Naidu Subbarao

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 10

Top Topics

Fuzzy Support Vector Machine

Molecular Dynamics

Top Venues

Int. J. Comput. Biol. Drug Des.

Comput. Biol. Medicine

IEEE ACM Trans. Comput. Biol. Bioinform.

J. Comput. Aided Mol. Des.

Publications

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)
Jyoti Verma, Abdul Hasan, Sujatha Sunil, Naidu Subbarao
In silico identification and in vitro antiviral validation of potential inhibitors against Chikungunya virus. J. Comput. Aided Mol. Des. 36 (7) (2022)
Yashbir Singh, Naidu Subbarao, Abhinav Jaimini, Quincy A. Hathaway, Amina Kunovac, Bradley James Erickson, Vishnu Swarup, Himanshu Narayan Singh
Genome-wide expression reveals potential biomarkers in breast cancer bone metastasis. J. Integr. Bioinform. 19 (3) (2022)
Manish Manish, Smriti Mishra, Ayush Anand, Naidu Subbarao
Computational molecular interaction between SARS-CoV-2 main protease and theaflavin digallate using free energy perturbation and molecular dynamics. Comput. Biol. Medicine 150 (2022)
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 (2021)
Chetna Kumari, Muhammad Abulaish, Naidu Subbarao
Exploring Molecular Descriptors and Fingerprints to Predict mTOR Kinase Inhibitors using Machine Learning Techniques. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (5) (2021)
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) (2020)
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) (2018)
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) (2018)
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) (2017)
Ragothaman Yennamalli, Naidu Subbarao, Thorsten Kampmann, Ross P. McGeary, Paul R. Young, Bostjan Kobe
Identification of novel target sites and an inhibitor of the dengue virus E protein. J. Comput. Aided Mol. Des. 23 (6) (2009)
Preyesh Stephen, Ramachandran Vijayan, Audesh Bhat, Naidu Subbarao, R. N. K. Bamezai
and in silico virtual screening for novel inhibitors. J. Comput. Aided Mol. Des. 22 (9) (2008)