Module I: Core Topics

The Lecture program will cover five main Core Topics: (1) Biophysical modeling theory, (2) Biophysical modeling tools, (3) The NIH SPARC effort, (4) Neurophysiology review, (5) Computational knowledge management.

• Biophysical modeling theory (week 1)
  • Introduction to bond graph modeling and its application to representing key processes in neurobiology such as the maintenance of membrane potential, receptor activation and membrane channel mechanisms;
  • Ordinary Differential Equation (ODE) modeling and its relationship with bond graphs. Worked examples for solute(s) movement across the cell membrane, including relationship between the relative ionic concentrations across the membrane with potential difference, simulation of action potential with focus on sodium- and calcium-mediated spikes relevant to neuron, secretory cell and smooth muscle signaling.

  After “Biophysical modeling theory”, the student will be able to:

  • Understand solute transport across cell membranes;
  • Build a bond graph model of a simple transporter/channel/receptor mechanism;
  • Explain concepts of conservation of mass, charge and energy and appreciate that the bond graph formalism ensures conservation of mass, charge, and energy;
  • Understand the importance of consistent units in modeling and explain how to link unit consistency with bond graph formalism;
  • Use ODEs to model transporter processes and convert bond graphs to ODEs.
• Biophysical modeling tools (week 2)
  • Reproducibility of simulation results, the Physiome journal, modular modeling and multiscale modeling;
  • CellML, OpenCOR and the Physiome Model Repository (PMR);
  • Online computational resources.

  After “Biophysical modeling tools”, the student will be able to:

  • Explain the importance of adopting community standards to ensure the reproducibility of computational models and how the Physiome journal is contributing to the development of a modular, standards-based, multiscale modeling framework;
  • Understand the principles behind the development of CellML as a modeling standard, how to use CellML with the OpenCOR simulation environment and the PMR repository of CellML models; optional use of OpenCOR with o2S2PARC.
• The SPARC effort (week 2)
  • The Portal;
  • Knowledge management;
  • FAIRness: Ensuring SPARC resources are findable, accessible, interoperable and reusable. Background on international FAIRness efforts will also be provided;
  • Data streams: Curation/segmentation/annotation examples for microscopy, neuron tracing, gene expression and electrophysiology experiments.

  After “the SPARC effort”, the student will be able to:

  • Use the SPARC portal for browsing/searching SPARC datasets and simulations, navigating flatmaps, downloading and accessing data;
  • Be familiar with the theory and content of the SPARC Knowledge graph (SKG), reference ontologies, metadata and how to access the SKG;
  • Explain the FAIRness principles;
  • Understand data streams.
• Neurophysiology Review (week 3)
  • The neurobiology of the pancreas (exocrine secretion), kidney (juxtaglomerular apparatus, renal tubular system, afferent/efferent arterioles), stomach (gastric glands), large intestine (colonic crypts and surface epithelium), gut immunity (spleen and Peyer’s patches);
  • The biology of key transporter gene families in mammals.

  After “Neurophysiology review”, the student will be able to:

  • Leverage the Medical Physiology textbook to navigate the salient concepts in transport physiology;
  • Navigate schematics that describe the physiological regulation of transport processes;
  • Familiarize with the notion of drug absorption, distribution, metabolism, and excretion (ADME).
• Computational knowledge management (week 4)
  • ApiNATOMY flow scaffolds: linking advective and diffusive flows across multiple scales to map out flows of fluids and solutes;
  • Autonomic and enteric nervous system maps in SPARC: introduction and examples from stomach and colon.

  After “Computational knowledge management”, the student will be able to:

  • Experience the use of knowledge graphs to manage information about biological connectivity networks;
  • Build schematics that describe the physiological regulation of transport processes by drawing knowledge from the Medical Physiology textbook and representing it using the ApiNATOMY formalism;
  • Leverage ApiNATOMY to map out drug ADME processes in the context of whole-body transport thoroughfares.