z-logo
open-access-imgOpen Access
Measuring gene functional similarity based on group-wise comparison of GO terms
Author(s) -
Zhixia Teng,
Maozu Guo,
Xiaoyan Liu,
Qiguo Dai,
Chunyu Wang,
Ping Xuan
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt160
Subject(s) - semantic similarity , similarity (geometry) , computer science , context (archaeology) , cluster analysis , similarity measure , data mining , function (biology) , information retrieval , computational biology , artificial intelligence , biology , genetics , image (mathematics) , paleontology
Compared with sequence and structure similarity, functional similarity is more informative for understanding the biological roles and functions of genes. Many important applications in computational molecular biology require functional similarity, such as gene clustering, protein function prediction, protein interaction evaluation and disease gene prioritization. Gene Ontology (GO) is now widely used as the basis for measuring gene functional similarity. Some existing methods combined semantic similarity scores of single term pairs to estimate gene functional similarity, whereas others compared terms in groups to measure it. However, these methods may make error-prone judgments about gene functional similarity. It remains a challenge that measuring gene functional similarity reliably.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom