Intelligence Algorithms for Protein Classification by Mass Spectrometry.
Mass spectrometry (MS) is an important technique in protein research. Effective classification methods by MS data could contribute to early and less-invasive diagnosis and also facilitate developments in the bioinformatics field. As MS data is featured by high dimension, appropriate methods which ca...
| Published in: | BioMed Research International pp. 1 - 12 |
|---|---|
| Main Authors: | , , , , |
| Format: | review tables/charts Journal Article |
| Published: |
Wiley-Blackwell
11/11/2018
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132934824&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132934824 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 11/11/2018 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 132934824 132934824 132934824 10.1155/2018/2862458 132934824 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Intelligence Algorithms for Protein Classification by Mass Spectrometry. aug: au: Fan, Zichuan Kong, Fanchen Zhou, Yang Chen, Yiqing Dai, Yalan affil: School of Computer and Information Science, Southwest University, Chongqing 400715, China sug: subj: Proteins Classification Mass Spectrometry Methods Algorithms Bioinformatics Biological Markers Machine Learning ab: Mass spectrometry (MS) is an important technique in protein research. Effective classification methods by MS data could contribute to early and less-invasive diagnosis and also facilitate developments in the bioinformatics field. As MS data is featured by high dimension, appropriate methods which can effectively deal with the large amount of MS data have been widely studied. In this paper, the applications of methods based on intelligence algorithms have been investigated. Firstly, classification and biomarker analysis methods using typical machine learning approaches have been discussed. Then those are followed by the Ensemble strategy algorithms. Clearly, simple and basic machine learning algorithms hardly addressed the various needs of protein MS classification. Preprocessing algorithms have been also studied, as these methods are useful for feature selection or feature extraction to improve classification performance. Protein MS data growing with data volume becomes complicated and large; improvements in classification methods in terms of classifier selection and combinations of different algorithms and preprocessing algorithms are more emphasized in further work. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|