 37(Supplement): 42-50 (2021) - 2020
- [i2]Omid Bazgir, Souparno Ghosh, Ranadip Pal:
Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction. CoRR abs/2009.04076 (2020)
2010 – 2019
- 2019
- [j32]Raziur Rahman, Saugato Rahman Dhruba, Kevin Matlock, Carlos De Niz, Souparno Ghosh, Ranadip Pal:
Evaluating the consistency of large-scale pharmacogenomic studies. Briefings Bioinform. 20(5): 1734-1753 (2019) - [j31]Kevin Matlock, Raziur Rahman, Souparno Ghosh, Ranadip Pal:
Sstack: an R package for stacking with applications to scenarios involving sequential addition of samples and features. Bioinform. 35(17): 3143-3145 (2019) - [j30]Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci, Ranadip Pal:
Selected research articles from the 2018 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. 20-S(12): 316:1-316:3 (2019) - [j29]Saugato Rahman Dhruba, Aminur Rahman, Raziur Rahman, Souparno Ghosh, Ranadip Pal:
Recursive model for dose-time responses in pharmacological studies. BMC Bioinform. 20-S(12): 317:1-317:12 (2019) - [i1]Omid Bazgir, Ruibo Zhang, Saugato Rahman Dhruba, Raziur Rahman, Souparno Ghosh, Ranadip Pal:
REFINED (REpresentation of Features as Images with NEighborhood Dependencies): A novel feature representation for Convolutional Neural Networks. CoRR abs/1912.05687 (2019) - 2018
- [j28]Joshua Mayer, Raziur Rahman, Souparno Ghosh, Ranadip Pal:
Sequential feature selection and inference using multi-variate random forests. Bioinform. 34(8): 1336-1344 (2018) - [j27]Kevin Matlock, Carlos De Niz, Raziur Rahman, Souparno Ghosh, Ranadip Pal:
Investigation of model stacking for drug sensitivity prediction. BMC Bioinform. 19-S(3): 21-33 (2018) - [j26]Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci, Ranadip Pal:
Selected research articles from the 2017 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. 19-S(3): 69:1-69:4 (2018) - [j25]Saugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, Souparno Ghosh, Ranadip Pal:
Application of transfer learning for cancer drug sensitivity prediction. BMC Bioinform. 19-S(17): 51-63 (2018) - [j24]Bijoy K. Ghosh, Aniruddha Datta, Ranadip Pal:
Deep Sequencing Data Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 15(2): 482-483 (2018) - [c37]Aminur Rahman, Saugato Rahman Dhruba, Souparno Ghosh, Ranadip Pal:
Recursive Model for Dose-time Responses in Pharmacological Studies. BCB 2018: 583 - [c36]Kevin Matlock, Saugato Rahman Dhruba, Moazzam Nazir, Ranadip Pal:
An investigation of proteomic data for application in precision medicine. BHI 2018: 377-380 - [c35]Raziur Rahman, Chamila Perera, Souparno Ghosh, Ranadip Pal:
Adaptive Multi-task Elastic Net based feature selection from Pharmacogenomics Databases. EMBC 2018: 279-282 - [c34]Saugato Rahman Dhruba, Raziur Rahman, Kevin Matlock, Souparno Ghosh, Ranadip Pal:
Dimensionality Reduction based Transfer Learning applied to Pharmacogenomics Databases. EMBC 2018: 1246-1249 - 2017
- [j23]Raziur Rahman, John Otridge, Ranadip Pal:
IntegratedMRF: random forest-based framework for integrating prediction from different data types. Bioinform. 33(9): 1407-1410 (2017) - [j22]Kevin Matlock, Noah Berlow, Charles Keller, Ranadip Pal:
Combination therapy design for maximizing sensitivity and minimizing toxicity. BMC Bioinform. 18(S-4): 17-29 (2017) - [c33]Kevin Matlock, Carlos De Niz, Raziur Rahman, Souparno Ghosh, Ranadip Pal:
Investigation of Model Stacking for Drug Sensitivity Prediction. BCB 2017: 772 - 2016
- [j21]Carlos De Niz, Raziur Rahman, Xiangyuan Zhao, Ranadip Pal:
Algorithms for Drug Sensitivity Prediction. Algorithms 9(4): 77 (2016) - [c32]Kevin Matlock, Noah Berlow, Charles Keller, Ranadip Pal:
Combination therapy design for maximizing sensitivity and minimizing toxicity. BCB 2016: 530-531 - [c31]Raziur Rahman, Ranadip Pal:
Analyzing drug sensitivity prediction based on dose response curve characteristics. BHI 2016: 140-143 - [c30]Hua Xie, Ranadip Pal, Sunanda Mitra:
A descriptive model of resting-state networks using Markov chains. EMBC 2016: 3594-3597 - [c29]Jason E. Hill, Kevin Matlock, Ranadip Pal, Brian Nutter, Sunanda Mitra:
Automated segmentation of MS lesions in FLAIR, DIR and T2-w MR images via an information theoretic approach. Image Processing 2016: 97842J - 2014
