InferenceMAP is a software aimed at analysing single molecule dynamics. InferenceMAP is based on Bayesian analysis of Random Walks and this version is focused on mapping Random Walks at the full cell scale in 2D. It uses unsupervised machine learning to perform density based meshing and outputs maps of diffusion/drift/force/potential with posterior distribution of all the parameters. InferenceMAP can generate large amounts of trajectories in the inferred maps using the master equation approximation of the Fokker-Planck describing the motion. Finally, InferenceMAP provides multiple representations of both raw data and inferred fields.
This Software has been developed by Mohamed El Beheiry (Institut Curie in Dahan’s lab, email@example.com) and Jean-Baptiste Masson (Pasteur Institute).
The manual of inferenceMAP: InferenceMAP_Manual
InferenceMAP running on Windows: InferenceMAP_Windows
InferenceMAP running on Mac/Unix: InferenceMAP_Mac