| CUPSAT: prediction of protein stability upon point mutations V Parthiban, MM Gromiha, D Schomburg Nucleic acids research 34 (suppl_2), W239-W242, 2006 | 434 | 2006 |
| ProTherm and ProNIT: thermodynamic databases for proteins and protein–nucleic acid interactions MDS Kumar, KA Bava, MM Gromiha, P Prabakaran, K Kitajima, H Uedaira, ... Nucleic acids research 34 (suppl_1), D204-D206, 2006 | 385 | 2006 |
| Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information S Ahmad, MM Gromiha, A Sarai Bioinformatics 20 (4), 477-486, 2004 | 375 | 2004 |
| ProTherm, version 4.0: thermodynamic database for proteins and mutants KA Bava, MM Gromiha, H Uedaira, K Kitajima, A Sarai Nucleic acids research 32 (suppl_1), D120-D121, 2004 | 346 | 2004 |
| Comparison between long-range interactions and contact order in determining the folding rate of two-state proteins: application of long-range order to folding rate prediction MM Gromiha, S Selvaraj Journal of molecular biology 310 (1), 27-32, 2001 | 325 | 2001 |
| Inter-residue interactions in protein folding and stability MM Gromiha, S Selvaraj Progress in biophysics and molecular biology 86 (2), 235-277, 2004 | 282 | 2004 |
| ASAView: Database and tool for solvent accessibility representation in proteins S Ahmad, M Gromiha, H Fawareh, A Sarai BMC bioinformatics 5 (1), 51, 2004 | 276 | 2004 |
| Prediction of RNA binding sites in a protein using SVM and PSSM profile M Kumar, MM Gromiha, GPS Raghava Proteins: Structure, Function, and Bioinformatics 71 (1), 189-194, 2008 | 261 | 2008 |
| Important amino acid properties for enhanced thermostability from mesophilic to thermophilic proteins MM Gromiha, M Oobatake, A Sarai Biophysical chemistry 82 (1), 51-67, 1999 | 229 | 1999 |
| Real value prediction of solvent accessibility from amino acid sequence S Ahmad, MM Gromiha, A Sarai Proteins: Structure, Function, and Bioinformatics 50 (4), 629-635, 2003 | 220 | 2003 |
| Identification of DNA-binding proteins using support vector machines and evolutionary profiles M Kumar, MM Gromiha, GPS Raghava BMC bioinformatics 8 (1), 463, 2007 | 200 | 2007 |
| Computational studies of drug repurposing and synergism of lopinavir, oseltamivir and ritonavir binding with SARS-CoV-2 Protease against COVID-19 N Muralidharan, R Sakthivel, D Velmurugan, MM Gromiha Journal of Biomolecular Structure and Dynamics, 1-6, 2020 | 194 | 2020 |
| Role of structural and sequence information in the prediction of protein stability changes: comparison between buried and partially buried mutations MM Gromiha, M Oobatake, H Kono, H Uedaira, A Sarai Protein Engineering 12 (7), 549-555, 1999 | 164 | 1999 |
| FOLD-RATE: prediction of protein folding rates from amino acid sequence MM Gromiha, AM Thangakani, S Selvaraj Nucleic acids research 34 (suppl_2), W70-W74, 2006 | 160 | 2006 |
| ProTherm: thermodynamic database for proteins and mutants MM Gromiha, J An, H Kono, M Oobatake, H Uedaira, A Sarai Nucleic acids research 27 (1), 286-288, 1999 | 148 | 1999 |
| Intermolecular and intramolecular readout mechanisms in protein–DNA recognition MM Gromiha, JG Siebers, S Selvaraj, H Kono, A Sarai Journal of molecular biology 337 (2), 285-294, 2004 | 143 | 2004 |
| iPTREE-STAB: interpretable decision tree based method for predicting protein stability changes upon mutations LT Huang, MM Gromiha, SY Ho Bioinformatics 23 (10), 1292-1293, 2007 | 142 | 2007 |
| Structural analysis of cation–π interactions in DNA binding proteins MM Gromiha, C Santhosh, S Ahmad International journal of biological macromolecules 34 (3), 203-211, 2004 | 128 | 2004 |
| NETASA: neural network based prediction of solvent accessibility S Ahmad, MM Gromiha Bioinformatics 18 (6), 819-824, 2002 | 128 | 2002 |
| A statistical model for predicting protein folding rates from amino acid sequence with structural class information MM Gromiha Journal of chemical information and modeling 45 (2), 494-501, 2005 | 124 | 2005 |
