Protein De novo Sequencing

dc.contributor.advisorMa, Bin
dc.contributor.authorWang, Rong
dc.date.accessioned2016-05-13T14:42:59Z
dc.date.available2016-05-13T14:42:59Z
dc.date.issued2016-05-13
dc.date.submitted2016-05-03
dc.description.abstractIn the proteomic mass spectrometry field, peptide and protein identification can be classified into two categories: database search that relies on existing peptide and protein databases and de novo sequencing with no prior knowledge. There are many unknown protein sequences in nature, especially those proteins that play an vital role in drug development pipelines, such as monoclonal antibodies and venoms. To sequence these unknown proteins, de novo sequencing is a necessity. There have been standard algorithms for de novo sequencing a short peptide from its tandem mass spectrum (MS/MS). However, the de novo sequencing of a whole protein is still in its infancy. The most promising method is to digest the protein into overlapping short peptides with different enzymes. After each peptide is de novo sequenced with MS/MS, these overlapping peptides are then assembled together either manually or with a computer algorithm. Such an automated assembly algorithm becomes the main purpose of this thesis. Compared to the DNA sequence assembly counterpart, the main challenges are the high error rates and the short sequence length of each de novo peptide. To meet these challenges, novel scoring methods and algorithms are proposed and a software program is developed. The program is tested on a standard data set and demonstrates superior performance when compared to the state-of-the-art.en
dc.identifier.urihttp://hdl.handle.net/10012/10472
dc.language.isoenen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.subjectprotein de novo sequencingen
dc.subjectde novo peptideen
dc.titleProtein De novo Sequencingen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentDavid R. Cheriton School of Computer Scienceen
uws-etd.degree.disciplineComputer Scienceen
uws-etd.degree.grantorUniversity of Waterlooen
uws.contributor.advisorMa, Bin
uws.contributor.affiliation1Faculty of Mathematicsen
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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