InferenceMAP: Mapping of Single-Molecule Dynamics with Bayesian Inference

TL;DR

InferenceMAP is an interactive software tool that employs Bayesian inference to generate detailed spatial maps of single-molecule dynamics within cells, addressing a key gap in analyzing high-density single-particle tracking data.

Contribution

It introduces a novel Bayesian-based software for mapping heterogeneous molecular motion in cells, enabling detailed analysis of single-molecule trajectories.

Findings

Provides detailed spatial maps of molecular dynamics

Enables analysis of heterogeneous and complex trajectories

Fills a gap in publicly available SPT analysis tools

Abstract

Single-particle tracking (SPT) grants unprecedented insight into cellular function at the molecular scale [1]. Throughout the cell, the movement of single-molecules is generally heterogeneous and complex. Hence, there is an imperative to understand the multi-scale nature of single-molecule dynamics in biological systems. We have previously shown that with high-density SPT, spatial maps of the parameters that dictate molecule motion can be generated to intricately describe cellular environments [2,3,4]. To date, however, there exist no publically available tools that reconcile trajectory data to generate the aforementioned maps. We address this void in the SPT community with InferenceMAP: an interactive software package that uses a powerful Bayesian method to map the dynamic cellular space experienced by individual biomolecules.