Using support vector machines to distinguish enzymes: approached by incorporating wavelet transform

DOI10.1016/J.JTBI.2008.10.026zbMath1400.92411OpenAlexW1970898136WikidataQ51861300 ScholiaQ51861300MaRDI QIDQ1617442

Ru-Ping Liang, San-Hua Luo, Jian-Ding Qiu, Jian Hua Huang

Publication date: 8 November 2018

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2008.10.026

zbMATH Keywords

waveletbioinformaticssupport vector machineenzyme structureamino acid hydrophobicity

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Learning and adaptive systems in artificial intelligence (68T05) Protein sequences, DNA sequences (92D20)

Cites Work

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• Predicting enzyme family classes by hybridizing gene product composition and pseudo-amino acid composition
• Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes
• ECS: an automatic enzyme classifier based on functional domain composition
• Ten Lectures on Wavelets
• Multiresolution Approximations and Wavelet Orthonormal Bases of L 2 (R)

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