Predicting promoters by pseudo-trinucleotide compositions based on discrete wavelets transform

DOI10.1016/j.jtbi.2012.11.024zbMath1406.92480OpenAlexW1970993738WikidataQ48042659 ScholiaQ48042659MaRDI QIDQ1715130

Zong Dai, Xuan Zhou, Zhan-Chao Li, Xiao-Yong Zou

Publication date: 4 February 2019

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

Full work available at URL: https://doi.org/10.1016/j.jtbi.2012.11.024

zbMATH Keywords

support vector machinesprediction accuracyDNA sequence representation

Mathematics Subject Classification ID

Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Learning and adaptive systems in artificial intelligence (68T05) Protein sequences, DNA sequences (92D20) Genetics and epigenetics (92D10)

Uses Software

• LIBSVM
• Cell-PLoc
• ProSOM
• N-SCAN
• PseAAC-Builder
• iLoc-Hum
• iLoc-Euk
• OligoPred
• BacPP
• PromoterExplorer

Cites Work

• Unnamed Item
• Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices
• Some remarks on protein attribute prediction and pseudo amino acid composition
• BacPP: bacterial promoter prediction -- a tool for accurate sigma-factor specific assignment in enterobacteria
• Convergence analysis and error estimate of finite element method of a nonlinear fluid-structure interaction problem

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