The ontology reference model for visual selectivity analysis in drug-target interactions

Qiong Cheng, Felix A. Lopez, Celia Duran, Christopher Camarillo, Tudor I. Oprea, Stephan C Schuerer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In a drug development process, appropriate drug-binding selectivity is critical for a success drug. However the selectivity in a data source, showing the intensity of efforts, may be limited to prior knowledge of the expertise or be biased towards the hypothesis testing. With the increasing of drug screening data, it is challenging to coordinate the efforts and execute data governance at a large scale. Visual selectivity analysis for examining target selection is in demand. We proposed a knowledge-driven approach and designed an ontology reference model to provide an intuitive view of the selectivity in a drug-target interaction network data. We employed the model to carry out the visual selectivity analysis on the NIMH Psychoactive Drug Screening Program (PDSP) data and the LINCS Compounds-interacting ChEMBL Database. The analysis indicates the possible 'dark matter' drug targets. The approach can be expanded to coordinate other experimental screening data and set a stage for the analysis of the mechanism of action of biological therapies.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2091-2097
Number of pages7
Volume2017-January
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
CountryUnited States
CityKansas City
Period11/13/1711/16/17

Keywords

  • binding selectivity
  • drug-target interactions
  • ontology

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Cheng, Q., Lopez, F. A., Duran, C., Camarillo, C., Oprea, T. I., & Schuerer, S. C. (2017). The ontology reference model for visual selectivity analysis in drug-target interactions. In Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (Vol. 2017-January, pp. 2091-2097). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217982