Sorana D. BOLBOACA (2007) Applied Statistics (Time Series, Principal Component Analysis) - Collagen

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Applied Statistics (Time Series, Principal Component Analysis) - Collagen - Structure-Properties Characterization

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CONTRIBUTORS:

	Principal Investigator:	Sorana D. BOLBOACA (Iuliu Hatieganu University of Medicine and Pharmacy Cluj-Napoca)
	Co-investigator:	Lorentz JÄNTSCHI (Technical University of Cluj-Napoca)

FUNDED BY:

CNCSIS

GRANT PROGRAM:

YEARS:

2007 - 2008

PUB TYPE:

Grant (ID: 93)

GRANT AMOUNT:

74,900 Dollars (United States of America)

SUBJECT(S):

Collagen; Aminoacids; Molecular Biology; Time Series; Principal Component Analysis

HTTP:

PUB ID:

103-436-550 (Last edited on 2007/07/18 09:36:56 GMT-6)

SUMMARY:
The project entitled APPLIED STATISTICS (TIME SERIES, PRINCIPAL COMPONENT ANALYSIS) - COLLAGEN - STRUCTURE PROPERTIES CHARACTERIZATION propose the integration of knowwledge results from the periodicity/cyclical analysis of amino-acids from the protein chains of collagen type I and respectively of knowledge results from principal component analysis into mathematical models. The mathematical models will be develop based on the results ontained through principal component analysis and time series analysis applied on collagen type I. The properties of amino-acids from the composition of collagen type I will be study by the use of Molecular Descriptors Family approach, an original methodology which proved its abilities in estimation and prectiction of properties and activities of biological active compounds. Web implementation propose the integration of results obtained from the study of amino-acids and collagen type I through modles translation into online applications and online publication of reseach results: knowledge databases of amino-acids and collagen type I, mathematical models obtained through analysis of periodicity/cyclical arrangements of amino-acids into the structure of collagen type I and principal component analysis applied on collagen type one, modlecular descriptors, and models able to charcaterize the relationships between structure and properties.

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