Daniel J. B. Clarke

Perturb-Seqr integrates multiple Connectivity Mapping datasets to enable drug and target discovery by searching for gene expression signatures of drug and gene perturbations.

The paper describes the Common Fund Data Ecosystem (CFDE), which integrates NIH Common Fund data resources to enable discovery, analysis, and collaboration across heterogeneous datasets.

The CFDE Workbench integrates metadata and processed data from Common Fund programs to enable FAIR and AI-ready cross-program knowledge discovery.

The paper introduces a knowledge graph framework for integrating and querying biomedical data across domains, demonstrating its utility in eight use cases.

The paper introduces a gene set foundation model trained on diverse gene sets to predict gene functions, achieving superior performance compared to existing methods.

RummaGEO automatically mines gene sets from GEO RNA-seq studies for human and mouse, enabling signature search and metadata analysis.

The paper shows that transient Notch activation converts human pluripotent stem cell-derived cardiomyocytes into Purkinje fiber-like cells with altered electrophysiology and gene expression.

The paper introduces a web-based platform for building bioinformatics workflows using APIs, enabling hypothesis generation across multiple data sources.

Rummagene extracts and provides access to gene sets from PMC publications for search and analysis, revealing trends and enabling functional predictions.

The paper presents a LINCS Microenvironment perturbation dataset cataloging transcriptional, proteomic, epigenomic, and phenotypic responses of MCF10A cells to six ligands, enabling integrative analysis of molecular and phenotypic changes.

The paper constructs a reproductive toxicity knowledge graph (ReproTox-KG) to link birth defects, drugs, and genes, identifying potential molecular mechanisms for drug-induced birth defects.

iLINCS provides a web-based platform for analyzing omics signatures of diseases and cellular perturbations through integrative analytics and visualization tools.

The paper describes the development of a metadata federation system for NIH Common Fund data to improve discoverability without data movement.

PrismExp improves gene function prediction by partitioning RNA-seq co-expression data into tissue-specific segments, outperforming cross-tissue approaches across multiple domains.

FAIRshake evaluates the FAIRness of research digital resources through community-driven metrics, automated assessments, and visualization tools, revealing opportunities for improvement.