- [j20]Noah Berlow, Lara E. Davis, Charles Keller, Ranadip Pal:
Inference of dynamic biological networks based on responses to drug perturbations. EURASIP J. Bioinform. Syst. Biol. 2014: 14 (2014) - [j19]Noah Berlow, Saad Haider, Qian Wan, Mathew Geltzeiler, Lara E. Davis, Charles Keller, Ranadip Pal:
An Integrated Approach to Anti-Cancer Drug Sensitivity Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 11(6): 995-1008 (2014) - [c28]Yiran Li, Ranadip Pal, Changzhi Li:
Non-contact multi-radar smart probing of body orientation based on micro-Doppler signatures. EMBC 2014: 598-601 - [c27]Qian Wan, Yiran Li, Changzhi Li, Ranadip Pal:
Gesture recognition for smart home applications using portable radar sensors. EMBC 2014: 6414-6417 - [c26]Saad Haider, Ranadip Pal:
Analysis of multivariate drug sensitivity dependence structure using copulas. GlobalSIP 2014: 1352-1355 - [c25]Qian Wan, Ranadip Pal:
Multi-objective optimization of ensemble of regression trees using genetic algorithms. GlobalSIP 2014: 1356-1359 - 2013
- [j18]Noah Berlow, Lara E. Davis, Emma L. Cantor, Bernard Séguin, Charles Keller, Ranadip Pal:
A new approach for prediction of tumor sensitivity to targeted drugs based on functional data. BMC Bioinform. 14: 239 (2013) - [j17]Mehmet Umut Caglar, Ranadip Pal:
Stochastic Model Simulation Using Kronecker Product Analysis and Zassenhaus Formula Approximation. IEEE ACM Trans. Comput. Biol. Bioinform. 10(5): 1125-1136 (2013) - [j16]Ranadip Pal:
Modeling and inference of genetic interactions. WIREs Data Mining Knowl. Discov. 3(6): 453-466 (2013) - [c24]Noah Berlow, Saad Haider, Ranadip Pal, Charles Keller:
Quantifying the inference power of a drug screen for predictive analysis. GENSiPS 2013: 49-52 - [c23]Qian Wan, Ranadip Pal:
A multivariate random forest based framework for drug sensitivity prediction. GENSiPS 2013: 53 - [c22]Saad Haider, Ranadip Pal:
Inference of tumor inhibition pathways from drug perturbation data. GlobalSIP 2013: 95-98 - 2012
- [j15]Ranadip Pal, Sonal Bhattacharya, Mehmet Umut Caglar:
Robust Approaches for Genetic Regulatory Network Modeling and Intervention: A review of recent advances. IEEE Signal Process. Mag. 29(1): 66-76 (2012) - [j14]Ranadip Pal, Sonal Bhattacharya:
Transient Dynamics of Reduced-Order Models of Genetic Regulatory Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 9(4): 1230-1244 (2012) - [c21]Mehmet Umut Caglar, Ranadip Pal:
Complexity reduction of stochastic master equation simulation based on Kronecker product analysis. BCB 2012: 186-193 - [c20]Ranadip Pal, Noah Berlow, Saad Haider:
Anticancer drug sensitivity analysis: An integrated approach applied to Erlotinib sensitivity prediction in the CCLE database. GENSiPS 2012: 9-12 - [c19]Saad Haider, Noah Berlow, Ranadip Pal, Lara E. Davis, Charles Keller:
Combination therapy design for targeted therapeutics from a drug-protein interaction perspective. GENSiPS 2012: 58-61 - [c18]Ranadip Pal, Noah Berlow:
A Kinase Inhibition Map Approach for Tumor Sensitivity Prediction and Combination Therapy Design for Targeted Drugs. Pacific Symposium on Biocomputing 2012: 351-362 - [c17]Noah Berlow, Ranadip Pal, Lara E. Davis, Charles Keller:
Analyzing pathway design from drug perturbation experiments. SSP 2012: 552-555 - 2011
- [c16]Noah Berlow, Ranadip Pal:
Generation of intervention strategy for a Genetic Regulatory Network represented by a family of Markov Chains. EMBC 2011: 7610-7613 - [c15]Sonal Bhattacharya, Ranadip Pal:
A novel critical time analysis approach for genetic regulatory networks. GENSiPS 2011: 29-32 - [c14]Noah Berlow, Ranadip Pal:
A novel approach for tumor sensitivity prediction and combination therapy design for targeted drugs. GENSiPS 2011: 36-37 - [c13]Saad Haider, Ranadip Pal:
Inference of a genetic regulatory network model from limited time series data. GENSiPS 2011: 162-165 - 2010
- [j13]Edward R. Dougherty, Ranadip Pal, Xiaoning Qian, Michael L. Bittner, Aniruddha Datta:
Stationary and structural control in gene regulatory networks: basic concepts. Int. J. Syst. Sci. 41(1): 5-16 (2010) - [j12]Ranadip Pal:
