Predicting the Types of Ion Channel-Targeted Conotoxins Based on AVC-SVM Model.
The conotoxin proteins are disulfide-rich small peptides. Predicting the types of ion channel-targeted conotoxins has great value in the treatment of chronic diseases, epilepsy, and cardiovascular diseases. To solve the problem of information redundancy existing when using current methods, a new mod...
| Publicado en: | BioMed Research International Vol. 2017; pp. 1 - 9 |
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| Autores principales: | , , , |
| Formato: | equations & formulas tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
4/9/2017
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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=122385382&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122385382 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 4/9/2017 vid: 2017 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 122385382 122385382 122385382 10.1155/2017/2929807 122385382 ppf: 1 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Predicting the Types of Ion Channel-Targeted Conotoxins Based on AVC-SVM Model. aug: au: Xianfang, Wang Junmei, Wang Xiaolei, Wang Yue, Zhang affil: School of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China sug: subj: Ion Channels Models, Biological Marine Toxins Human Pearson's Correlation Coefficient Analysis of Variance Experimental Studies ab: The conotoxin proteins are disulfide-rich small peptides. Predicting the types of ion channel-targeted conotoxins has great value in the treatment of chronic diseases, epilepsy, and cardiovascular diseases. To solve the problem of information redundancy existing when using current methods, a new model is presented to predict the types of ion channel-targeted conotoxins based on AVC (Analysis of Variance and Correlation) and SVM (Support Vector Machine). First, the F value is used to measure the significance level of the feature for the result, and the attribute with smaller F value is filtered by rough selection. Secondly, redundancy degree is calculated by Pearson Correlation Coefficient. And the threshold is set to filter attributes with weak independence to get the result of the refinement. Finally, SVM is used to predict the types of ion channel-targeted conotoxins. The experimental results show the proposed AVC-SVM model reaches an overall accuracy of 91.98%, an average accuracy of 92.17%, and the total number of parameters of 68. The proposed model provides highly useful information for further experimental research. The prediction model will be accessed free of charge at our web server. pubtype: Academic Journal doctype: equations & formulas tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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