Genetic variant effect prediction by supervised nonnegative matrix tri-factorization-Reference-Cited by-同舟云学术

Genetic variant effect prediction by supervised nonnegative matrix tri-factorization

Published:2021 Issue:5 Volume:17 Page:740-751
ISSN:2515-4184
Container-title:Molecular Omics
language:en
Short-container-title:Mol. Omics

Author:

Arani Asieh Amousoltani¹,Sehhati Mohammadreza²^ORCID,Tabatabaiefar Mohammad Amin³⁴

Affiliation:

1. Department of Bioelectric and Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

2. Department of Bioinformatics, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

3. Department of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

4. GTaC Corp., Deputy of Research and Technology, Isfahan University of Medical Sciences, Isfahan, Iran

Abstract

A new feature space, which can discriminate deleterious variants, was constructed by the integration of various input data using the proposed supervised nonnegative matrix tri-factorization (sNMTF) algorithm.

Funder

Isfahan University of Medical Sciences

Publisher

Royal Society of Chemistry (RSC)

Subject

Genetics,Molecular Biology,Biochemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/MO/D1MO00038A

Reference64 articles.

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