A discrete mathematical setting

The MP theory has been introduced by Prof. Vincenzo Manca in 2004 in order to algorithmically model biological dynamics. Theoretical and modeling results have been published in more than 60 papers.

An open-source project

The reliability of the algorithms provided by the library is emphasized by the complete availability of the sources, which are released under the GNU Lesser General Public License (LGPL) Version 3.


Welcome to MpTheory Java Library!

MpTheory Java Library is an open-source project released under GNU Lesser General Public License (LGPL) Version 3.

The library collects a set of Java objects and algorithms for modeling observed dynamics by means of the Metabolic P (MP) theory, that is, a discrete mathematical theory based on P systems, introduced by Prof. Vincenzo Manca in 2004 for modeling biological dynamics.

By means of the library, it is possible to model dynamical systems both at continuous and at discrete time. Moreover, the library comprises a set of regression algorithms for inferring MP models starting from time series of observations.

A complete multi-platform solution

As any Java software, the library is completely multi-platform, it is distributed with a comprehensive documentation, and it can be used everywhere it is installed a Java 6.0 runtime environment.

Full usability from the most popular computing environments

The library can be directly used within the most popular computing environments, such as MATLAB, GNU Octave, Mathematica, and R.

A framework for the systematic algorithmic solution to dynamical inverse problems

Given time series as input, implemented regression algorithms provide systems of recurrent equations generating them.

An easy and powerful modeling framework

All the java objects have been designed for enhancing the modeling experience even for scientists who are not familiar with programming languages or are mostly familiar with classic modeling environments (ODEs, DDEs).
All the implemented algorithms have been strongly optimized and support multi-threading.

A wide applicability modeling framework

The regression algorithms are suitable for modeling any kind of dynamics. Successful modeling results comprise metabolic dynamics, gene expression networks, and population dynamics.


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