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arXiv · 2002.07064

Biological Random Walks: integrating heterogeneous data in disease gene prioritization

Michele Gentili·Leonardo Martini·Manuela Petti·Lorenzo Farina·Luca Becchetti
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Abstract

This work proposes a unified framework to leverage biological information in network propagation-based gene prioritization algorithms. Preliminary results on breast cancer data show significant improvements over state-of-the-art baselines, such as the prioritization of genes that are not identified as potential candidates by interactome-based algorithms, but that appear to be involved in/or potentially related to breast cancer, according to a functional analysis based on recent literature.

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Michele Gentili, Leonardo Martini, Manuela Petti, Lorenzo Farina, Luca Becchetti. 2020-02-14. Biological Random Walks: integrating heterogeneous data in disease gene prioritization. https://doi.org/10.1109/cibcb.2019.8791472

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