De Novo Markup Language, a Standard To Represent De Novo Sequencing Results From Ms/Ms Data

dc.contributor.author Takan, Savaş
dc.contributor.author Allmer, Jens
dc.coverage.doi 10.1109/HIBIT.2012.6209038
dc.date.accessioned 2017-03-14T10:16:30Z
dc.date.available 2017-03-14T10:16:30Z
dc.date.issued 2012
dc.description 7th International Symposium on Health Informatics and Bioinformatics, HIBIT 2012; Cappadocia; Turkey; 19 April 2012 through 22 April 2012 en_US
dc.description.abstract Proteomics is the study of the proteins that can be derived from a genome. For the identification and sequencing of proteins, mass spectrometry has become the tool of choice. Within mass spectrometry-based proteomics, proteins can be identified or sequenced by either database search or de novo sequencing. Both methods have certain advantages and drawbacks but in the long run we envision de novo sequencing to become the predominant tool. Currently, de novo sequencing results are stored in arbitrary file formats, depending on the developers of the algorithms. We identified this as a large and unnecessary obstacle while integrating results from multiple de novo sequencing algorithms. Therefore, we designed a standard file format for the representation of de novo sequencing results. We further developed an application programming interface since we identified the lack of proper APIs as another obstacle, introducing a needlessly high learning curve for developers. © 2012 IEEE. en_US
dc.description.sponsorship Turkish Academy of Sciences en_US
dc.identifier.citation Takan, S., and Allmer, J. (2012, April 19-22). De novo markup language, a standard to represent de novo sequencing results from MS/MS data. Paper presented at the 7th International Symposium on Health Informatics and Bioinformatics, HIBIT 2012. doi:10.1109/HIBIT.2012.6209038 en_US
dc.identifier.doi 10.1109/HIBIT.2012.6209038 en_US
dc.identifier.doi 10.1109/HIBIT.2012.6209038
dc.identifier.isbn 9781467308786
dc.identifier.scopus 2-s2.0-84862729441
dc.identifier.uri http://doi.org/10.1109/HIBIT.2012.6209038
dc.identifier.uri https://hdl.handle.net/11147/5047
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof 7th International Symposium on Health Informatics and Bioinformatics, HIBIT 2012 en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Database searches en_US
dc.subject De novo sequencing en_US
dc.subject Learning curves en_US
dc.subject Proteins en_US
dc.subject Proteomics en_US
dc.title De Novo Markup Language, a Standard To Represent De Novo Sequencing Results From Ms/Ms Data en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.institutional Takan, Savaş
gdc.author.institutional Allmer, Jens
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gdc.coar.access open access
gdc.coar.type text::conference output
gdc.collaboration.industrial false
gdc.description.department İzmir Institute of Technology. Computer Engineering en_US
gdc.description.endpage 36 en_US
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 31 en_US
gdc.description.wosquality N/A
gdc.identifier.openalex W2093275150
gdc.index.type Scopus
gdc.oaire.diamondjournal false
gdc.oaire.impulse 0.0
gdc.oaire.influence 2.635068E-9
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gdc.oaire.keywords Proteomics
gdc.oaire.keywords Proteins
gdc.oaire.keywords Learning curves
gdc.oaire.keywords Database searches
gdc.oaire.keywords De novo sequencing
gdc.oaire.popularity 6.199582E-10
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0301 basic medicine
gdc.oaire.sciencefields 0303 health sciences
gdc.oaire.sciencefields 03 medical and health sciences
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