Anchita Das Sharma
MTech Genetic Engineering student and bioinformatics researcher
anchita-das
Chengalpattu, Tamil Nadu, India
Joined April 2026
Network
235 connectionsSummary
Active in bioinformatics and peptide research — authorship and co-authorship on multiple computational biology and antimicrobial/antifungal peptide studies indicate hands-on experience with in-silico methods for peptide discovery and characterization. researchgate+3
Undergraduate-to-postgraduate trajectory in biotechnology/genetic engineering — completed a B.Tech in Biotechnology and pursued an M.Tech in Genetic Engineering at SRM IST, reflecting formal academic training in molecular biology and related fields. deepenrich
Industry-facing laboratory experience — held R&D scientist role and industrial trainee positions providing practical wet-lab and quality-control exposure in pharmaceutical and life-science settings. deepenrich
Engaged online academic profile and credentials — maintains scholarly profiles (Google Scholar, ResearchGate), a LinkedIn presence for professional roles, and Coursera certifications demonstrating continuing online learning. google+2
Work
Education
Projects
Writing
High Throughput Meta-analysis of Antimicrobial Peptides for Characterizing Class Specific Therapeutic Candidates: An in-silico Approach
January 1, 2024A high-throughput meta-analysis applying in-silico methods to characterize antimicrobial peptide classes and identify therapeutic candidates.
Bioinformatics Approaches Applied to the Discovery of Antifungal Peptides
March 1, 2023Survey/analysis of computational bioinformatics methods used to discover antifungal peptides.
Two optimized antimicrobial peptides with therapeutic potential for clinical antibiotic-resistant Staphylococcus aureus
Research on design/optimization of antimicrobial peptides with potential therapeutic effect against antibiotic-resistant Staphylococcus aureus.
ClassAMP: A Prediction Tool for Classification of Antimicrobial Peptides
Work related to ClassAMP, a computational prediction tool for classification of antimicrobial peptides.