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Sanjay S. Bankapur
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2020 – today
- 2024
- [c5]Essmily Simon, Sanjay S. Bankapur:
Prediction of Drug-Target Interactions Using BERT for Protein Sequences and Drug Compound. COMSNETS 2024: 436-438 - 2022
- [j5]Sanjay S. Bankapur, Nagamma Patil:
An Effective Multi-Label Protein Sub-Chloroplast Localization Prediction by Skipped-Grams of Evolutionary Profiles Using Deep Neural Network. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1449-1458 (2022) - 2021
- [j4]Aditya Jayasimha, Rahul Mudambi, P. Pavan, B. M. Lokaksha, Sanjay S. Bankapur, Nagamma Patil:
An effective feature extraction with deep neural network architecture for protein-secondary-structure prediction. Netw. Model. Anal. Health Informatics Bioinform. 10(1): 58 (2021) - [j3]Sanjay S. Bankapur, Nagamma Patil:
Enhanced Protein Structural Class Prediction Using Effective Feature Modeling and Ensemble of Classifiers. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2409-2419 (2021) - 2020
- [j2]Prince Kumar, Sanjay S. Bankapur, Nagamma Patil:
An enhanced protein secondary structure prediction using deep learning framework on hybrid profile based features. Appl. Soft Comput. 86 (2020) - [j1]Sanjay S. Bankapur, Nagamma Patil:
ProgSIO-MSA: Progressive-based single iterative optimization framework for multiple sequence alignment using an effective scoring system. J. Bioinform. Comput. Biol. 18(2): 2050005:1-2050005:28 (2020) - [c4]K. Karthik, Gokul S. Krishnan, Shashank Shetty, Sanjay S. Bankapur, Ranjit P. Kolkar, T. S. Ashwin, Manjunath K. Vanahalli:
Analysis and Prediction of Fantasy Cricket Contest Winners Using Machine Learning Techniques. FICTA (1) 2020: 443-453
2010 – 2019
- 2018
- [c3]Sanjay S. Bankapur, Nagamma Patil:
Protein Secondary Structural Class Prediction Using Effective Feature Modeling and Machine Learning Techniques. BIBE 2018: 18-21 - 2017
- [c2]Sanjay S. Bankapur, Nagamma Patil:
Position-Residue Specific Dynamic Gap Penalty Scoring Strategy for Multiple Sequence Alignment. CSBio 2017: 42-45 - [c1]Sanjay S. Bankapur, Nagamma Patil:
Efficient and Effective Multiple Protein Sequence Alignment Model Using Dynamic Progressive Approach with Novel Look Back Ahead Scoring System. PReMI 2017: 397-404
Coauthor Index
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