Shawn M. Gomez

This study shows that daraxonrasib, a pan-RAS(on) inhibitor, effectively inhibits TNBC cell proliferation and tumor growth, either alone or in combination with a MEK inhibitor.

This study shows trametinib causes mitochondrial injury and innate immune activation in mouse hearts, leading to cardiomyopathy and heart failure.

The paper uses proteomic kinome profiling and machine learning to predict kinase inhibitor cardiotoxicity by analyzing off-target kinase engagement and its association with cardiac adverse events.

The paper develops a classifier, DeCAF, to identify permissive and restraining cancer-associated fibroblast subtypes from bulk RNAseq data and validates its clinical relevance across multiple cancer types.

This study quantifies kinase protein abundance in human tissues using proteomic mass spectrometry, revealing heterogeneity in breast cancer subtypes and enabling clinical applications.

The paper uses machine learning to predict clinical outcomes in pediatric Crohn's disease by analyzing gene expression from ileal and colonic tissues.

The paper links kinase inhibitor treatment effects to cell line responses using integrated kinome profiling data and builds predictive models with high accuracy.

The paper predicts cancer cell line sensitivity to kinase inhibitor combinations using kinome inhibition states and machine learning, achieving high accuracy in both simulated and experimental settings.

The paper predicts cell viability in cancer cell lines using kinase inhibitor profiles and gene expression data, achieving R2 of 0.78 and RMSE of 0.154.

EMBER predicts kinase-substrate phosphorylation events using a deep learning model that integrates motif and phylogeny information, improving phosphorylation network mapping.

The paper evaluates druggable genes in mice and finds that many understudied ones have significant phenotypes similar to human diseases, suggesting therapeutic potential.

The paper links kinome state with cell viability in PDAC tumor and stroma cell lines using regression and classification models, finding predictive relationships and key kinases driving viability responses.

This paper refines the definition of the human kinome, identifies understudied kinases, and highlights their potential as drug targets through differential expression, essentiality, and mutation data.

Coral provides an interactive web tool for visualizing human kinome data with customizable features and high-resolution outputs.