DocumentCode :
464293
Title :
Semantic Analysis of Genome Annotations using Weighting Schemes
Author :
Done, Bogdan ; Khatri, Purvesh ; Done, Arina ; Draghici, Sorin
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI
fYear :
2007
fDate :
1-5 April 2007
Firstpage :
212
Lastpage :
218
Abstract :
The correct interpretation of many molecular biology experiments depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are meant to act as repositories for our biological knowledge as we acquire and refine it. Hence, by definition they are incomplete at any given time. In this paper we describe a technique that improves our previous method for extracting implicit semantic relationships between genes and functions. We added a number of weighting schemes to our previous latent semantic indexing approach. We used this technique to analyze the current annotations of the human genome. The predictions of 15 different weighting schemes were compared and evaluated. Out of the top 50 functional annotations predicted using the best performing weighting scheme, we found support in the literature for 82% of them. For 10% of our prediction we did not find any relevant publications, and 6% were actually contradicted by existing literature. This weighting scheme also outperformed the simple binary scheme used in our previous approach. Our method is independent of the organism and can be used to analyze and improve the quality of the data of any public or private annotation database
Keywords :
biology computing; genetics; information analysis; annotation databases; biological knowledge; genome annotations; implicit semantic relationships; molecular biology; semantic analysis; weighting schemes; Bioinformatics; Biological processes; Computational biology; Computational intelligence; Databases; Genomics; Humans; Indexing; Ontologies; Organisms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0710-9
Type :
conf
DOI :
10.1109/CIBCB.2007.4221226
Filename :
4221226
Link To Document :
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