More Agility to Semantic Similarities Algorithm Implementations
GO Similarity Algorithms that compare gene ontology terms has become a popular area of research in bioinformatics. While the focus of the research is on the design and improvement of GO semantic similarity algorithms, there is still a need for implementation of such algorithms before they can be used to solve real problems. This can be very challenging given that the audiences usually come from a biologybackground and they are not programmers. A number of implementations exist for some wellestablished algorithms but these implementations are not generic enough to support any algorithm other than the ones they are designed for. The aim of this paper is to move the focus away from implementation, allowing researchers to focus on algorithms design and execution rather than implementation. This is achieved by an implementation approach capable of understanding and executing user defined GO semantic similarity algorithms. Question/Answers were used to for the definition of the user-defined algorithm. Additionally, this approach understands any direct acyclic digraph in an OBO like format and its annotations.
Go Similarity algorithms Gene ontology Semantic terms similarity Gene product semantic similarity
KonstantinosTsaramirsis
Computer Science, Facuhy of Science Royal Holloway, University of London,Egham, UK
国际会议
海口
英文
121-126
2011-02-22（万方平台首次上网日期，不代表论文的发表时间）