Dilraj Kaur

The paper develops a tool to predict, design, and scan IL-2-inducing peptides using machine learning, deep learning, and ensemble methods, achieving high accuracy on multiple datasets.

The paper introduces a software package that computes over 50,000 features for protein/peptide function prediction, including residue-level annotations.

The paper identifies nine apoptotic pathway genes associated with prognosis in papillary thyroid carcinoma and develops risk prediction models with high accuracy.

The paper identifies prognostic biomarkers for UCEC survival using gene expression profiles of PRRs and develops risk stratification models with improved performance when combined with clinical data.

This study develops a hybrid model combining BLAST and machine learning to predict pattern recognition receptors, achieving high accuracy with an MCC of 0.82 and AUROC of 0.95.

GPSRdocker provides a docker-based container integrating bioinformatics tools for genomics, proteomics, and systems biology, enabling local or cloud use of computational resources.