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Biology and Biochemistry
India
2026

D-Index & Metrics

Biology and Biochemistry

D-Index
89
Citations
31243
World Ranking
2535
National Ranking
5

Research.com Recognitions

  • 2026 - Research.com Biology and Biochemistry in India Leader Award
  • 2025 - Research.com Biology and Biochemistry in India Leader Award
  • 2023 - Research.com Biology and Biochemistry in India Leader Award
  • 2022 - Research.com Biology and Biochemistry in India Leader Award

Overview

Gajendra P. S. Raghava is affiliated with the Indraprastha Institute of Information Technology Delhi in India. Their research spans multiple fields, notably Biochemistry, Genetics and Molecular Biology, with 264 publications, and Medicine, with 98 publications. Within these, detailed focus areas include Molecular Biology, Immunology, Cancer Research, Microbiology, and Radiology, Nuclear Medicine and Imaging.

Their main research topics include:

  • Vaccines and immunoinformatics approaches
  • Machine Learning in Bioinformatics
  • Antimicrobial Peptides and Activities
  • Monoclonal and Polyclonal Antibodies Research
  • RNA and protein synthesis mechanisms
  • Immunotherapy and Immune Responses
  • Genomics and Phylogenetic Studies

Frequent publication venues for their work include:

  • bioRxiv (Cold Spring Harbor Laboratory), 64 publications
  • Computers in Biology and Medicine, 11 publications
  • Briefings in Bioinformatics, 10 publications
  • Drug Discovery Today, 5 publications
  • Frontiers in Immunology, 5 publications

Some of the prominent recent papers authored by their team are:

  • AlgPred 2.0: an improved method for predicting allergenic proteins and mapping of IgE epitopes, 2020, Briefings in Bioinformatics
  • AntiCP 2.0: an updated model for predicting anticancer peptides, 2020, Briefings in Bioinformatics
  • ToxinPred2: an improved method for predicting toxicity of proteins, 2022, Briefings in Bioinformatics
  • ToxinPred 3.0: An improved method for predicting the toxicity of peptides, 2024, Computers in Biology and Medicine
  • Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19, 2020, Briefings in Bioinformatics

Their frequent coauthors include:

  • Sumeet Patiyal
  • Anjali Dhall
  • Shubham Choudhury
  • Neelam Sharma
  • Akanksha Arora

In addition to journal articles, Gajendra P. S. Raghava has contributed to book publications, including a book published by Springer Nature titled "Recent Advances in Civil Engineering" in 2022.

Best Publications

  • Prediction of continuous B-cell epitopes in an antigen using recurrent neural network.

    Sudipto Saha;G. P. S. Raghava

  • In Silico Approach for Predicting Toxicity of Peptides and Proteins

    Sudheer Gupta;Pallavi Kapoor;Kumardeep Chaudhary;Ankur Gautam

  • ProPred: prediction of HLA-DR binding sites

    Harpreet Singh;G. P. S. Raghava

  • AlgPred: prediction of allergenic proteins and mapping of IgE epitopes.

    Sudipto Saha;G. P. S. Raghava

  • Designing of interferon-gamma inducing MHC class-II binders

    Sandeep Kumar Dhanda;Pooja Vir;Gajendra P S Raghava

  • ProPred1: prediction of promiscuous MHC Class-I binding sites.

    Harpreet Singh;G.P.S. Raghava

  • BcePred: Prediction of Continuous B-Cell Epitopes in Antigenic Sequences Using Physico-chemical Properties

    Sudipto Saha;G. P. S. Raghava

  • THPdb: Database of FDA-approved peptide and protein therapeutics

    Salman Sadullah Usmani;Gursimran Bedi;Jesse S. Samuel;Sandeep Singh

  • Prediction of CTL epitopes using QM, SVM and ANN techniques.

    Manoj Bhasin;G.P.S. Raghava

  • ESLpred: SVM-based method for subcellular localization of eukaryotic proteins using dipeptide composition and PSI-BLAST

    Manoj Bhasin;G. P. S. Raghava

  • Improved Method for Linear B-Cell Epitope Prediction Using Antigen’s Primary Sequence

    Harinder Singh;Hifzur Rahman Ansari;Gajendra P. S. Raghava

  • Identification of conformational B-cell Epitopes in an antigen from its primary sequence

    Hifzur Rahman Ansari;Gajendra P. S. Raghava

  • Classification of nuclear receptors based on amino acid composition and dipeptide composition.

    Manoj Bhasin;Gajendra P.S. Raghava

  • CancerPPD: a database of anticancer peptides and proteins

    Atul Tyagi;Abhishek Tuknait;Priya Anand;Sudheer Gupta

  • Analysis and prediction of antibacterial peptides.

    Sneh Lata;BK Sharma;Gajendra Ps Raghava

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

    Manish Kumar;M. Michael Gromiha;G. P. S. Raghava

  • NPACT: Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database

    Manu Mangal;Parul Sagar;Harinder Singh;Gajendra P. S. Raghava

  • PSLpred: prediction of subcellular localization of bacterial proteins

    Manoj Bhasin;Aarti Garg;G. P. S. Raghava

  • In silico approaches for designing highly effective cell penetrating peptides

    Ankur Gautam;Kumardeep Chaudhary;Rahul Kumar;Arun Sharma

  • Prediction of IL4 Inducing Peptides

    Sandeep Kumar Dhanda;Sudheer Gupta;Pooja Vir;G. P. S. Raghava

Frequent Co-Authors

Manoj Bhasin
Manoj Bhasin Emory University
Samir K. Brahmachari
Samir K. Brahmachari Institute of Genomics and Integrative Biology
Geoffrey J. Barton
Geoffrey J. Barton University of Dundee
M. Michael Gromiha
M. Michael Gromiha Indian Institute of Technology Madras
Darren R. Flower
Darren R. Flower Aston University
Ole Lund
Ole Lund Danish National Genome Center
Vinod Scaria
Vinod Scaria Institute of Genomics and Integrative Biology
Rakesh K. Jain
Rakesh K. Jain Harvard University
Thomas Kieber-Emmons
Thomas Kieber-Emmons University of Arkansas for Medical Sciences
Shoba Ranganathan
Shoba Ranganathan Macquarie University

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