QuaBingo: A Prediction System for Protein Quaternary Structure Attributes Using Block Composition.
Background. Quaternary structures of proteins are closely relevant to gene regulation, signal transduction, and many other biological functions of proteins. In the current study, a new method based on protein-conserved motif composition in block format for feature extraction is proposed, which is te...
| Publicado en: | BioMed Research International Vol. 2016; pp. 1 - 11 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
8/17/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117506562&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117506562 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 8/17/2016 vid: 2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 117506562 117506562 117506562 10.1155/2016/9480276 117506562 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: QuaBingo: A Prediction System for Protein Quaternary Structure Attributes Using Block Composition. aug: au: Tung, Chi-Hua Chen, Chi-Wei Guo, Ren-Chao Ng, Hui-Fuang Chu, Yen-Wei affil: Department of Bioinformatics, Chung-Hua University, Room S116, No. 707, Section 2, WuFu Road, Hsinchu 30012, Taiwan sug: subj: Proteins Physiology Artificial Intelligence Validation Studies Correlation Coefficient Amino Acids Oligonucleotide Array Sequence Analysis Polymers Resource Databases kappa Statistic Algorithms Funding Source ab: Background. Quaternary structures of proteins are closely relevant to gene regulation, signal transduction, and many other biological functions of proteins. In the current study, a new method based on protein-conserved motif composition in block format for feature extraction is proposed, which is termed block composition. Results. The protein quaternary assembly states prediction system which combines blocks with functional domain composition, called QuaBingo, is constructed by three layers of classifiers that can categorize quaternary structural attributes of monomer, homooligomer, and heterooligomer. The building of the first layer classifier uses support vector machines (SVM) based on blocks and functional domains of proteins, and the second layer SVM was utilized to process the outputs of the first layer. Finally, the result is determined by the Random Forest of the third layer. We compared the effectiveness of the combination of block composition, functional domain composition, and pseudoamino acid composition of the model. In the 11 kinds of functional protein families, QuaBingo is 23% of Matthews Correlation Coefficient (MCC) higher than the existing prediction system. The results also revealed the biological characterization of the top five block compositions. Conclusions. QuaBingo provides better predictive ability for predicting the quaternary structural attributes of proteins. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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