Using data compression for multidimensional distribution analysis [molecular biology]

Author

Onizuka, Kentaro ; Noguchi, Tamotsu ; Akiyama, Yutaka ; Matsuda, Hideo

Author_Institution

Adv. Technol. Res. Labs., Matsushita Electr. Ind. Co. Ltd., Kyoto, Japan

Volume

17

Issue

3

fYear

2002

Firstpage

48

Lastpage

54

Abstract

A new method for multi-dimensional distribution analysis using a data compression technique applied to the knowledge-based mean-force potentials between residues for the analysis of protein sequence-structure compatibility performs much better than that of conventional 1D distance-based potentials derived from binned distributions.

Keywords

biology computing; computer aided analysis; data analysis; data compression; knowledge based systems; molecular biophysics; molecular configurations; physics computing; potential energy functions; proteins; sequences; binned distributions; data compression; distance-based potentials; intelligent systems; knowledge-based mean-force potentials; molecular biology; multi-dimensional distribution analysis; protein residues; protein sequence-structure compatibility; Aerospace industry; Computer industry; Data compression; Histograms; Image analysis; Image coding; Image sequence analysis; Multidimensional systems; Proteins; Space technology;

fLanguage

English

Journal_Title

Intelligent Systems, IEEE

Publisher

ieee

ISSN

1541-1672

Type

jour

DOI

10.1109/MIS.2002.1005631

Filename

1005631