Popular protein manuscript released on bioRxiv

Bioinformatics Data science HUPO

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Our manuscript on popular proteins across the human diseasome is now on preprint. In this manuscript we worked with collaborators at Cedars-Sinai and Stanford to identify proteins that are preferentially associated with each of over 10,000 disease terms recorded in three standardized vocabularies (Disease Ontology, Pathway Ongology, and Human Phenotype Ontology).

One of the interesting things we looked at is whether we can use this massive collection of popular protein lists across disease terms to analyze gene and protein list data such as from a list of differentially regulated proteins in a proteomics experiment comparing normal and diseased tissues. We attempted to achieve this by allowing "protein-to-topic" queries. For instance, since we know that the disease terms “acute myocardial infarction”, “pulmonary embolism”, and “kidney failure” each feature cardiac troponin I as a popular protein, when querying TNNI3 against this popular protein database, we should then be able to find the diseases with which the protein is associated.

We will also be presenting the poster shown above on the project at the Human Proteome Organization meeting in Orlando at the end of the month. For more information please see our preprint on bioRxiv and visit the Pubpular web app.