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      A Cross-platform Toolkit for Mass Spectrometry and Proteomics

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      1 , 2 , 3 , 16 , 3 , 6 , 7 , 15 , 4 , 2 , 3 , 4 , 4 , 2 , 2 , 2 , 14 , 14 , 5 , 3 , 3 , 3b , 8 , 8 , 8 , 9 , 9 , 10 , 10 , 11 , 11 , 12 , 13 , 13 , 3b , 13 , 14 , 14 , 3 , 3 , 2 , 1 , 3 , 16
      Nature biotechnology

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          Abstract

          Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples 1 , identify pathways affected by endogenous and exogenous perturbations 2 , and characterize protein complexes 3 . Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access 4, 5 . In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.

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          Most cited references9

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          Is Open Access

          mzML—a Community Standard for Mass Spectrometry Data*

          Mass spectrometry is a fundamental tool for discovery and analysis in the life sciences. With the rapid advances in mass spectrometry technology and methods, it has become imperative to provide a standard output format for mass spectrometry data that will facilitate data sharing and analysis. Initially, the efforts to develop a standard format for mass spectrometry data resulted in multiple formats, each designed with a different underlying philosophy. To resolve the issues associated with having multiple formats, vendors, researchers, and software developers convened under the banner of the HUPO PSI to develop a single standard. The new data format incorporated many of the desirable technical attributes from the previous data formats, while adding a number of improvements, including features such as a controlled vocabulary with validation tools to ensure consistent usage of the format, improved support for selected reaction monitoring data, and immediately available implementations to facilitate rapid adoption by the community. The resulting standard data format, mzML, is a well tested open-source format for mass spectrometer output files that can be readily utilized by the community and easily adapted for incremental advances in mass spectrometry technology.
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            XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization.

            Mass spectrometry based metabolomics represents a new area for bioinformatics technology development. While the computational tools currently available such as XCMS statistically assess and rank LC-MS features, they do not provide information about their structural identity. XCMS(2) is an open source software package which has been developed to automatically search tandem mass spectrometry (MS/MS) data against high quality experimental MS/MS data from known metabolites contained in a reference library (METLIN). Scoring of hits is based on a "shared peak count" method that identifies masses of fragment ions shared between the analytical and reference MS/MS spectra. Another functional component of XCMS(2) is the capability of providing structural information for unknown metabolites, which are not in the METLIN database. This "similarity search" algorithm has been developed to detect possible structural motifs in the unknown metabolite which may produce characteristic fragment ions and neutral losses to related reference compounds contained in METLIN, even if the precursor masses are not the same.
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              • Record: found
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              mzAPI: a new strategy for efficiently sharing mass spectrometry data.

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                Author and article information

                Journal
                9604648
                20305
                Nat Biotechnol
                Nat. Biotechnol.
                Nature biotechnology
                1087-0156
                1546-1696
                16 May 2012
                10 October 2012
                10 April 2013
                : 30
                : 10
                : 918-920
                Affiliations
                [1 ] Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37212-8575, USA
                [2 ] Department of Genome Sciences, University of Washington, Seattle, WA 98195
                [3 ] Center for Applied Molecular Medicine, University of Southern California, Los Angeles, CA 90033, USA
                [3b ] USC Stevens Institute for Innovation, University of Southern California, Los Angeles, CA 90089, USA
                [4 ] Insilicos, Seattle WA 98109
                [5 ] Matrix Science, Boston, MA 02110
                [6 ] Department of Stress & Developmental Biology, Leibniz Institute for Plant Biochemistry, Halle (Saale), Germany
                [7 ] Proteomics Services, Cambridge Centre for Proteomics, Cambridge, England
                [8 ] AB SCIEX, Foster City, CA 94404
                [8b ] AB SCIEX, Concord, Ontario, Canada
                [9 ] Agilent Technologies, Santa Clara, California 95051
                [10 ] Bruker Daltonik GmbH, Fahrenheitstraße 4, 28359 Bremen, Germany
                [11 ] Thermo Fisher Scientific, San Jose, CA 95134
                [12 ] Waters Corporation, Manchester, UK, M22 5PP
                [13 ] LabKey Software, Seattle, WA 98102
                [14 ] Institute for Systems Biology, Seattle, WA 98109
                [15 ] Genome Biology, EMBL Heidelberg, Germany
                [16 ] Canary Center for Cancer Early Detection, Stanford University, Stanford, CA 94024
                Author notes
                Corresponding Author: Parag Mallick, Ph.D. Stanford University 1501 S California Avenue, Room 2212 Palo Alto, CA 94304 paragm@ 123456stanford.edu
                [*]

                These authors contributed equally

                Article
                NIHMS374482
                10.1038/nbt.2377
                3471674
                23051804
                c506fc03-e2bb-43ae-b164-48693efea47f

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                Biotechnology
                Biotechnology

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