Use of Model Organism and Disease Databases to Support Matchmaking for Human Disease Gene Discovery

Christopher J. Mungall, Nicole L. Washington, Jeremy Nguyen-Xuan, Christopher Condit, Damian Smedley, Sebastian Köhler, Tudor Groza, Kent Shefchek, Harry Hochheiser, Peter N. Robinson, Suzanna E. Lewis, Melissa A. Haendel

Research output: Contribution to journalArticle

21 Scopus citations

Abstract

The Matchmaker Exchange application programming interface (API) allows searching a patient's genotypic or phenotypic profiles across clinical sites, for the purposes of cohort discovery and variant disease causal validation. This API can be used not only to search for matching patients, but also to match against public disease and model organism data. This public disease data enable matching known diseases and variant-phenotype associations using phenotype semantic similarity algorithms developed by the Monarch Initiative. The model data can provide additional evidence to aid diagnosis, suggest relevant models for disease mechanism and treatment exploration, and identify collaborators across the translational divide. The Monarch Initiative provides an implementation of this API for searching multiple integrated sources of data that contextualize the knowledge about any given patient or patient family into the greater biomedical knowledge landscape. While this corpus of data can aid diagnosis, it is also the beginning of research to improve understanding of rare human diseases.

Original languageEnglish (US)
Pages (from-to)979-984
Number of pages6
JournalHuman mutation
Volume36
Issue number10
DOIs
StatePublished - Oct 1 2015

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Keywords

  • Informatics
  • Matchmaker Exchange
  • Model systems
  • Ontology
  • Phenotype
  • Rare disease

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Mungall, C. J., Washington, N. L., Nguyen-Xuan, J., Condit, C., Smedley, D., Köhler, S., Groza, T., Shefchek, K., Hochheiser, H., Robinson, P. N., Lewis, S. E., & Haendel, M. A. (2015). Use of Model Organism and Disease Databases to Support Matchmaking for Human Disease Gene Discovery. Human mutation, 36(10), 979-984. https://doi.org/10.1002/humu.22857