Protein Function Prediction Using Deep Restricted Boltzmann Machines.
Accurately annotating biological functions of proteins is one of the key tasks in the postgenome era. Many machine learning based methods have been applied to predict functional annotations of proteins, but this task is rarely solved by deep learning techniques. Deep learning techniques recently hav...
| Publicado en: | BioMed Research International Vol. 2017; pp. 1 - 10 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
6/28/2017
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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=123822712&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 123822712 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 6/28/2017 vid: 2017 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 123822712 123822712 123822712 10.1155/2017/1729301 123822712 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Protein Function Prediction Using Deep Restricted Boltzmann Machines. aug: au: Zou, Xianchun Wang, Guijun Yu, Guoxian affil: College of Computer and Information Science, Southwest University, Chongqing, China sug: subj: Proteins Physiology Technology Genome Human Learning Neural Transmission Funding Source ab: Accurately annotating biological functions of proteins is one of the key tasks in the postgenome era. Many machine learning based methods have been applied to predict functional annotations of proteins, but this task is rarely solved by deep learning techniques. Deep learning techniques recently have been successfully applied to a wide range of problems, such as video, images, and nature language processing. Inspired by these successful applications, we investigate deep restricted Boltzmann machines (DRBM), a representative deep learning technique, to predict the missing functional annotations of partially annotated proteins. Experimental results on Homo sapiens, Saccharomyces cerevisiae, Mus musculus, and Drosophila show that DRBM achieves better performance than other related methods across different evaluation metrics, and it also runs faster than these comparing methods. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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