Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107007
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical and Electronic Engineering | - |
dc.creator | Wan, S | en_US |
dc.creator | Mak, MW | en_US |
dc.creator | Kung, SY | en_US |
dc.date.accessioned | 2024-06-07T00:59:35Z | - |
dc.date.available | 2024-06-07T00:59:35Z | - |
dc.identifier.issn | 0022-5193 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/107007 | - |
dc.language.iso | en | en_US |
dc.publisher | Academic Press | en_US |
dc.rights | © 2016 Elsevier Ltd. All rights reserved. | en_US |
dc.rights | © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.rights | The following publication Wan, S., Mak, M. W., & Kung, S. Y. (2016). Mem-ADSVM: A two-layer multi-label predictor for identifying multi-functional types of membrane proteins. Journal of theoretical biology, 398, 32-42 is available at https://doi.org/10.1016/j.jtbi.2016.03.013. | en_US |
dc.subject | Adaptive-decision scheme | en_US |
dc.subject | Gene ontology | en_US |
dc.subject | Membrane protein type prediction | en_US |
dc.subject | Multi-label classification | en_US |
dc.subject | Two-layer classification | en_US |
dc.title | Mem-ADSVM : a two-layer multi-label predictor for identifying multi-functional types of membrane proteins | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 32 | en_US |
dc.identifier.epage | 42 | en_US |
dc.identifier.volume | 398 | en_US |
dc.identifier.doi | 10.1016/j.jtbi.2016.03.013 | en_US |
dcterms.abstract | Identifying membrane proteins and their multi-functional types is an indispensable yet challenging topic in proteomics and bioinformatics. However, most of the existing membrane-protein predictors have the following problems: (1) they do not predict whether a given protein is a membrane protein or not; (2) they are limited to predicting membrane proteins with single-label functional types but ignore those with multi-functional types; and (3) there is still much room for improvement for their performance. To address these problems, this paper proposes a two-layer multi-label predictor, namely Mem-ADSVM, which can identify membrane proteins (Layer I) and their multi-functional types (Layer II). Specifically, given a query protein, its associated gene ontology (GO) information is retrieved by searching a compact GO-term database with its homologous accession number. Subsequently, the GO information is classified by a binary support vector machine (SVM) classifier to determine whether it is a membrane protein or not. If yes, it will be further classified by a multi-label multi-class SVM classifier equipped with an adaptive-decision (AD) scheme to determine to which functional type(s) it belongs. Experimental results show that Mem-ADSVM significantly outperforms state-of-the-art predictors in terms of identifying both membrane proteins and their multi-functional types. This paper also suggests that the two-layer prediction architecture is better than the one-layer for prediction performance. For reader׳s convenience, the Mem-ADSVM server is available online at http://bioinfo.eie.polyu.edu.hk/MemADSVMServer/. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of theoretical biology, 7 June 2016, v. 398, p. 32-42 | en_US |
dcterms.isPartOf | Journal of theoretical biology | en_US |
dcterms.issued | 2016-06-07 | - |
dc.identifier.scopus | 2-s2.0-84961844202 | - |
dc.identifier.eissn | 1095-8541 | en_US |
dc.description.validate | 202405 bcch | - |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | EIE-0856 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6629908 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Mak_Mem-Adsvm_Two-Layer_Multi-Label.pdf | Pre-Published version | 1.88 MB | Adobe PDF | View/Open |
Page views
6
Citations as of Jun 30, 2024
Downloads
4
Citations as of Jun 30, 2024
SCOPUSTM
Citations
26
Citations as of Jun 21, 2024
WEB OF SCIENCETM
Citations
24
Citations as of Jun 27, 2024
![](/image/google_scholar.jpg)
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.