Mar 31, 2020

Predicting candidate genes from phenotypes, functions, and anatomical site of expression

BioRxiv : the Preprint Server for Biology

Abstract

Motivation: Over the past years, many computational methods have been developed to incorporate information about phenotypes for disease gene prioritization task. These methods generally compute the similarity between a patient's phenotypes and a database of gene-phenotype to find the most phenotypically similar match. The main limitation in these methods is their reliance on knowledge about phenotypes associated with particular genes, which is not complete in humans as well as in many model organisms such as the mouse and fish. Information about functions of gene products and anatomical site of gene expression is available for more genes and can also be related to phenotypes through ontologies and machine learning models. Results: We developed a novel graph-based machine learning method for biomedical ontologies which is able to exploit axioms in ontologies and other graph-structured data. Using our machine learning method, we embed genes based on their associated phenotypes, functions of the gene products, and anatomical location of gene expression. We then develop a machine learning model to predict gene--disease associations based on the associations between genes and multiple biomedical ontologies, and this model significan...Continue Reading

  • References
  • Citations

References

  • We're still populating references for this paper, please check back later.
  • References
  • Citations

Citations

  • This paper may not have been cited yet.

Mentioned in this Paper

Study
Neurons
Brain
Research Personnel
Anatomical Space Structure
Behavioral Defense Response
Brain Function
Neuroimaging
Analysis
Population Group

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.

Related Papers

Comparative and Functional Genomics
G V GkoutosD Davidson
Pacific Symposium on Biocomputing
O BodenreiderA T McCray
Journal of Biomedical Semantics
Irene PapatheodorouDamian Smedley
BioRxiv : the Preprint Server for Biology
Fatima Zohra SmailiRobert Hoehndorf
© 2020 Meta ULC. All rights reserved