Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes-Reference-Cited by-同舟云学术

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

Published:2018-09-01 Issue:17 Volume:34 Page:i901-i907
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Alshahrani Mona¹,Hoehndorf Robert¹

Affiliation:

1. Computer, Electrical and Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

Funder

King Abdullah University of Science and Technology

KAUST

Office of Sponsored Research

OSR

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/34/17/i901/25702311/bty559.pdf

Reference35 articles.

1. Gene prioritization through genomic data fusion;Aerts;Nat. Biotechnol,2006

2. Neuro-symbolic representation learning on biological knowledge graphs;Alshahrani;Bioinformatics,2017

3. A new face and new challenges for Online Mendelian Inheritance in Man (OMIM);Amberger;Hum. Mutat,2011

4. The mouse genome database: integration of and access to knowledge about the laboratory mouse;Blake;Nucleic Acids Res,2014

5. Semantic prioritization of novel causative genomic variants;Boudellioua;PLoS Comput. Biol,2017

Cited by 47 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops;Frontiers in Plant Science;2024-03-20

2. Hyperbolic hierarchical knowledge graph embeddings for biological entities;Journal of Biomedical Informatics;2023-11

3. A Self-Supervised Framework for Learning Biological Entities Representation by Fusing Class Information;IEEE Journal of Biomedical and Health Informatics;2023-08

4. Predicting disease genes based on multi-head attention fusion;BMC Bioinformatics;2023-04-21

5. A literature embedding model for cardiovascular disease prediction using risk factors, symptoms, and genotype information;Expert Systems with Applications;2023-03