Vakul Mohanty

TCR-FramePose: a local-frame representation for decomposing global docking and CDR3 loop geometry in TCR-pMHC recognition

This paper introduces TCR-FramePose, a geometric framework for analyzing TCR-pMHC recognition, showing it captures novel structural features beyond conventional descriptors.

Agent-based modeling of cellular dynamics in adoptive cell therapy

This paper introduces ABMACT, an agent-based model to simulate tumor-immune dynamics in adoptive cell therapy and identifies key factors for optimal efficacy.

Spatial immune hubs defined by conserved activated dendritic cells are remodeled by immunotherapy

The paper constructs an integrated atlas of tumor-infiltrating dendritic cells across species and immunotherapy conditions, revealing conserved activation states and spatial reorganization in response to therapy.

Romaciclib, a CDK8/CDK19 inhibitor, can overcome venetoclax resistance through a combinatorial strategy

This study shows that romaciclib combined with venetoclax overcomes venetoclax resistance in AML through synergistic apoptosis induction and suppression of resistance pathways.

Literature-scaled immunological gene set annotation using AI-powered immune cell knowledge graph (ICKG)

The paper constructs an immune cell knowledge graph (ICKG) using AI to annotate immunological gene sets more accurately than existing methods.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

The paper constructs immune-specific gene sets using non-negative matrix factorization on bulk RNA-seq data to improve immune subtype analysis and ICB response prediction.

novoRNABreak: local assembly for novel splice junction and fusion transcript detection from RNA-seq data

novoRNABreak detects novel splice junctions and fusion transcripts in cancer RNA-seq data with high sensitivity and efficiency.

Characterizing metabolism from bulk and single-cell RNA-seq data using METAFlux

The paper develops METAFlux to infer metabolic fluxes from bulk and single-cell RNA-seq data, showing improved accuracy over existing methods in cancer TME analysis.

Characterizing transition cells in developmental processes from scRNA-seq data

The paper models scRNA-seq data from developmental processes using SDEs to identify transition cells that explain heterogeneity and predict cell fate in early tumorigenesis.

Sensei: How many samples to tell evolution in single-cell studies?

Sensei determines required sample sizes for detecting cell type abundance changes in single-cell studies using a beta-binomial model and t-test expansion.

Single-Cell Manifold Preserving Feature Selection (SCMER)

SCMER identifies non-redundant molecular features that delineate both common cell lineages and rare cellular states in single-cell data.

Single-cell copy number lineage tracing enabling gene discovery

The paper introduces MEDALT and LSA to reconstruct copy number lineage trees from single-cell data and identify fitness-associated genes, showing improved accuracy over phylogenetics methods in cancer datasets.

Unbiased integration of single cell multi-omics data

bindSC integrates single-cell multi-omics data accurately by aligning rows and columns without approximations, outperforming existing methods in various biological contexts.

OmicPioneer-sc: an integrated, interactive visualization environment for single-cell sequencing data

OmicPioneer-sc provides an interactive visualization tool for single-cell sequencing data, integrating dimensionality reduction, heat maps, and pathway modules to aid in cell-type annotation and multi-omic analysis.