Open AccessBioentity2vec: Attribute- and behavior-driven representation for predicting multi-type relationships between bioentities
Author(s) -
Zhen-Hao Guo,
ZhuHong You,
Yanbin Wang,
De-Shuang Huang,
Hai-Cheng Yi,
Zhan-Heng Chen
Publication year - 2020
Publication title -
gigascience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.947
H-Index - 54
ISSN - 2047-217X
DOI - 10.1093/gigascience/giaa032
Subject(s) - computer science , biological network , biological data , representation (politics) , data mining , artificial intelligence , machine learning , aggregate (composite) , precision and recall , classifier (uml) , bioinformatics , biology , politics , political science , law , materials science , composite material
The explosive growth of genomic, chemical, and pathological data provides new opportunities and challenges for humans to thoroughly understand life activities in cells. However, there exist few computational models that aggregate various bioentities to comprehensively reveal the physical and functional landscape of biological systems.