Merve Dede

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.

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.

Recovering false negatives in CRISPR fitness screens with JLOE

The paper shows CRISPR screens have a 20% false negative rate and introduces JLOE to recover false negatives without increasing false discoveries.

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.

Multiplex enCas12a screens show functional buffering by paralogs is systematically absent from genome-wide CRISPR/Cas9 knockout screens

The paper shows that paralog buffering limits detection of synthetic lethal interactions in CRISPR screens, revealing many under-detected genetic dependencies.

Discovery of novel putative tumor suppressors from CRISPR screens reveals rewired lipid metabolism in AML cells

The paper identifies novel tumor suppressors from CRISPR screens and reveals rewired lipid metabolism in AML cells through functional analysis of gene modules.

Biases and Blind-Spots in Genome-Wide CRISPR Knockout Screens

This study identifies significant false negatives and blind spots in CRISPR knockout screens, showing that many genes are functionally buffered and never detected as essential.

Hierarchical organization of the human cell from a cancer coessentiality network

The paper constructs a coessentiality network from CRISPR knockout screens to infer gene function and reveal hierarchical cell organization.