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Integration of genomic variation and phenotypic data using HmtPhenome

Preste, R.; Attimonelli, M.

2019-06-04 bioinformatics
10.1101/660282 bioRxiv
Show abstract

A full understanding of relationships between variants, genes, phenotypes and diseases is often overlooked when investigating mitochondrial functionality in both healthy and pathological situations. Gaining a comprehensive overview of this network can indeed offer interesting insights, and guide researchers and clinicians towards a full-spectrum knowledge of the mitochondrial system.\n\nGiven the current lack of tools addressing this need, we have developed HmtPhenome (https://www.hmtphenome.uniba.it), a new web resource that aims at providing a visual network of connections among variants, genes, phenotypes and diseases having any level of involvement in the mitochondrial functionality. Data are collected from several third party resources and aggregated on the fly, allowing users to clearly identify interesting relations between the involved entities. Tabular data with additional hyperlinks are also included in the output returned by HmtPhenome, so that users can extend their analysis with further information from external resources.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.