DocumentCode
2093756
Title
Operon prediction based on quadratic discriminant analysis in Escherichia coli genome
Author
Ji, Meizhen ; Lu, Jun ; Zhang, Ying ; Ding, Changjiang ; Qin, Dandan ; Bai, Haiyan
Author_Institution
College of Science, Inner Mongolia University of Technology, Hohhot, 010051, China
fYear
2010
fDate
4-6 Dec. 2010
Firstpage
376
Lastpage
379
Abstract
The operon is a specific functional organization of genes found in bacterial genomes. It plays an important role in constructing the genetic regulation network. Genes within most operons have more common structures and functional characteristics. These common features become the basis of operon prediction. Annotation of operons in a bacterial genome is an important step in determining an organism´s transcriptional regulatory program. Quadratic discriminant analysis (QDA) approach is here used to predict Escherichia coli k12 (E.coli) operons. Three features were chosen as QDA input vectors, 1)intergenic distance, 2)the common gene ontology(GO) annotation numbers of a gene pair, 3) statistical correlation of a gene pair based on sequence. Our study show that i) intergenic distance and the common GO annotation numbers of a gene pair are very important for the operons prediction, ii) the correlation information of a gene pair based on sequence is a good supplement for the operons prediction when GO annotation lose. The prediction using statistical correlation of a gene pair is a new thought. Based on these new insights, for E.coli on our own dataset our operon prediction program obtain the prediction sensitivity, specificity, accuracy, auROC at 91.5%, 85.2%, 88.4%, 0.9317, respectively. On dataset of Taboada etc it is 94.9%, 92.2%, 93.7%, 0.9582, respectively. This result is superior to that based on intergenic distance and STRING-like scores of Taboada and colleagues.
Keywords
Accuracy; Bioinformatics; Correlation; Genomics; Hidden Markov models; Microorganisms; Proteins; intergenic distance; operon; statistical correlation of sequence;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location
Hangzhou, China
Print_ISBN
978-1-4244-7616-9
Type
conf
DOI
10.1109/ICISE.2010.5689023
Filename
5689023
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