Mapping and analysis of human disease network map (diseasome) on mouse genotype & phenotype network

Date

2017

Author

Can, Sultan Nilay

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Mouse is the primary model organism to study mammalian genetics. The genome of mouse is incisively and specifically modified and controlled to study the mutations in the human genome, to discover the molecular mechanisms of various complex human diseases such as cancers, diabetes, hereditary and neurological disorders. Various ontology systems have been constructed to express metabolic functions and diseases as controlled vocabulary terms. This way, abstract definitions such as gene functions, diseases or phenotypes become machine readable and quantifiable data. Mammalian Phenotype Ontology (MPO) is one of these databases that generates standardized terms to define phenotyping textures in mammals by carrying out gene knock out experiments in mice, which was followed by the observation of abnormal phenotypes. v In a previous study, biological networks were designed to analyse the relationships between complex human diseases and the genes responsible for the occurrence of those diseases. Human disease network focused on 22 different disease classes and brought insight to the complex relations between different disease classes. This study aims to map the human disease network onto the mouse genotype/phenotype data by generating multi-partite networks of human diseases – human/mouse genes – phenotypic abnormalities observed in targeted knock-out-mouse models. The resulting networks are presented to the research community in an online interactive platform. The output of this work is expected to aid experimental researchers to select the appropriate targeted knock-out mouse models to study a specific human disease. Furthermore, the mappings between disease and phenotype terms is expected to enrich the ongoing efforts to curate specific symptoms and effects of diseases to improve medical diagnosis.  

Subject Keywords

Diseases., Genomes., Gene mapping., Gene regulatory networks.

URI

http://etd.lib.metu.edu.tr/upload/12621198/index.pdf
https://hdl.handle.net/11511/26626

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Graduate School of Informatics, Thesis