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However, before the mass spectrometric data can be used it has to be corrected for biases caused by naturally occurring stable isotopes, by the analytical technique(s) employed, or by the biological sample itself. Finally the MS data and the labeling information it contains have to be assembled into a data format usable by flux analysis software (of which several dedicated packages exist). Currently the processing of mass spectrometric data is time-consuming and error-prone requiring peak by peak cut-and-paste analysis and manual curation. In order to facilitate high-throughput metabolic flux analysis, the automation of multiple steps in the analytical workflow is necessary.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Here we describe <jats:italic>iMS2Flux,<\/jats:italic> software developed to automate, standardize and connect the data flow between mass spectrometric measurements and flux analysis programs. This tool streamlines the transfer of data from extraction via correction tools to <jats:sup>13<\/jats:sup>C-Flux software by processing MS data from stable isotope labeling experiments. It allows the correction of large and heterogeneous MS datasets for the presence of naturally occurring stable isotopes, initial biomass and several mass spectrometry effects. Before and after data correction, several checks can be performed to ensure accurate data. The corrected data may be returned in a variety of formats including those used by metabolic flux analysis software such as <jats:italic>13CFLUX<\/jats:italic>, <jats:italic>OpenFLUX<\/jats:italic> and <jats:italic>13CFLUX2<\/jats:italic>.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>\n              <jats:italic>iMS2Flux<\/jats:italic> is a versatile, easy to use tool for the automated processing of mass spectrometric data containing isotope labeling information. It represents the core framework for a standardized workflow and data processing. Due to its flexibility it facilitates the inclusion of different experimental datasets and thus can contribute to the expansion of flux analysis applications.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-13-295","type":"journal-article","created":{"date-parts":[[2012,11,12]],"date-time":"2012-11-12T21:37:11Z","timestamp":1352756231000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["iMS2Flux\u2013 a high\u2013throughput processing tool for stable isotope labeled mass spectrometric data used for metabolic flux analysis"],"prefix":"10.1186","volume":"13","author":[{"given":"C Hart","family":"Poskar","sequence":"first","affiliation":[]},{"given":"Jan","family":"Huege","sequence":"additional","affiliation":[]},{"given":"Christian","family":"Krach","sequence":"additional","affiliation":[]},{"given":"Mathias","family":"Franke","sequence":"additional","affiliation":[]},{"given":"Yair","family":"Shachar-Hill","sequence":"additional","affiliation":[]},{"given":"Bj\u00f6rn H","family":"Junker","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,11,12]]},"reference":[{"key":"5641_CR1","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/978-1-4684-1125-6_3","volume-title":"Biological Regulation and Development","author":"JJ Blum","year":"1982","unstructured":"Blum JJ, Stein RB: On the analysis of metabolic networks. 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