Parag Mallick

Multi-Scale Tri-Modal Histology Dataset Integrating Tumor Morphology, Immune Patterns, and Clinical Outcomes

Prostate-TriMod integrates visual morphology, spatial tissue maps, and clinical outcomes for prostate cancer to enable multimodal AI research.

Annotation-Free Prediction of Cancer Cells and Glands and Spatial Analysis of Immune Cells.

The paper develops TOPAZ, a tool that predicts cancerous cells/glands and analyzes immune cell spatial relationships in prostate cancer, finding that immune cell distance from cancer glands correlates with recurrence risk.

Examination of the role of mutualism in immune evasion

This study uses a computational simulation to show that mutualism enhances immune evasion in slow-growing tumors, increasing their survival chances compared to tumors without mutualism.

A theoretical framework for proteome-scale single-molecule protein identification using multi-affinity protein binding reagents

This paper introduces a theoretical framework called PrISM for proteome-scale single-molecule protein identification using multi-affinity reagents and demonstrates its high coverage and dynamic range in simulations.

Geostatistical visualization of ecological interactions in tumors

The paper introduces a geostatistical approach to visualize tumor heterogeneity and spatial patterns in the tumor microenvironment using agent-based models of ecological interactions.