Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models.

Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models. Research Abstract Details 

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Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models. Abstract Text:

Zhimeng Wang,Lin Jiang,Menglong Li,Lina Sun,Rongying Lin,Zhimeng Wang,Lin Jiang,Menglong Li,Lina Sun,Rongying Lin,

There are approximately 10(9) proteins in a cell. A hotspot in bioinformatics is how to identify a protein subcellular localization, if its sequence is known. In this paper, a method using fast Fourier transform-based support vector machine is developed to predict the subcellular localization of proteins from their physicochemical properties and structural parameters. The prediction accuracies reached 83% in prokaryotic organisms and 84% in eukaryotic organisms with the substitution model of the c-p-v matrix (c, composition; p, polarity; and v, molecular volume). The overall prediction accuracy was also evaluated using the "leave-one-out" jackknife procedure. The influence of the substitution model on prediction accuracy has also been discussed in the work. The source code of the new program is available on request from the authors.

Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models. Publishing Authors By Initials

Z Wang,L Jiang,M Li,L Sun,R Lin,Z Wang,L Jiang,M Li,L Sun,R Lin,

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Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Acta biochimica et biophysica Sinica

VOLUME: 39

Page Numbers: 715-21

Journal Abbreviation: Acta Biochim. Biophys. Sin. (S

ISSN: 1672-9145

DAY: 6

MONTH: Sep

YEAR: 2007

Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models. Information

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LANGUAGE: eng

NlmUniqueID: 101206716

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Grant and Affiliation Information for Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models.

AFFILIATION: College of Chemistry, Sichuan University, Chengdu 610064, China.

Country: China

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MEDLINETA: Acta Biochim Biophys Sin (Shan

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