WIMMEROVÁ, Michaela, Soren B. ENGELSEN, Emmanuel BETTLER, Christelle BRETON and Anne IMBERTY. Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis. Biochimie. Elsevier, 2003, vol. 85, No 7, p. 691-700. ISSN 0300-9084.
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Basic information
Original name Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis
Authors WIMMEROVÁ, Michaela (203 Czech Republic, guarantor), Soren B. ENGELSEN (208 Denmark), Emmanuel BETTLER (250 France), Christelle BRETON (250 France) and Anne IMBERTY (250 France).
Edition Biochimie, Elsevier, 2003, 0300-9084.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10600 1.6 Biological sciences
Country of publisher Netherlands
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 3.707
RIV identification code RIV/00216224:14310/03:00008870
Organization unit Faculty of Science
UT WoS 000185771000009
Keywords in English Glycosyltransferase; Mycobacterium; Fold recognition; Chemometrics
Tags chemometrics, Fold recognition, glycosyltransferase, MYCOBACTERIUM
Tags International impact, Reviewed
Changed by Changed by: prof. RNDr. Michaela Wimmerová, Ph.D., učo 854. Changed: 4/1/2007 15:32.
Abstract
Fold recognition was applied to the systematic analysis of the all sequences encoded by the genome of Mycobacterium tuberculosis H37Rv in order to identify new putative glycosyltransferases. The search was conducted against a library composed of all known crystal structures of glycosyltransferases and some related proteins. A clear relationship appeared between some sequences and some folds. It appears necessary to complete the fold recognition approach with a statistical approach in order to identify the relevant data above the background noise. Exploratory data analysis was carried out using several methods. Analytical methods confirmed the validity of the approach, while predictive methods, although very preliminary in the present case, allowed for identifying a number of sequences of interest that should be further investigated. This new approach combining bioinformatics and chemometrics appears to be a powerful tool for analysis of newly sequenced genomes. Its application to glycobiology is of great interest.
Links
LN00A016, research and development projectName: BIOMOLEKULÁRNÍ CENTRUM
Investor: Ministry of Education, Youth and Sports of the CR, Biomolecular Center
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