دورية أكاديمية

mzStudio: A Dynamic Digital Canvas for User-Driven Interrogation of Mass Spectrometry Data

التفاصيل البيبلوغرافية
العنوان: mzStudio: A Dynamic Digital Canvas for User-Driven Interrogation of Mass Spectrometry Data
المؤلفون: Scott B. Ficarro, William M. Alexander, Jarrod A. Marto
المصدر: Proteomes, Vol 5, Iss 3, p 20 (2017)
بيانات النشر: MDPI AG, 2017.
سنة النشر: 2017
المجموعة: LCC:Microbiology
مصطلحات موضوعية: bioinformatics software, mass spectrometry, quantification, results distribution, API, application programming interface, SQLite, Microbiology, QR1-502
الوصف: Although not yet truly ‘comprehensive’, modern mass spectrometry-based experiments can generate quantitative data for a meaningful fraction of the human proteome. Importantly for large-scale protein expression analysis, robust data pipelines are in place for identification of un-modified peptide sequences and aggregation of these data to protein-level quantification. However, interoperable software tools that enable scientists to computationally explore and document novel hypotheses for peptide sequence, modification status, or fragmentation behavior are not well-developed. Here, we introduce mzStudio, an open-source Python module built on our multiplierz project. This desktop application provides a highly-interactive graphical user interface (GUI) through which scientists can examine and annotate spectral features, re-search existing PSMs to test different modifications or new spectral matching algorithms, share results with colleagues, integrate other domain-specific software tools, and finally create publication-quality graphics. mzStudio leverages our common application programming interface (mzAPI) for access to native data files from multiple instrument platforms, including ion trap, quadrupole time-of-flight, Orbitrap, matrix-assisted laser desorption ionization, and triple quadrupole mass spectrometers and is compatible with several popular search engines including Mascot, Proteome Discoverer, X!Tandem, and Comet. The mzStudio toolkit enables researchers to create a digital provenance of data analytics and other evidence that support specific peptide sequence assignments.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2227-7382
العلاقة: https://www.mdpi.com/2227-7382/5/3/20Test; https://doaj.org/toc/2227-7382Test
DOI: 10.3390/proteomes5030020
الوصول الحر: https://doaj.org/article/a54a3fc2720f45279481ad8bd3ab8ff8Test
رقم الانضمام: edsdoj.54a3fc2720f45279481ad8bd3ab8ff8
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22277382
DOI:10.3390/proteomes5030020