SUMMARY: Quantification of growth parameters and extracellular uptake and production fluxes is central in systems and synthetic biology. Fluxes can be estimated using various mathematical models by fitting time-course measurements of the concentration of cells and extracellular substrates and products. A single tool is available to non-computational biologists to calculate extracellular fluxes, but it is hardly interoperable and is limited to a single hard-coded growth model. We present our open-source flux calculation software, PhysioFit, which can be used with any growth model and is interoperable by design. PhysioFit includes some of the most common growth models, and advanced users can implement additional models to calculate extracellular fluxes and other growth parameters for metabolic systems or experimental setups that follow alternative kinetics. PhysioFit can be used as a Python library and offers a graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. AVAILABILITY AND IMPLEMENTATION: PhysioFit v3 is implemented in Python 3 and was tested on Windows, Unix, and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/PhysioFit/ and https://physiofit.readthedocs.io/.

Abstract Summary: MSeasy performs unsupervised data mining on gas chromatography–mass spectrometry data. It detects putative compounds within complex metabolic mixtures through the clustering of mass spectra. Retention times or retention indices are used after clustering, together with other validation criteria, for quality control of putative compounds. The package generates a fingerprinting or profiling matrix compatible with NIST mass spectral search program and ARISTO webtool (Automatic Reduction of Ion Spectra To Ontology) for molecule identification. Most commonly used file formats, NetCDF, mzXML and ASCII, are acceptable. A graphical and user-friendly interface, MSeasyTkGUI, is available for R novices. Availability: MSeasy and MSeasytkGUI are implemented as R packages available at http://cran.r-project.org/web/packages/MSeasy/index.html and http://cran.r-project.org/web/packages/MSeasyTkGUI/index.html Contact: [email protected] Supplementary information: Additional information, self-guided tutorials and demonstration data are available on the web site: http://sites.google.com/site/rpackagemseasy/home. Workflow of MSeasy is available in supplementary material