Metadata-Version: 2.1
Name: iocbio.kinetics
Version: 1.5.0
Summary: IOCBio Kinetics
Home-page: https://sysbio.ioc.ee
Author: IOCBio team
Author-email: iocbio@sysbio.ioc.ee
License: GPLv3
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: X11 Applications :: Qt
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: AUTHORS.md

# Kinetics analysis program

IOCBIO Kinetics is a cross-platform application for analysis of
different traces, as described by its plugins. While originally
developed for analysis of enzyme kinetics, the other types of traces
can be analyzed as well. It is designed to analyze traces where some
measured parameter depends on one other parameter, such as time or
space. For example, respiration rate measurements via following oxygen
concentration in time and its changes through addition of metabolites.

The analysis of experimental traces is built as a pipeline, with the
data imported from the experiment file, regions of interest
automatically generated or set by user, data fitted and
analyzed. Communication between different plugins is done through the
database backend with the analysis results stored in the
database. Software is modular with the new modules added easily to fit
the new types of experiments.

- User documenation: https://iocbio.gitlab.io/kinetics
- Issues: https://gitlab.com/iocbio/kinetics/issues
- Releases: https://gitlab.com/iocbio/kinetics/-/releases

# Citations and software description

Software is described in a paper (see below) that gives a background
information regarding use of the software and shows an example
analysis of sparks. Please cite this paper if you use the software.

Vendelin, M., Laasmaa, M., Kalda, M., Branovets, J., Karro, N.,
Barsunova, K., & Birkedal, R. (2020). IOCBIO Kinetics: An open-source
software solution for analysis of data traces. _PLOS Computational
Biology_, 16(12), e1008475. https://doi.org/10.1371/journal.pcbi.1008475

## Copyright

Copyright (C) 2018-2020 Laboratory of Systems Biology, Department of
Cybernetics, School of Science, Tallinn University of Technology
(https://sysbio.ioc.ee).

Software license: GPLv3, see [LICENSE](LICENSE).

Contact: Marko Vendelin <markov@sysbio.ioc.ee>
