A novel network-based method for measuring the functional relationship between gene sets
Author(s) -
Qianghu Wang,
Jie Sun,
Meng Zhou,
Haixiu Yang,
Yan Li,
Xiang Li,
Sali Lv,
Xia Li,
Yixue Li
Publication year - 2011
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/btr154
Subject(s) - computational biology , gene , functional genomics , gene regulatory network , similarity (geometry) , functional analysis , biology , rank (graph theory) , computer science , data mining , genetics , genomics , genome , artificial intelligence , gene expression , mathematics , image (mathematics) , combinatorics
In the functional genomic era, a large number of gene sets have been identified via high-throughput genomic and proteomic technologies. These gene sets of interest are often related to the same or similar disorders or phenotypes, and are commonly presented as differentially expressed gene lists, co-expressed gene modules, protein complexes or signaling pathways. However, biologists are still faced by the challenge of comparing gene sets and interpreting the functional relationships between gene sets into an understanding of the underlying biological mechanisms.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom