Mehran Karimzadeh

The paper introduces ecCLIP for high-resolution RBP binding maps and Pythia for structure-aware RNA-protein interaction modeling, improving RNA half-life prediction and variant effect assessment.

X-Cell predicts causal perturbation responses across diverse cellular contexts using a diffusion language model trained on a large CRISPRi Perturb-seq dataset.

This study identifies an intrinsically disordered region in LARP6 that restricts conformational flexibility of the La-module, enabling RNA-binding selectivity and promoting cancer cell viability and invasion.

This study identifies oncRNAs as drivers of HPV-negative head and neck cancer and shows their potential for pre-diagnostic detection.

Exai-1 is a transformer-based model that integrates RNA sequence and expression data to improve cfRNA analysis for disease detection.

The paper identifies ZZEF1 as a tRNA-specific transcription factor that suppresses breast cancer metastasis by regulating tRNA-LysUUU expression and affecting codon-specific translation.

The paper identifies transcription factors that drive osteosarcoma cell states and shows that modulating them can increase sensitivity to targeted therapy.

This study investigates the molecular effects of androgen in the human breast using single-cell transcriptome, chromatin, and spatial profiling of transgender men undergoing androgen therapy, revealing changes in gene expression, immune populations, vasculature, and metabolism.

Virtual ChIP-seq predicts transcription factor binding in new cell types using neural networks and integrates ChIP-seq data with chromatin accessibility and gene expression.

The paper introduces a single-molecule sequencing method to measure nucleosome positions on chromatin fibers and reveals heterogeneous patterns of oligonucleosome occupancy across epigenomic domains.

The paper introduces Umap and Bismap tools to assess genome and methylome mappability, revealing significant non-uniquely mappable regions in both unmodified and bisulfite-converted genomes.

The paper describes using Segway software to annotate genomes with chromatin data from ChIP-seq experiments, providing a semi-automated workflow for interpretation.