Protein functional class prediction using global encoding of amino acid sequence

DOI10.1016/j.jtbi.2009.07.017zbMath1403.92212OpenAlexW2068922715WikidataQ45963564 ScholiaQ45963564MaRDI QIDQ1628865

Yu Shu, Xi Li, Qingguang Zeng, Bo Liao, Jia-wei Luo

Publication date: 11 December 2018

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

Full work available at URL: https://doi.org/10.1016/j.jtbi.2009.07.017

zbMATH Keywords

nearest neighbor algorithmglobal encodingphysiochemical propertyprotein functional class prediction

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10) Protein sequences, DNA sequences (92D20)

Related Items (4)

Alignment free comparison: similarity distribution between the DNA primary sequences based on the shortest absent word ⋮ Robust feature generation for protein subchloroplast location prediction with a weighted GO transfer model ⋮ High performance set of PseAAC and sequence based descriptors for protein classification ⋮ A 3D graphical representation of protein sequences based on the Gray code

Uses Software

• MARCH-INSIDE
• SVM-Prot

Cites Work

• Unnamed Item
• Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices
• Multi-target QPDR classification model for human breast and colon cancer-related proteins using star graph topological indices
• SVM-Prot

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