Kiphynet: an online network simulation tool connecting cellular kinetics and physiological transport.

Area of Science:

• Physiological modeling
• Systems biology
• Computational biology

Background:

• Human metabolism relies on complex functional networks operating at multiple scales.
• Bridging these multi-scale networks for local and global dynamics is a significant challenge in physiological modeling.

Purpose of the Study:

• Develop an interactive web application for simulating and visualizing transport and reactions in 3D microvascular networks.
• Facilitate the integration of multi-omics and vascular imaging data for physiological studies.

Main Methods:

• Utilizes a discrete graph-based modeling framework (KiPhyNet) to bridge multi-scale functional networks.
• Implemented in Python with MATLAB as the simulator engine, deployed on an Apache web server.
• Assimilates multi-omics and vascular imaging data to link structural changes to functional responses.

Main Results:

• Enables simulation of advection-dispersion transport, biochemical exchange, and metabolic reactions.
• Users can interactively examine simulation results, including steady-state velocity/pressure and dynamic concentration fields.
• Input parameters include network topology, biophysical attributes, boundary conditions, and kinetic properties.

Conclusions:

• KiPhyNet offers accessible, barrier-free simulation of time-course experiments for multi-scale microvascular network models.
• Provides a discrete modeling framework for advancing research in physiology and metabolism.
• The application and its documentation are freely available online.