M. Michael Gromiha mostly deals with Protein structure, Biochemistry, Peptide sequence, Computational biology and Amino acid. His work carried out in the field of Protein structure brings together such families of science as Crystallography, Interaction energy, Transmembrane protein, Protein folding and Protein engineering. M. Michael Gromiha has included themes like Folding, Globular protein and Protein structure prediction in his Protein folding study.
His study focuses on the intersection of Biochemistry and fields such as Biophysics with connections in the field of Hydrogen bond and Protein tertiary structure. His Peptide sequence study combines topics in areas such as Data mining, Artificial neural network, Machine learning, Artificial intelligence and Sequence analysis. His Computational biology research incorporates themes from Genetics, Bioinformatics, Mutant, Support vector machine and Sequence.
M. Michael Gromiha spends much of his time researching Computational biology, Amino acid, Biochemistry, Protein structure and Protein folding. His work in Computational biology tackles topics such as Mutation which are related to areas like Point mutation. His research integrates issues of Protein secondary structure, Biophysics, Mutant, Peptide sequence and Membrane protein in his study of Amino acid.
His Protein secondary structure research focuses on subjects like Stereochemistry, which are linked to Accessible surface area. His Protein structure study integrates concerns from other disciplines, such as Crystallography and Protein engineering. His Folding research extends to Protein folding, which is thematically connected.
Computational biology, Protein aggregation, Drug discovery, Biochemistry and Biophysics are his primary areas of study. The concepts of his Computational biology study are interwoven with issues in Mutation, Gene, Transcriptome, Mutation and Drug. His Biochemistry study often links to related topics such as Molecular dynamics.
His Biophysics study incorporates themes from Glycoprotein and Aromatic amino acids, Enzyme. M. Michael Gromiha interconnects Amino acid, Membrane protein, DNA sequencing and Transmembrane protein in the investigation of issues within Neutral mutation. The study incorporates disciplines such as Protein secondary structure, Database, Protein domain, Peptide sequence and Protein structure in addition to Mutant.
The scientist’s investigation covers issues in Computational biology, Neutral mutation, Drug repositioning, Gene and Severe acute respiratory syndrome coronavirus 2. He combines subjects such as Protein protein, Binding free energy and Class information with his study of Computational biology. His Neutral mutation research includes themes of Mutation, Membrane protein and Transmembrane protein.
His research in Membrane protein intersects with topics in Globular protein, Cytoplasm, Function and Metabolism. To a larger extent, M. Michael Gromiha studies Biochemistry with the aim of understanding Transmembrane protein. His Gene research is multidisciplinary, incorporating elements of Protein secondary structure and Database.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
CUPSAT: prediction of protein stability upon point mutations
Vijaya Parthiban;M. Michael Gromiha;Dietmar Schomburg.
Nucleic Acids Research (2006)
ProTherm and ProNIT: thermodynamic databases for proteins and protein–nucleic acid interactions
M. D. Shaji Kumar;K. Abdulla Bava;M. Michael Gromiha;Ponraj Prabakaran.
Nucleic Acids Research (2006)
Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information
Shandar Ahmad;M. Michael Gromiha;Akinori Sarai.
ProTherm, version 4.0: thermodynamic database for proteins and mutants
K. Abdulla Bava;M. Michael Gromiha;Hatsuho Uedaira;Koji Kitajima.
Nucleic Acids Research (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.
M.Michael Gromiha;S Selvaraj.
Journal of Molecular Biology (2001)
Inter-residue interactions in protein folding and stability.
M.Michael Gromiha;S. Selvaraj.
Progress in Biophysics & Molecular Biology (2004)
ASAView : Database and tool for solvent accessibility representation in proteins
Shandar Ahmad;M. Michael Gromiha;Hamed Fawareh;Akinori Sarai.
BMC Bioinformatics (2004)
Prediction of RNA binding sites in a protein using SVM and PSSM profile
Manish Kumar;M. Michael Gromiha;G. P. S. Raghava.
Computational studies of drug repurposing and synergism of lopinavir, oseltamivir and ritonavir binding with SARS-CoV-2 protease against COVID-19.
Nisha Muralidharan;R. Sakthivel;D. Velmurugan;M. Michael Gromiha.
Journal of Biomolecular Structure & Dynamics (2021)
Important amino acid properties for enhanced thermostability from mesophilic to thermophilic proteins.
M.Michael Gromiha;Motohisa Oobatake;Akinori Sarai.
Biophysical Chemistry (1999)
Profile was last updated on December 6th, 2021.
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