Context-sensitive probabilistic Boolean networks: steady-state properties, reduction, and steady-state approximation. IEEE Trans. Signal Process. 58(2): 879-890 (2010) - [j11]Ranadip Pal, Sonal Bhattacharya:
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. 58(6): 3341-3351 (2010) - [c12]Ranadip Pal, Sonal Bhattacharya:
Effect of coarse-scale modeling on control outcome of genetic regulatory networks. ACC 2010: 5942-5947 - [c11]Ranadip Pal, Mehmet Umut Caglar:
Control of stochastic master equation models of genetic regulatory networks by approximating their average behavior. GENSiPS 2010: 1-4 - [c10]Kwaku Akrofi, Ranadip Pal, Mary C. Baker, Brian Nutter, Randolph W. Schiffer:
Classification of Alzheimer's disease and mild cognitive impairment by pattern recognition of EEG power and coherence. ICASSP 2010: 606-609 - [c9]Ye Yang, Ranadip Pal, Michael O'Boyle:
Classification of cognitive states using functional MRI data. Image Processing 2010: 762322
2000 – 2009
- 2009
- [j10]Ritwik Layek, Aniruddha Datta, Ranadip Pal, Edward R. Dougherty:
Adaptive intervention in probabilistic boolean networks. Bioinform. 25(16): 2042-2048 (2009) - [j9]Ranadip Pal, Aniruddha Datta, Edward R. Dougherty:
Bayesian robustness in the control of gene regulatory networks. IEEE Trans. Signal Process. 57(9): 3667-3678 (2009) - [c8]Ritwik Layek, Aniruddha Datta, Ranadip Pal, Edward R. Dougherty:
Adaptive intervention in Probabilistic Boolean Networks. ACC 2009: 5647-5652 - [c7]Ranadip Pal, Sonal Bhattacharya:
Steady-state preserving reduction for genetic regulatory network models. CBMS 2009: 1-6 - [c6]Ranadip Pal:
Analyzing steady state probability distributions of Context-sensitive Probabilistic Boolean Networks. GENSiPS 2009: 1-4 - [c5]Ranadip Pal, Aniruddha Datta, Edward R. Dougherty:
Quantification of data extraction noise in probabilistic Boolean Network modeling. GENSiPS 2009: 1-4 - 2008
- [j8]Ranadip Pal, Aniruddha Datta, Edward R. Dougherty:
Robust Intervention in Probabilistic Boolean Networks. IEEE Trans. Signal Process. 56(3): 1280-1294 (2008) - [c4]Sunanda Mitra, M. O'Boyle, Enrique Corona, Bian Li, F. Afrin, Brian Nutter, M. Baker, Ranadip Pal, Bijoy K. Ghosh, Tanja Karp:
Generating structure-function correlations by ICA- based mapping of activation patterns on co-registered fMRI and FA-DTI data. ACSCC 2008: 1393-1396 - 2007
- [j7]Anirulddlha Datta, Ranadip Pal, Ashish Choudhary, Edward R. Dougherty:
Control approaches for probabilistic gene regulatory networks - What approaches have been developed for addreassinig the issue of intervention? IEEE Signal Process. Mag. 24(1): 54-63 (2007) - [j6]Ivan Ivanov, Ranadip Pal, Edward R. Dougherty:
Dynamics Preserving Size Reduction Mappings for Probabilistic Boolean Networks. IEEE Trans. Signal Process. 55(5-2): 2310-2322 (2007) - [c3]Ranadip Pal, Aniruddha Datta, Edward R. Dougherty:
Robust Intervention in Probabilistic Boolean Networks. ACC 2007: 2405-2410 - 2006
- [j5]Ranadip Pal, Aniruddha Datta, Edward R. Dougherty:
Optimal infinite-horizon control for probabilistic Boolean networks. IEEE Trans. Signal Process. 54(6-2): 2375-2387 (2006) - [c2]Ranadip Pal, Aniruddha Datta, Edward R. Dougherty:
Optimal infinite horizon control for probabilistic Boolean networks. ACC 2006 - 2005
- [j4]Ranadip Pal, Aniruddha Datta, Michael L. Bittner, Edward R. Dougherty:
Intervention in context-sensitive probabilistic Boolean networks. Bioinform. 21(7): 1211-1218 (2005) - [j3]Ranadip Pal, Aniruddha Datta, Albert J. Fornace Jr., Michael L. Bittner, Edward R. Dougherty:
Boolean relationships among genes responsive to ionizing radiation in the NCI 60 ACDS. Bioinform. 21(8): 1542-1549 (2005) - [j2]Ranadip Pal, Ivan Ivanov, Aniruddha Datta, Michael L. Bittner, Edward R. Dougherty:
Generating Boolean networks with a prescribed attractor structure. Bioinform. 21(21): 4021-4025 (2005) - [c1]Ranadip Pal, Aniruddha Datta, Michael L. Bittner, Edward R. Dougherty:
External control in a special class of probabilistic Boolean networks. ACC 2005: 411-416vol.1 - 2004
- [j1]Xiaobo Zhou, Xiaodong Wang, Ranadip Pal, Ivan Ivanov, Michael L. Bittner, Edward R. Dougherty:
A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks. Bioinform. 20(17): 2918-2927 (2004)
Coauthor Index
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