Hamim Zafar

This study shows ethanol exposure activates BMP signaling and reprograms cardiomyocyte transcriptomes, identifying key genes involved in ethanol-induced congenital heart disease.

This paper benchmarks spatial deconvolution and domain detection methods across diverse tissues and technologies, identifying top-performing approaches and highlighting method limitations.

Renoir maps ligand-target activities across spatial topologies and identifies context-specific cell-cell interactions from spatial transcriptomics data.

This paper identifies myeloid Gi signaling as a weight-independent immunometabolic switch that regulates systemic insulin sensitivity through opposing cytokine programs.

This study shows that activating Gq-signaling in islet macrophages impairs β-cell insulin secretion via the AMPK-sphingolipid axis, revealing a new immune-endocrine communication mechanism.

This study maps dynamic changes in murine pancreatic islet cell composition and transcriptional states during hyperglycaemia progression using single-cell multi-omics data.

This study shows that amylin aggregates faster on fibrillar collagen, leading to β-cell death and dysfunction, which accelerates diabetic progression.

The paper analyzes scRNA-seq data to infer clone-specific gene regulatory networks in tumors and shows distinct network architectures and treatment-induced rewiring across cancer types.

multiHIVE integrates CITE-seq data using a hierarchical deep generative model, improving trajectory inference and gene trend identification.

PHALCON improves variant calling and tumor phylogeny reconstruction in large-scale single-cell panel sequencing data by modeling tumor evolution under a finite-sites model.

The paper introduces NSC-seq, a CRISPR-based molecular clock to track temporal and clonal events in development and precancer, revealing polyancestral initiation in colonic precancers.

The paper shows that Yorkie acts as a tumor suppressor in Drosophila squamous epithelia by suppressing TOR-driven α-tubulin acetylation, which is tissue-specific and distinct from other epithelial lineages.

scDREAMER integrates single-cell datasets across batches and species using a deep generative model and adversarial classifier, outperforming existing methods in batch correction and scalability.

The paper identifies THBS2/TSP2 as a key driver of fibrogenesis in NAFLD by showing its expression in HSCs and its role in collagen activation, suggesting it as a potential anti-fibrotic target.

MARGARET improves trajectory inference by accurately reconstructing complex cell-state manifolds and identifying cell fate plasticity in single-cell RNA-seq data.

FiMO infers the temporal order of somatic mutations in cancer using a Bayesian framework, outperforming existing methods on synthetic and real datasets.

This paper introduces LinTIMaT, a method that integrates CRISPR-Cas9 mutation and transcriptomic data to reconstruct lineage trees with improved accuracy and coherence.

SiCloneFit jointly reconstructs tumor clones and their phylogeny from single-cell genome sequencing data using a Bayesian framework to account for technical errors.

This paper introduces scVILP, a combinatorial method for detecting mutations in single-cell sequencing data by reconstructing phylogenies, achieving better runtime than existing methods.

SiFit infers tumor phylogenies from single-cell sequencing data using a finite-sites model, improving accuracy over infinite-sites methods in colorectal cancer datasets.