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Use case: PhenoBridge - crossing the species bridge between mouse and human | BioMedBridges

WP7 - Use case: PhenoBridge - crossing the species bridge between mouse and human

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This use case tackles a major challenge related to the available mouse phenotype and human clinical data: different ontological phenotype descriptions hinder researchers from both sides to cross the species bridge between mouse models and human. We will make use of comparable diabetes and obesity-related large-scale datasets in mouse and human provided by Infrafrontier, BBMRI and ELIXIR.

This use case will

  1. Identify and develop a set of annotations, necessary terminologies, and mappings between  terminologies for human and mouse models of diabetes and obesity
  2. Identify and group related interacting parameters in human and mouse which are involved in the development of clinical and molecular phenotypes
  3. Formalise rules for phenotypic annotation in human and mouse to work towards automation of phenotypic discovery and develop a related prototype service.

Integration at the level of phenotypes in these species requires interaction with the wider community. Different resources are currently in use, requiring expert input to describe the phenotypes, but also to formalize the phenotypic  descriptions. To maximise use of existing terminologies (mouse phenotype, human phenotype ontology etc), WP7 will work with the different communities to map between existing terms, provide new terms and also to annotate existing datasets.


Task 1: Analysis of existing mouse phenotype and human disease ontology terms

The analysis will lead to the submission of proposals for new terms to gather a comprehensive set of terms to describe diabetes and obesity phenotypes in mouse and human. As a first step, potentially relevant phenotypic parameters available from mouse high-throughput screening and in-depth phenotyping studies as well as from human studies across technologies such as gene expression and GWAS studies from the BioSD and metabolome profiles will be listed. For analysed parameters associated with diabetic/obese conditions that are not yet described appropriately in ontology terms, new terms have to be defined. A many to many mapping of phenotypic or diagnostic parameters onto ontology terms will be developed using the clinical expertise of scientists coming from the mouse or human diabetes and obesity fields.

Task 2: Mapping of mouse and human phenotypes of diabetes and obesity

Based on the ontology terms developed in Task 1, observation patterns will be defined that describe clinical and molecular characteristics of diabetes and obesity phenotypes in mouse and human. The identification of rules and criteria for identifying diabetes and obesity phenotypes (and how they map in mice and humans) will lead to a prototype for an automated procedure to identify phenotype matches across mouse and human.

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