| ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years R Nikam, A Kulandaisamy, K Harini, D Sharma, MM Gromiha Nucleic acids research 49 (D1), D420-D424, 2021 | 174 | 2021 |
| Seq2Feature: a comprehensive web-based feature extraction tool R Nikam, MM Gromiha Bioinformatics 35 (22), 4797-4799, 2019 | 28 | 2019 |
| Deep learning-based method for predicting and classifying the binding affinity of protein-protein complexes R Nikam, K Yugandhar, MM Gromiha Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics 1871 (6), 140948, 2023 | 10 | 2023 |
| DeepBSRPred: Deep learning-based binding site residue prediction for proteins R Nikam, K Yugandhar, MM Gromiha Amino Acids 55 (10), 1305-1316, 2023 | 9 | 2023 |
| Discrimination and prediction of protein-protein binding affinity using deep learning approach R Nikam, K Yugandhar, M Michael Gromiha Intelligent Computing Theories and Application: 14th International …, 2018 | 5 | 2018 |
| DeepPPAPredMut: deep ensemble method for predicting the binding affinity change in protein–protein complexes upon mutation R Nikam, S Jemimah, MM Gromiha Bioinformatics 40 (5), btae309, 2024 | 3 | 2024 |
| Illustrative Tutorials for ProThermDB: Thermodynamic Database for Proteins and Mutants A Kulandaisamy, R Nikam, K Harini, D Sharma, MM Gromiha Current Protocols 1 (11), e306, 2021 | 1 | 2021 |
| Influence of amino acid properties for characterizing amyloid peptides in human proteome R Prabakaran, R Nikam, S Kumar, MM Gromiha Intelligent Computing Theories and Application: 13th International …, 2017 | 1 | 2017 |
| Suffix graph-an efficient approach for network motif mining R Nikam, U Chauhan J. Data Min. Genomics Proteomics 7 (3), 2153-2156, 2016 | 1 | 2016 |
| Binding affinity changes upon mutation in protein–protein complexes R Nikam, F Ridha, S Jemimah, K Yugandhar, MM Gromiha PROTEIN MUTATIONS: Consequences on Structure, Functions, and Diseases, 105-122, 2025 | | 2025 |
