Cristian Bologa

BiomarkerKB integrates and standardizes biomarker data from multiple sources to enable structured exploration and discovery of biomarker-disease relationships.

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.

KG2ML identifies disease-associated genes not in existing knowledge graphs using positive unlabeled learning and integrates with machine learning for improved classification.

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.

TIGA aggregates and ranks gene-trait associations from GWAS data to prioritize drug targets using statistical and bibliometric evidence.

The paper introduces the Drug Target Ontology (DTO) to classify and integrate drug discovery data by formalizing druggable protein targets and their characteristics.