SGFSC: speeding the gene functional similarity calculation based on hash tables.
BACKGROUND
In recent years, many measures of gene functional similarity have been proposed and widely used in all kinds of essential research. These methods are mainly divided into two categories: pairwise approaches and group-wise approaches. However, a common problem with these methods is their time consumption, especially when measuring the gene functional similarities of a large number of gene pairs. The problem of computational efficiency for pairwise approaches is even more prominent because they are dependent on the combination of semantic similarity. Therefore, the efficient measurement of gene functional similarity remains a challenging problem.


RESULTS
To speed current gene functional similarity calculation methods, a novel two-step computing strategy is proposed: (1) establish a hash table for each method to store essential information obtained from the Gene Ontology (GO) graph and (2) measure gene functional similarity based on the corresponding hash table. There is no need to traverse the GO graph repeatedly for each method with the help of the hash table. The analysis of time complexity shows that the computational efficiency of these methods is significantly improved. We also implement a novel Speeding Gene Functional Similarity Calculation tool, namely SGFSC, which is bundled with seven typical measures using our proposed strategy. Further experiments show the great advantage of SGFSC in measuring gene functional similarity on the whole genomic scale.


CONCLUSIONS
The proposed strategy is successful in speeding current gene functional similarity calculation methods. SGFSC is an efficient tool that is freely available at http://nclab.hit.edu.cn/SGFSC . The source code of SGFSC can be downloaded from http://pan.baidu.com/s/1dFFmvpZ .
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People's Republic of China.
Zhen
Z
Tian
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People's Republic of China.
Chunyu
C
Wang
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People's Republic of China. maozuguo@hit.edu.cn.
Maozu
M
Guo
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People's Republic of China.
Xiaoyan
X
Liu
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People's Republic of China.|Department of Information Management and Information System, Northeast Forestry University, Harbin, 150001, People's Republic of China.
Zhixia
Z
Teng
D000465:Algorithms; D015415:Biomarkers / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D063990:Gene Ontology; D023281:Genomics / Q000379:methods; D006801:Humans; D058977:Molecular Sequence Annotation; D011381:Programming Languages; D012660:Semantics
D015415:Biomarkers
Gene functional similarity; Gene ontology; Hash table