Colleen H. Xu
A5026748072- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Genomics and Rare Diseases
- Computational Drug Discovery Methods
- Topic Modeling
- Monoclonal and Polyclonal Antibodies Research
- Advanced Biosensing Techniques and Applications
- Genetics, Bioinformatics, and Biomedical Research
- Biomedical and Engineering Education
- Biosimilars and Bioanalytical Methods
Scripps Research Institute
2022-2024
Regeneron (United States)
2019
Abstract There are thousands of distinct disease entities and concepts, each which known by different sometimes contradictory names. The lack a unified system for managing these poses major challenge both machines humans that need to harmonize information better predict causes treatments disease. Mondo Disease Ontology is an open, community-driven ontology integrates key medical biomedical terminologies, supporting data integration improve diagnosis, treatment, translational research....
Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge can easily represent heterogeneous types of information, and many algorithms tools exist querying analyzing graphs. Biomedical have been used in a variety applications, including drug repurposing, identification targets, prediction side effects, clinical decision support. Typically, constructed by centralization integration from multiple disparate sources. Here, we describe...
Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to sheer number and complexity sources. In addition, semantic incompatibilities hinder efforts harmonize integrate across these diverse As part The Biomedical Translator Consortium, we developed graph-based question-answering system designed augment human reasoning accelerate translational scientific discovery: system. We applied answer biomedical questions in...
As large clinical and multiomics datasets knowledge resources accumulate, they need to be transformed into computable actionable information support automated reasoning. These range from laboratory experiment results electronic health records (EHRs). Barriers accessibility sharing of such include diversity content, size privacy. Effective transformation data requires harmonization stakeholder goals, implementation, enforcement standards regarding quality completeness, availability for...
Background: Soluble drug target in clinical study samples generated false positive results anti-drug antibody (ADA) bridging assays due to target-mediated bridging. Results: The combination of two target-blocking reagents and mild basic assay pH resulted high tolerance recombinant protein reduced levels positivity with pharmacokinetic profiles that did not indicate significant ADA response. Testing low-affinity serum from immunized rabbits known nonclinical studies rats confirmed the assay's...
Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge can easily represent heterogeneous types of information, and many algorithms tools exist querying analyzing graphs. Biomedical have been used in a variety applications, including drug repurposing, identification targets, prediction side effects, clinical decision support. Typically, constructed by centralization integration from multiple disparate sources. Here, we describe...