Document Detail


Detection of influent virulence and resistance genes in microarray data through quasi likelihood modeling.
MedLine Citation:
PMID:  23296985     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Publicly available genomic data are a great source of biological knowledge that can be extracted when appropriate data analysis is used. Predicting the biological function of genes is of interest to understand molecular mechanisms of virulence and resistance in pathogens and hosts and is important for drug discovery and disease control. This is commonly done by searching for similar gene expression behavior. Here, we used publicly available Streptococcus pyogenes microarray data obtained during primate infection to identify genes that have a potential influence on virulence and Phytophtora infestance inoculated tomato microarray data to identify genes potentially implicated in resistance processes. This approach goes beyond co-expression analysis. We employed a quasi-likelihood model separated by primate gender/inoculation condition to model median gene expression of known virulence/resistance factors. Based on this model, an influence analysis considering time course measurement was performed to detect genes with atypical expression. This procedure allowed for the detection of genes potentially implicated in the infection process. Finally, we discuss the biological meaning of these results, showing that influence analysis is an efficient and useful alternative for functional gene prediction.
Authors:
José S Romeo; Francisco Torres-Avilés; Liliana López-Kleine
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-8
Journal Detail:
Title:  Molecular genetics and genomics : MGG     Volume:  -     ISSN:  1617-4623     ISO Abbreviation:  Mol. Genet. Genomics     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101093320     Medline TA:  Mol Genet Genomics     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Departamento de Matemática y Ciencia de la Computación, Universidad de Santiago de Chile, Santiago, Chile.
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