PseAAC-General: Fast Building Various Modes of General Form of Chou's Pseudo-Amino Acid Composition for Large-Scale Protein Datasets

Pufeng Du; Shuwang Gu; Yasen Jiao

doi:10.3390/ijms15033495

PseAAC-General: Fast Building Various Modes of General Form of Chou's Pseudo-Amino Acid Composition for Large-Scale Protein Datasets

Pufeng Du^*, Shuwang Gu, Yasen Jiao

^*Corresponding author for this work

Department of Computer Science

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

255 Citations (Scopus)

63 Downloads (CityUHK Scholars)

Abstract

The general form pseudo-amino acid composition (PseAAC) has been widely used to represent protein sequences in predicting protein structural and functional attributes. We developed the program PseAAC-General to generate various different modes of Chou's general PseAAC, such as the gene ontology mode, the functional domain mode, and the sequential evolution mode. This program allows the users to define their own desired modes. In every mode, 544 physicochemical properties of the amino acids are available for choosing. The computing efficiency is at least 100 times that of existing programs, which makes it able to facilitate the extensive studies on proteins and peptides. The PseAAC-General is freely available via SourceForge. It runs on both Linux and Windows.

Original language	English
Pages (from-to)	3495-3506
Number of pages	12
Journal	International Journal of Molecular Sciences
Volume	15
Issue number	3
Online published	26 Feb 2014
DOIs	https://doi.org/10.3390/ijms15033495
Publication status	Published - Mar 2014

Funding

This work was supported by National Science Foundation of China (NSFC 61005041); Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP 20100032120039); Tianjin Natural Science Foundation (No. 12JCQNJC02300); China Post-doctoral Science Foundation (2012T50240 and 2013M530114); HK Scholar Program (XJ2012033) and the Seed Foundation of Tianjin University (No. 60302006 and 60302024).

Research Keywords

general form
large-scale datasets
pseudo-amino acid composition
DISCRETE WAVELET TRANSFORM
SUPPORT VECTOR MACHINE
PREDICTING SUBCELLULAR-LOCALIZATION
ENZYME SUBFAMILY CLASSES
COUPLED RECEPTOR CLASSES
OUTER-MEMBRANE PROTEINS
STRUCTURAL CLASS
MULTIPLE SITES
APPROXIMATE ENTROPY
WEB-SERVER

Publisher's Copyright Statement

This full text is made available under CC-BY 3.0. https://creativecommons.org/licenses/by/3.0/

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abstract = "The general form pseudo-amino acid composition (PseAAC) has been widely used to represent protein sequences in predicting protein structural and functional attributes. We developed the program PseAAC-General to generate various different modes of Chou's general PseAAC, such as the gene ontology mode, the functional domain mode, and the sequential evolution mode. This program allows the users to define their own desired modes. In every mode, 544 physicochemical properties of the amino acids are available for choosing. The computing efficiency is at least 100 times that of existing programs, which makes it able to facilitate the extensive studies on proteins and peptides. The PseAAC-General is freely available via SourceForge. It runs on both Linux and Windows.",

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PseAAC-General: Fast Building Various Modes of General Form of Chou's Pseudo-Amino Acid Composition for Large-Scale Protein Datasets. / Du, Pufeng; Gu, Shuwang; Jiao, Yasen.
In: International Journal of Molecular Sciences, Vol. 15, No. 3, 03.2014, p. 3495-3506.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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PseAAC-General: Fast Building Various Modes of General Form of Chou's Pseudo-Amino Acid Composition for Large-Scale Protein Datasets

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