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Detecting Protein Variants within Ma...

University of Toronto (Canada).

Detecting Protein Variants within Mass Spectrometry Datasets.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Detecting Protein Variants within Mass Spectrometry Datasets./
作者:	Alfaro, Javier Antonio.
面頁冊數:	1 online resource (113 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Contained By:	Dissertation Abstracts International79-08B(E).
標題:	Bioinformatics. -
電子資源:	click for full text (PQDT)
ISBN:	9780355813449

Detecting Protein Variants within Mass Spectrometry Datasets.
Alfaro, Javier Antonio.

Detecting Protein Variants within Mass Spectrometry Datasets. - 1 online resource (113 pages)

Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.

Thesis (Ph.D.)--University of Toronto (Canada), 2018.

Includes bibliographical references

An important aim of cancer proteomics is to understand how the cancer proteome, with all its variation in both protein sequence and protein abundance, emerges from aberrations characterized within cancer genomic and transcriptomic datasets. A challenge in reaching this goal is that standard mass-spectrometry-based onco-proteomic strategies typically ignore variations in protein sequences, instead characterizing cancer proteomes in terms of changing abundances of standard reference proteins. In this thesis, I assess strategies for incorporating information about protein sequence variation within standard proteomics analysis strategies. I develop a pipeline for the characterization of variations within protein sequences and assess the best methodology to do so.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355813449Subjects--Topical Terms:

583857
Bioinformatics.
Index Terms--Genre/Form:

554714
Electronic books.

Detecting Protein Variants within Mass Spectrometry Datasets.
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500 $a Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
500 $a Includes supplementary digital materials.
500 $a Advisers: Thomas Kislinger; Paul C. Boutros.
502 $a Thesis (Ph.D.)--University of Toronto (Canada), 2018.
504 $a Includes bibliographical references
520 $a An important aim of cancer proteomics is to understand how the cancer proteome, with all its variation in both protein sequence and protein abundance, emerges from aberrations characterized within cancer genomic and transcriptomic datasets. A challenge in reaching this goal is that standard mass-spectrometry-based onco-proteomic strategies typically ignore variations in protein sequences, instead characterizing cancer proteomes in terms of changing abundances of standard reference proteins. In this thesis, I assess strategies for incorporating information about protein sequence variation within standard proteomics analysis strategies. I develop a pipeline for the characterization of variations within protein sequences and assess the best methodology to do so.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Bioinformatics. $3 583857
650 4 $a Biophysics. $3 581576
650 4 $a Biochemistry. $3 582831
655 7 $a Electronic books. $2 local $3 554714
690 $a 0715
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710 2 $a University of Toronto (Canada). $b Medical Biophysics. $3 1184111
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10681585 $z click for full text (PQDT)

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