Method for rapid protein identification in a large database.
Protein identification is an integral part of proteomics research. The available tools to identify proteins in tandem mass spectrometry experiments are not optimized to face current challenges in terms of identification scale and speed owing to the exponential growth of the protein database and the...
| Publicado en: | BioMed Research International Vol. 2013; pp. 414069 - 414070 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
2013
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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=104092201&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104092201 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 2013 vid: 2013 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104092201 2012245718 NLM24000323 PMC3755435 104092201 ppf: 414069 ppct: 1 formats: fmt: @attributes: type: P tig: atl: Method for rapid protein identification in a large database. aug: au: Zhang, Wenli Zhao, Xiaofang affil: Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China ; State Key Laboratory of Computer Architecture, ICT, CAS, Beijing 100190, China ; Graduate University of Chinese Academy of Sciences, Beijing 100049, China. sug: subj: Algorithms Data Mining Methods Management Information Systems Resource Databases Proteins Genetic Techniques Methods Sequence Analysis Methods Amino Acids Documentation ab: Protein identification is an integral part of proteomics research. The available tools to identify proteins in tandem mass spectrometry experiments are not optimized to face current challenges in terms of identification scale and speed owing to the exponential growth of the protein database and the accelerated generation of mass spectrometry data, as well as the demand for nonspecific digestion and post-modifications in complex-sample identification. As a result, a rapid method is required to mitigate such complexity and computation challenges. This paper thus aims to present an open method to prevent enzyme and modification specificity on a large database. This paper designed and developed a distributed program to facilitate application to computer resources. With this optimization, nearly linear speedup and real-time support are achieved on a large database with nonspecific digestion, thus enabling testing with two classical large protein databases in a 20-blade cluster. This work aids in the discovery of more significant biological results, such as modification sites, and enables the identification of more complex samples, such as metaproteomics samples. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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