# Data Collaboration

The Data Collaboration MATLAB toolbox is a software package designed to integrate experimental data into quantitative predictive models. In the academic environment, the methodology facilitated by the software has been applied to a combustion chemistry application and an atmospheric chemistry application. A subset of the tools has also been applied to robust analysis of a biological cell-signaling model. See below under "Associated Work". The software allows the user to input results of one or more experimental measurements taken on the system along with their expected uncertainty. Taken with a parametrized model, the observations implicitly describe a set of feasible parameter values. Questions about this set, such as is it nonempty (model validation) or what is the range of values a given model can take over it (model prediction) are posed as mathematical programs. These are solved by recently developed techniques for optimization problems involving polynomials.

### Releases

- Download Page. Download the latest release of the MATLAB software via sourceforge
- Tracker. To report bugs, and request for new features or support, see this sourceforge feature.

### Associated work

See the associated academic works page for a list of papers, presentation slides, summary slides, and tutorial notes.

### Links

- MATLAB - A high level programming language for algorithm development, numeric computation, and data analysis.
- SeDuMi - A MATLAB software package to solve optimization problems over symmetric cones.
- GRI-Mech - Methane Combustion Chemistry.
- PrIME - Process Informatics Model. A collection (and associated methogology) of chemical reaction systems data to develope predictive models based on the scientific collaboratory paradigm.
- YALMIP - A MATLAB toolbox for rapid prototyping of optimization problems.
- SOSTOOLS - Sum of squares optimization toolbox for MATLAB.