CoLoMoTo (Consortium for Logical Models and Tools) is a consortium of research groups interested in logical (qualitative) modelling of biological systems: modelers, curators and developers of methods and software tools. The consortium works on the definition of standards for model representation and interchange (especially the SBML qual format), and on the comparison of methods, models and tools.
The CoLoMoTo consortium was announced in the following publication:
We organize various events around qualitative modeling techniques: introductory courses, tutorials on software tools, and research workshops.
Logical models are available from various repositories listed below. We encourage the use of the SBML qual exchange format to share models to a wide audience. However, other formats exist for historical or technical reasons.
See the list of common formats.
Many software tools have been developed to support the analysis of qualitative models. These tools have often been used separately, however as they provide complementary features, we think they can be combined to build rich analysis workflows.
The CoLoMoTo consortium has worked on the SBML qual to enable interoperability between some of these tools. The CoLoMoTo Notebook further provides a single Docker image integrating a large collection of tools and facilitates reproducible analysis.
See the list of available software tools.
Qualitative models provide logical rules controlling the activity level of each component. The updating semantics further defines the application of these rules, especially when the level of multiple components can be updated in the current state.
Deterministic semantics (e.g. synchronous) define a single successor. They are convenient for simulations but could generate artefactual behaviours due to their strong kinetic assumptions.
Non-deterministic semantics (e.g. asynchronous or permissive) provide a collection of alternative trajectories to capture the incertainty often associated to qualitative models. They are more likely to generate realistic biological behaviours, but it can be burried among a large number of trajectories (some artefactual) and they are more difficult to simulate.
See the list of updating semantics.
Simulations provide a natural way to evaluate the dynamical behaviour of a qualitative model by defining an initial state and applying the update functions.
Deterministic: Traces or continuous view.
Non-deterministic: State Transition graph or stochastic sampling.
Static analysis methods provide some dynamical informations without performing explicit simulations, which is especially useful for large models where classical simulations become untractable. These methods are well suited for the identification (or at least approximation) of attractors (representing stable phenotypes) and some reachability properties.
See the list of static analysis methods.
The CoLoMoTo mailing list is our main communication channel, it is open (upon registration) to anyone interested in qualitative modeling. You can also contact us on contact@colomoto.org or on the CoLoMoTo group on LinkedIn. You can also contact individual members if you have specific questions.
See the list of research groups involved in the consortium.