Pratik Dutta

Genomic Language Model for Predicting Enhancers and Their Allele-Specific Activity in the Human Genome

The paper develops DNABERT-Enhancer, a genomic language model for enhancer prediction, achieving high accuracy and identifying allele-specific activity and candidate SNPs.

PGViS: Personal Genome Variant interpretation Score for lung cancer genomes

PGViS quantifies non-coding germline regulatory risk in NSCLC by integrating variant-level signals with population reference data.

TSProm: Deciphering the Genomic Context of Tissue Specificity

TSProm identifies tissue-specific gene regulatory elements by training specialized DNA models and using explainable AI to analyze promoter sequences in human tissues.

HViLM: A Foundation Model for Viral Genomics Enables Multi-Task Prediction of Pathogenicity, Transmissibility, and Host Tropism

HViLM is a foundation model for viral genomics that predicts pathogenicity, transmissibility, and host tropism across multiple viral families with high accuracy.

Evaluation and optimization of sequence-based gene regulatory deep learning models

The paper evaluates and optimizes sequence-based gene regulatory deep learning models using a DREAM Challenge dataset, showing improvements through architectural and training strategy refinements.