Taha Mohseni Ahooyi

ddkg.skill translates biomedical questions into Cypher queries for the DDKG, improving accuracy through structured references and validation.

MOSAIC learns graph node embeddings by analyzing dominant spectral components of diffusion operators, outperforming existing methods in biomedical graph tasks.

The paper introduces BIFO, an ontology that specifies biologically admissible directed transformations in biomedical knowledge graphs to enable meaningful signal propagation.

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

The paper develops HSCLO38, a framework for connecting genomic features in a knowledge graph, and evaluates its performance with large-scale genomic data.

Petagraph integrates biomolecular data into a unified knowledge graph using UMLS ontologies to enable efficient multi-omics analysis across multiple datasets.

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.