Shipra Jain

The paper develops an ensemble method combining machine learning and motif analysis to predict druggable proteins, achieving high accuracy on an independent validation dataset.

This paper develops models to predict RA-inducing peptides using machine learning, deep learning, and large language models, achieving high AUC scores and implementing them in a web tool.

The paper introduces IL4Pred2, a host-specific method for predicting IL-4 inducing peptides in human and mouse, achieving high AUC and MCC scores on independent datasets.

This paper develops a machine learning model and software tool to predict NF-κB inhibitors from chemical libraries, achieving reliable predictions validated against experimental data.

The paper develops a logistic regression model with a propensity index panel of ten genes to accurately screen prostate cancer, achieving 96.36% accuracy and 0.99 AUROC.

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

This paper develops models to predict, scan, and design TNF-α inducing epitopes for human and mouse, achieving AUROC values up to 0.83 for human and 0.77 for mouse.

This paper introduces IL-13Pred, a method to predict IL-13 inducing peptides in proteins, with high accuracy for managing COVID-19 severity.

Nfeature computes a large number of features for DNA and RNA sequences, providing a standalone package and web platform for researchers.

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