We here present the jmzReader library: a collection of Java application programming interfaces (APIs) to parse the most commonly used peak list and XML-based mass spectrometry (MS) data formats: DTA, MS2, MGF, PKL, mzXML, mzData, and mzML (based on the already existing API jmzML). The library is optimized to be used in conjunction with mzIdentML, the recently released standard data format for reporting protein and peptide identifications, developed by the HUPO proteomics standards initiative (PSI). mzIdentML files do not contain spectra data but contain references to different kinds of external MS data files. As a key functionality, all parsers implement a common interface that supports the various methods used by mzIdentML to reference external spectra. Thus, when developing software for mzIdentML, programmers no longer have to support multiple MS data file formats but only this one interface. The library (which includes a viewer) is open source and, together with detailed documentation, can be downloaded from http://code.google.com/p/jmzreader/.
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http://dx.doi.org/10.1002/pmic.201100578 | DOI Listing |
Front Netw Physiol
February 2022
Simulation and Data Lab Neuroscience, Institute for Advanced Simulation, Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, JARA, Jülich, Germany.
Whole brain network models are now an established tool in scientific and clinical research, however their use in a larger workflow still adds significant informatics complexity. We propose a tool, RateML, that enables users to generate such models from a succinct declarative description, in which the mathematics of the model are described without specifying how their simulation should be implemented. RateML builds on NeuroML's Low Entropy Model Specification (LEMS), an XML based language for specifying models of dynamical systems, allowing descriptions of neural mass and discretized neural field models, as implemented by the Virtual Brain (TVB) simulator: the end user describes their model's mathematics once and generates and runs code for different languages, targeting both CPUs for fast single simulations and GPUs for parallel ensemble simulations.
View Article and Find Full Text PDFRapid Commun Mass Spectrom
January 2022
Federal Institute of Hydrology, Koblenz, Germany.
Rationale: Non-target screening techniques using high-resolution mass spectrometers become more and more important for environmental sciences. Highly reliable and sophisticated software solutions are required to deal with the large amount of data obtained from such analyses.
Methods: Processing of high-resolution LC-HRMS data was performed upon conversion into an open, XML-based data format followed by an automated assignment of chromatographic peaks using the open-source programming language R.
Mass Spectrom Rev
September 2017
Research Division, Weill Cornell Medicine in Qatar, Doha, State of Qatar.
The evolution of data exchange in Mass Spectrometry spans decades and has ranged from human-readable text files representing individual scans or collections thereof (McDonald et al., 2004) through the official standard XML-based (Harold, Means, & Udemadu, 2005) data interchange standard (Deutsch, 2012), to increasingly compressed (Teleman et al., 2014) variants of this standard sometimes requiring purely binary adjunct files (Römpp et al.
View Article and Find Full Text PDFProteomics
September 2015
Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer.
View Article and Find Full Text PDFBioinformatics
September 2015
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
Unlabelled: 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.
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