Mayukh Mondal

IntegrateALL is an RNA-seq pipeline that integrates expression-based subtyping, gene fusion detection, and virtual karyotyping to classify B-ALL with high accuracy.

This study identifies how developmental maturity and fusion partner influence treatment response in KMT2A-rearranged B-ALL across all ages.

This study uses neural networks to analyze genetic data from Papua New Guinean populations, finding a bottleneck and slower growth rate rather than admixture with an early out of Africa population.

This study examines Denisovan and Neandertal DNA distribution in Papua New Guinean populations, finding that Denisovan-like haplotypes are associated with brain development and immune response genes, suggesting adaptive significance.

This study presents the first comprehensive mutational and transcriptional analysis of B-cell precursor lymphoblastic lymphoma (BCP-LBL), revealing molecular similarities to BCP-ALL but with distinct mutation patterns in epigenetic modifiers.

The paper analyzes whole exome sequencing data from individuals with severe mental illness to identify genes under positive selection and their biological functions.

This paper uses a deep learning approach to analyze whole-genome sequences and supports the back to Africa model over other hypotheses about human migration.

This study connects genetic ancestry from three ancient populations to complex traits in Estonian Biobank samples, finding ancestry-specific contributions to traits like BMI and blood cholesterol.

The paper identifies shared post-admixture adaptation patterns in the Americas by analyzing genomic data from 6,000 admixed individuals, highlighting regions associated with immune response and disease traits.