Contribution of model organism phenotypes to the computational identification of human disease genes

Abstract

Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype–phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past decade, cross-species phenotype comparisons have proven valuble, and several ontologies have been developed for this purpose. The relative contribution of different model organisms to computational identification of disease-associated genes is not fully explored. We used phenotype ontologies to semantically relate phenotypes resulting from loss-of-function mu

Abstract by Sarah M. Alghamdi; Paul N. Schofield; Robert Hoehndorf, Disease Models & Mechanisms (2022) — licensed CC BY 4.0.

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