H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Biology and Biochemistry H-index 58 Citations 10,266 267 World Ranking 6205 National Ranking 21

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Enzyme
  • DNA

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.

His most cited work include:

  • CUPSAT: prediction of protein stability upon point mutations (385 citations)
  • ProTherm and ProNIT: thermodynamic databases for proteins and protein–nucleic acid interactions (317 citations)
  • Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information (291 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Computational biology (34.95%)
  • Amino acid (25.97%)
  • Biochemistry (24.76%)

What were the highlights of his more recent work (between 2018-2021)?

  • Computational biology (34.95%)
  • Protein aggregation (6.80%)
  • Drug discovery (5.83%)

In recent papers he was focusing on the following fields of study:

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.

Between 2018 and 2021, his most popular works were:

  • Computational studies of drug repurposing and synergism of lopinavir, oseltamivir and ritonavir binding with SARS-CoV-2 protease against COVID-19. (196 citations)
  • Neurodegenerative Diseases - Is Metabolic Deficiency the Root Cause? (21 citations)
  • Multi-omics-based identification of SARS-CoV-2 infection biology and candidate drugs against COVID-19. (17 citations)

In his most recent research, the most cited papers focused on:

  • Gene
  • Enzyme
  • DNA

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.

Top Publications

CUPSAT: prediction of protein stability upon point mutations

Vijaya Parthiban;M. Michael Gromiha;Dietmar Schomburg.
Nucleic Acids Research (2006)

470 Citations

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)

399 Citations

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.
Bioinformatics (2004)

396 Citations

ProTherm, version 4.0: thermodynamic database for proteins and mutants

K. Abdulla Bava;M. Michael Gromiha;Hatsuho Uedaira;Koji Kitajima.
Nucleic Acids Research (2004)

359 Citations

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)

334 Citations

Inter-residue interactions in protein folding and stability.

M.Michael Gromiha;S. Selvaraj.
Progress in Biophysics & Molecular Biology (2004)

296 Citations

ASAView : Database and tool for solvent accessibility representation in proteins

Shandar Ahmad;M. Michael Gromiha;Hamed Fawareh;Akinori Sarai.
BMC Bioinformatics (2004)

286 Citations

Prediction of RNA binding sites in a protein using SVM and PSSM profile

Manish Kumar;M. Michael Gromiha;G. P. S. Raghava.
Proteins (2008)

272 Citations

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)

243 Citations

Important amino acid properties for enhanced thermostability from mesophilic to thermophilic proteins.

M.Michael Gromiha;Motohisa Oobatake;Akinori Sarai.
Biophysical Chemistry (1999)

236 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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