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Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledege discovery

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dc.contributor.advisor Reboiro Jato, Miguel
dc.contributor.advisor Gonzalez Peña, Daniel
dc.contributor.author López Fernández, Hugo
dc.date.accessioned 2017-03-08T13:10:33Z
dc.date.available 2017-03-08T13:10:33Z
dc.date.issued 2016-03-29
dc.date.submitted 2016-02-02
dc.identifier.uri http://hdl.handle.net/11093/625
dc.description.abstract Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS) has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI), machine learning (ML), and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community. spa
dc.description.sponsorship Ministerio de Ciencia e Innovación | Ref. TIN2009-14057-C03-02 spa
dc.description.sponsorship Ministerio de Ciencia e Innovación | Ref. AIB2010PT-00353 spa
dc.description.sponsorship Universidade de Vigo | Ref. 15VI013 spa
dc.description.sponsorship Universidade de Vigo | Ref. 08VIB6 spa
dc.description.sponsorship Concello de Ourense | Ref. INOU-14-08 spa
dc.language.iso eng spa
dc.rights Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.title Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledege discovery spa
dc.type doctoralThesis spa
dc.rights.accessRights openAccess spa
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/316265 spa
dc.publisher.departamento Informática spa
dc.publisher.grupoinvestigacion Sistemas Informáticos de Nova Xeración spa
dc.publisher.programadoc Programa Oficial de Doutoramento en Sistemas Software Intelixentes e Adaptables (RD 1393/2007)
dc.subject.unesco 1203.17 Informática spa
dc.subject.unesco 1203.04 Inteligencia Artificial spa
dc.date.read 2016-03-29
dc.date.updated 2017-03-08T09:30:23Z
dc.advisorID 5926
dc.advisorID 5044


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