Anand Devaprasath D. Jeyasekharan

This study identifies lipid-laden macrophages as an immunosuppressive niche in PCNSL, validated through spatial transcriptomics and mouse models, and shows SYK inhibition reverses their tumor-supportive activity.

PatternExtract generates spatial point patterns from pathology images and cell coordinates using a two-kernel segmentation method and automated classification, validated on lymphoma data.

This study maps ribosomal protein (RP) gene expression across human tissues using single-cell RNA sequencing, revealing tissue-specific patterns and linking RP heterogeneity to reproductive health and anaemia.

This study uses Perturb-seq to analyze pharmacogenomic interactions in gastric cancer, revealing gene-drug relationships and resistance mechanisms.

This study shows genotoxic chemotherapy increases CD59 expression, reducing complement-dependent cytotoxicity and rituximab efficacy in DLBCL via Chk1-mediated regulation.

ColocZStats is a 3D Slicer extension that enables colocalization analysis on z-stacks with user-defined ROIs and thresholding.

DruID integrates drug efficacy predictions with genetic and pharmacological data to provide personalized cancer drug recommendations, outperforming existing methods on cell line data.

ASTER identifies clinically actionable synthetic lethal gene pairs using statistical hypothesis testing on gene expression data.

This study shows TIP60 acetylates H2AZ, affecting DNA repair gene expression and doxorubicin sensitivity through RAD51 transcription.

The paper introduces a new network mining algorithm to identify pathway-centric interactions in cancer data, revealing dense between-pathway interactions with therapeutic potential.

The paper develops a method to predict synthetic lethal interactions by integrating heterogeneous data sources, outperforming existing methods with minimal feature engineering.