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Ms-data-core-api: an open-source, metadata-oriented library for computational proteomics.


ABSTRACT:

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The ms-data-core-api is a free, open-source library for developing computational proteomics tools and pipelines. The Application Programming Interface, written in Java, enables rapid tool creation by providing a robust, pluggable programming interface and common data model. The data model is based on controlled vocabularies/ontologies and captures the whole range of data types included in common proteomics experimental workflows, going from spectra to peptide/protein identifications to quantitative results. The library contains readers for three of the most used Proteomics Standards Initiative standard file formats: mzML, mzIdentML, and mzTab. In addition to mzML, it also supports other common mass spectra data formats: dta, ms2, mgf, pkl, apl (text-based), mzXML and mzData (XML-based). Also, it can be used to read PRIDE XML, the original format used by the PRIDE database, one of the world-leading proteomics resources. Finally, we present a set of algorithms and tools whose implementation illustrates the simplicity of developing applications using the library.

Availability and implementation

The software is freely available at https://github.com/PRIDE-Utilities/ms-data-core-api.

Supplementary information

Supplementary data are available at Bioinformatics online

Contact

juan@ebi.ac.uk.

SUBMITTER: Perez-Riverol Y 

PROVIDER: S-EPMC4547611 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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ms-data-core-api: an open-source, metadata-oriented library for computational proteomics.

Perez-Riverol Yasset Y   Uszkoreit Julian J   Sanchez Aniel A   Ternent Tobias T   Del Toro Noemi N   Hermjakob Henning H   Vizcaíno Juan Antonio JA   Wang Rui R  

Bioinformatics (Oxford, England) 20150424 17


<h4>Unlabelled</h4>The ms-data-core-api is a free, open-source library for developing computational proteomics tools and pipelines. The Application Programming Interface, written in Java, enables rapid tool creation by providing a robust, pluggable programming interface and common data model. The data model is based on controlled vocabularies/ontologies and captures the whole range of data types included in common proteomics experimental workflows, going from spectra to peptide/protein identific  ...[more]

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