Ragothaman M. Yennamalli

This study investigates calcium-dependent conformational changes in TG2 and their role in celiac disease using molecular dynamics and nsSNP analysis.

This study performs a meta-analysis of bovine transcriptomic datasets to identify immune-related differentially expressed genes and signaling pathways associated with disease resistance in cattle.

The paper identifies genomic signatures of innate immunity in indicine cattle breeds through whole-genome analysis, revealing immune-related variants and selection signals absent in taurine breeds.

The paper develops a structure-annotated genome-scale metabolic model for Bacillus subtilis to include levan biosynthesis, using AlphaFold2 for structural information.

The paper maps the metalloproteome of Deinococcus indicus DR1 by integrating structural and functional annotations to identify proteins involved in heavy-metal tolerance.

The paper trains a machine learning model to classify LPMO sequences into CAZy families using structural features extracted from 3D models.

The paper introduces a deep learning model for annotating LPMO families, achieving high accuracy and outperforming existing tools.

This study identifies genomic variations in Indian cattle breeds that contribute to immune traits and disease resistance through whole-genome sequencing and comparative analysis.

The paper introduces B-AMP v2.0, an upgraded repository of antimicrobial peptides and biofilm targets, with tools for in silico evaluation of AMPs against specific bacterial biofilm proteins.

The paper compares L-lysine and L-arginine biosynthesis pathways in 23 Deinococcus genomes, identifying structural variations and potential functional divergence.