Sumit Madan

The paper introduces a system for predicting tissue-specific E3 ligases for targeted protein degradation using a BERT-based model and integrated biological data.

This paper introduces MultiGML, a multimodal graph machine learning approach that predicts adverse drug events by integrating diverse data sources and provides explainable biological insights.

This paper introduces a deep learning method called STEP to predict virus-host protein-protein interactions using protein sequence embeddings and a Siamese neural network, demonstrating its effectiveness on SARS-CoV-2 and JCV proteins.

SEA provides a web tool for querying and analyzing small RNA expression across ten organisms, including differential expression and classification comparisons.