A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning

A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning

Abstract Background Selecting and prioritizing candidate disease genes is necessary before conducting laboratory studies as identifying disease genes from a large number of candidate genes using laboratory methods, is a very costly and time-consuming task. There are many machine learning-based gene...

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Bibliographic Details
Main Authors: Saeid Azadifar, Ali Ahmadi
Format: Article
Language:English
Published: BMC 2022-10-01
Series:BMC Bioinformatics
Subjects:
Gene prioritization
Graph convolutional networks
Protein–protein interaction
Semi-supervised learning
Gene identification
Online Access:https://doi.org/10.1186/s12859-022-04954-x

Internet

https://doi.org/10.1186/s12859-022-04954-x

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