Literature DB >> 16307524

What is mzXML good for?

Simon M Lin1, Lihua Zhu, Andrew Q Winter, Maciek Sasinowski, Warren A Kibbe.   

Abstract

mzXML (extensible markup language) is one of the pioneering data formats for mass spectrometry-based proteomics data collection. It is an open data format that has benefited and evolved as a result of the input of many groups, and it continues to evolve. Due to its dynamic history, its structure, purpose and applicability have all changed with time, meaning that groups that have looked at the standard at different points during its evolution have differing impressions of the usefulness of mzXML. In discussing mzXML, it is important to understand what mzXML is not. First, mzXML does not capture the raw data. Second, mzXML is not sufficient for regulatory submission. Third, mzXML is not optimized for computation and, finally, mzXML does not capture the experiment design. In general, it is the authors' opinion that XML is not a panacea for bioinformatics or a substitute for good data representation, and groups that want to use mzXML (or other XML-based representations) directly for data storage or computation will encounter performance and scalability problems. With these limitations in mind, the authors conclude that mzXML is, nonetheless, an indispensable data exchange format for proteomics.

Mesh:

Year:  2005        PMID: 16307524     DOI: 10.1586/14789450.2.6.839

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  14 in total

1.  An efficient data format for mass spectrometry-based proteomics.

Authors:  Anuj R Shah; Jennifer Davidson; Matthew E Monroe; Anoop M Mayampurath; William F Danielson; Yan Shi; Aaron C Robinson; Brian H Clowers; Mikhail E Belov; Gordon A Anderson; Richard D Smith
Journal:  J Am Soc Mass Spectrom       Date:  2010-07-07       Impact factor: 3.109

2.  Untargeted analysis of mass spectrometry data for elucidation of metabolites and function of enzymes.

Authors:  Raymundo Sanchez-Ponce; F Peter Guengerich
Journal:  Anal Chem       Date:  2007-04-05       Impact factor: 6.986

3.  mzAPI: a new strategy for efficiently sharing mass spectrometry data.

Authors:  Manor Askenazi; Jignesh R Parikh; Jarrod A Marto
Journal:  Nat Methods       Date:  2009-04       Impact factor: 28.547

4.  mzResults: an interactive viewer for interrogation and distribution of proteomics results.

Authors:  James T Webber; Manor Askenazi; Jarrod A Marto
Journal:  Mol Cell Proteomics       Date:  2011-01-25       Impact factor: 5.911

Review 5.  Comparative mass spectrometry-based metabolomics strategies for the investigation of microbial secondary metabolites.

Authors:  Brett C Covington; John A McLean; Brian O Bachmann
Journal:  Nat Prod Rep       Date:  2017-01-04       Impact factor: 13.423

6.  COMPASS: a suite of pre- and post-search proteomics software tools for OMSSA.

Authors:  Craig D Wenger; Douglas H Phanstiel; M Violet Lee; Derek J Bailey; Joshua J Coon
Journal:  Proteomics       Date:  2011-02-07       Impact factor: 3.984

7.  Liquid Chromatography Mass Spectrometry-Based Proteomics: Biological and Technological Aspects.

Authors:  Yuliya V Karpievitch; Ashoka D Polpitiya; Gordon A Anderson; Richard D Smith; Alan R Dabney
Journal:  Ann Appl Stat       Date:  2010       Impact factor: 2.083

8.  Interpretation of tandem mass spectra obtained from cyclic nonribosomal peptides.

Authors:  Wei-Ting Liu; Julio Ng; Dario Meluzzi; Nuno Bandeira; Marcelino Gutierrez; Thomas L Simmons; Andrew W Schultz; Roger G Linington; Bradley S Moore; William H Gerwick; Pavel A Pevzner; Pieter C Dorrestein
Journal:  Anal Chem       Date:  2009-06-01       Impact factor: 6.986

9.  multiplierz: an extensible API based desktop environment for proteomics data analysis.

Authors:  Jignesh R Parikh; Manor Askenazi; Scott B Ficarro; Tanya Cashorali; James T Webber; Nathaniel C Blank; Yi Zhang; Jarrod A Marto
Journal:  BMC Bioinformatics       Date:  2009-10-29       Impact factor: 3.169

10.  mzDB: a file format using multiple indexing strategies for the efficient analysis of large LC-MS/MS and SWATH-MS data sets.

Authors:  David Bouyssié; Marc Dubois; Sara Nasso; Anne Gonzalez de Peredo; Odile Burlet-Schiltz; Ruedi Aebersold; Bernard Monsarrat
Journal:  Mol Cell Proteomics       Date:  2014-12-11       Impact factor: 5.911

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.