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Naidu Subbarao
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2020 – today
- 2023
- [j12]Ram Nayan Verma, Rahul Deo, Rakesh Srivastava
, Naidu Subbarao, Gajendra Pratap Singh:
A new fuzzy support vector machine with pinball loss. Discov. Artif. Intell. 3(1) (2023) - 2022
- [j11]Manish Manish, Smriti Mishra, Ayush Anand
Computational molecular interaction between SARS-CoV-2 main protease and theaflavin digallate using free energy perturbation and molecular dynamics. Comput. Biol. Medicine 150: 106125 (2022) - [j10]Jyoti Verma, Abdul Hasan
In silico identification and in vitro antiviral validation of potential inhibitors against Chikungunya virus. J. Comput. Aided Mol. Des. 36(7): 521-536 (2022) - [j9]Yashbir Singh
Genome-wide expression reveals potential biomarkers in breast cancer bone metastasis. J. Integr. Bioinform. 19(3) (2022) - 2021
- [j8]Madhulata Kumari, Naidu Subbarao
Deep learning model for virtual screening of novel 3C-like protease enzyme inhibitors against SARS coronavirus diseases. Comput. Biol. Medicine 132: 104317 (2021) - [j7]Chetna Kumari
Exploring Molecular Descriptors and Fingerprints to Predict mTOR Kinase Inhibitors using Machine Learning Techniques. IEEE ACM Trans. Comput. Biol. Bioinform. 18(5): 1902-1913 (2021) - 2020
- [j6]Chetna Kumari, Muhammad Abulaish, Naidu Subbarao
Using SMOTE to Deal with Class-Imbalance Problem in Bioactivity Data to Predict mTOR Inhibitors. SN Comput. Sci. 1(3): 150 (2020)
2010 – 2019
- 2018
- [j5]Madhulata Kumari, Neeraj Tiwari, Subhash Chandra, Naidu Subbarao:
Comparative analysis of machine learning based QSAR models and molecular docking studies to screen potential anti-tubercular inhibitors against InhA of mycobacterium tuberculosis. Int. J. Comput. Biol. Drug Des. 11(3): 209-235 (2018) - [j4]Madhulata Kumari, Neeraj Tiwari, Naidu Subbarao
A genetic programming-based approach and machine learning approaches to the classification of multiclass anti-malarial datasets. Int. J. Comput. Biol. Drug Des. 11(4): 275-294 (2018) - 2017
- [j3]Madhulata Kumari, Neeraj Tiwari, Naidu Subbarao, Subhash Chandra:
Evaluation of predictive models based on random forest, decision tree and support vector machine classifiers and virtual screening of anti-mycobacterial compounds. Int. J. Comput. Biol. Drug Des. 10(3): 248-263 (2017)
2000 – 2009
- 2009
- [j2]Ragothaman Yennamalli
Identification of novel target sites and an inhibitor of the dengue virus E protein. J. Comput. Aided Mol. Des. 23(6): 333-341 (2009) - 2008
- [j1]Preyesh Stephen, Ramachandran Vijayan
Molecular modeling on pyruvate phosphate dikinase of Entamoeba histolytica and in silico virtual screening for novel inhibitors. J. Comput. Aided Mol. Des. 22(9): 647-660 (2008)
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