SOMMD

SOMMD streamlines the analysis of molecular dynamics simulations using self-organizing maps to facilitate the interpretation of atomistic trajectories.

Key Features:

• Data Import: Imports a wide range of molecular dynamics trajectories data types.
• Visualization: Generates enhanced visualizations for self-organizing map analyses.
• Transition Network Reconstruction: Reconstructs transition networks from molecular dynamics simulation data.
• Cluster Analysis: Performs cluster analysis using self-organizing maps.
• Pathways Mapping: Maps pathways in molecular dynamics simulations using self-organizing maps.

Scientific Applications:

• Biomolecular Process Analysis: Extracts essential information on functional dynamics from complex high-dimensional molecular dynamics simulation data.
• Conformational Dynamics Interpretation: Interprets atomistic trajectories to understand biomolecular conformational changes and transitions.

Methodology:

SOMMD applies self-organizing maps as a dimensionality reduction method for molecular dynamics simulation analysis, with workflows that include data import, self-organizing map computation, and generation of visualizations and transition networks.