Prediction of apoptosis protein subcellular location based on position-specific scoring matrix and isometric mapping algorithm.
Apoptosis proteins are related to many diseases. Obtaining the subcellular localization information of apoptosis proteins is helpful to understand the mechanism of diseases and to develop new drugs. At present, the researchers mainly focus on the primary protein sequences, so there is still room for...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 57; no. 12; pp. 2553 - 2566 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2019
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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=140034786&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 140034786 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Dec2019 vid: 57 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 140034786 140034786 NLM31621050 10.1007/s11517-019-02045-3 NLM31621050 140034786 ppf: 2553 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prediction of apoptosis protein subcellular location based on position-specific scoring matrix and isometric mapping algorithm. aug: au: Ruan, Xiaoli Zhou, Dongming Nie, Rencan Hou, Ruichao Cao, Zicheng affil: Information College, Yunnan University, 650504, Kunming, China sug: subj: Apoptosis Physiology Proteins Metabolism Sequence Analysis Algorithms Bioinformatics Methods Scales ab: Apoptosis proteins are related to many diseases. Obtaining the subcellular localization information of apoptosis proteins is helpful to understand the mechanism of diseases and to develop new drugs. At present, the researchers mainly focus on the primary protein sequences, so there is still room for improvement in the prediction accuracy of the subcellular localization of apoptosis proteins. In this paper, a new method named ERT-ECT-PSSM-IS is proposed to predict apoptosis proteins based on the position-specific scoring matrix (PSSM). First, the local and global features of different directions are extracted by evolutionary row transformation (ERT) and cross-covariance of evolutionary column transformation (ECT) based on PSSM (ERT-ECT-PSSM). Second, an improved isometric mapping algorithm (I-SMA) is used to eliminate redundant features. Finally, we adopt a support vector machine (SVM) to classify our results, and the prediction accuracy is evaluated by jackknife cross-validation tests. The experimental results show that the proposed method not only extracts more abundant feature expression but also has better predictive performance and robustness for the subcellular localization of apoptosis proteins in ZD98, ZW225, and CL317 databases. Graphical abstract Framework of the proposed prediction model. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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