Health Information Technology Commons^™

Missing Lateral Relationships In Top‑Level Concepts Of An Ontology, Ling Zheng, Yan Chen, Hua Min, P. Lloyd Hildebrand, Hao Liu, Michael Halper, James Geller, Sherri De Coronado, Yehoshua Perl

Publications and Research

Background: Ontologies house various kinds of domain knowledge in formal structures, primarily in the form of concepts and the associative relationships between them. Ontologies have become integral components of many health information processing environments. Hence, quality assurance of the conceptual content of any ontology is critical. Relationships are foundational to the definition of concepts. Missing relationship errors (i.e., unintended omissions of important definitional relationships) can have a deleterious effect on the quality of an ontology. An abstraction network is a structure that overlays an ontology and provides an alternate, summarization view of its contents. One kind of abstraction network is …

Outlier Concepts Auditing Methodology For A Large Family Of Biomedical Ontologies, Ling Zheng, Hua Min, Yan Chen, Vipina Keloth, James Geller, Yehoshua Perl, George Hripcsak

Publications and Research

Background: Summarization networks are compact summaries of ontologies. The “Big Picture” view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concepts. For ontologies that have outgoing lateral relationships, we have developed the "partial-area taxonomy" summarization network. Prior research has identified one kind of outlier concepts, concepts of small partials-areas within partial-area taxonomies. Previously we have shown that the small partial-area technique works successfully for four ontologies (or their hierarchies).

Methods: To improve the Quality Assurance (QA) scalability, a family-based QA framework, where one QA technique is potentially applicable to …

Target Engagement Imaging Of Parp Inhibitors In Small-Cell Lung Cancer, Brandon Carney, Susanne Kossatz, Benjamin H. Lok, Valentina Schneeberger, Kishore K. Gangangari, Naga Vara Kishore Pillarsetty, Wolfgang A. Weber, Charles M. Rudin, John T. Poirier, Thomas Reiner

Publications and Research

Insufficient chemotherapy response and rapid disease progression remain concerns for smallcell lung cancer (SCLC). Oncologists rely on serial CT scanning to guide treatment decisions, but this cannot assess in vivo target engagement of therapeutic agents. Biomarker assessments in biopsy material do not assess contemporaneous target expression, intratumoral drug exposure, or drug-target engagement. Here, we report the use of PARP1/2-targeted imaging to measure target engagement of PARP inhibitors in vivo. Using a panel of clinical PARP inhibitors, we show that PARP imaging can quantify target engagement of chemically diverse small molecule inhibitors in vitro and in vivo. We measure PARP1/2 inhibition …

Improved Genome-Scale Multitarget Virtual Screening Via A Novel Collaborative Filtering Approach To Cold-Start Problem, Hansaim Lim, Paul Gray, Lei Xie, Aleksandar Poleksic

Publications and Research

Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multitarget virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by …