About Physiome

About IMAG

Defining the Physiome

The Physiome is ...

The term comes from "physio-" (life) and "-ome" (as a whole). In its broadest sense, the physiome should define relationships from genome to organism and from functional behavior to gene regulation.

The physiome is the quantitative and integrated description of the functional behavior of the physiological state of an individual or species. The physiome describes the physiological dynamics of the normal intact organism and is built upon information and structure (genome, proteome, and morphome). The term comes from "physio-" (life) and "-ome" (as a whole). In its broadest sense, the physiome should define relationships from genome to organism and from functional behavior to gene regulation. In context of the Physiome Project, it includes integrated models of components of organisms, such as particular organs or cell systems, biochemical, or endocrine systems.

Building the Physiome Project

The Physiome Project is a worldwide effort to define the physiome through the development of databases and models which will facilitate the understanding of the integrative function of cells, organs, and organisms. The Project is focused on compiling and providing a central repository of databases, linking experimental information and computational models from many laboratories into a single, self-consistent framework. This coalescence of research effort will promote comprehensive databases and an integrative, analytical approach to the study of medicine and physiology.

Mission Statement

The Physiome Project aims to develop, collect, preserve, and disseminate information and integrated understandings of functional biological systems. Going beyond experimentation and observation, the key elements of the Project are the databasing of physiological, pharmacological, and pathological information on humans and other organisms and integration through computational modeling. "Models" include everything from diagrammatic schema, suggesting relationships among elements composing a system, to fully quantitative, computational models describing the behavior of physiological systems and an organism's response to environmental change. Each mathematical model is an internally self-consistent summary of available information, and thereby defines a "working hypothesis" about how a system operates. Predictions from such models are subject to test, with new results leading to new models. The behavior of complex biological systems will be gradually revealed through this step-by-step process of building upon and further refining "what is known."

(Bassingthwaighte JB. Strategies for the Physiome Project. Ann  Biomed Eng 28, 1043-1058, 2000.)

Goals of the Physiome Project:

  1. To develop and database observations of physiological phenomenon and interpret these in terms of mechanism (a fundamentally reductionist goal).
  2. To integrate experimental information into quantitative descriptions of the functioning of humans and other organisms (modern integrative biology glued together via modeling).
  3. To disseminate experimental data and integrative models for teaching and research.
  4. To foster collaboration amongst investigators worldwide, to speed up the discovery of how biological systems work.
  5. To determine the most effective targets (molecules or systems) for therapy, either pharmaceutic or genomic.
  6. To provide information for the design tissue-engineered, biocompatible implants.

Model development and archiving support at https://www.imagwiki.nibib.nih.gov/physiome provided by the following grants: NIH U01HL122199 Analyzing the Cardiac Power Grid, 09/15/2015 - 05/31/2020, NIH/NIBIB BE08407 Software Integration, JSim and SBW 6/1/09-5/31/13; NIH/NHLBI T15 HL88516-01 Modeling for Heart, Lung and Blood: From Cell to Organ, 4/1/07-3/31/11; NSF BES-0506477 Adaptive Multi-Scale Model Simulation, 8/15/05-7/31/08; NIH/NHLBI R01 HL073598 Core 3: 3D Imaging and Computer Modeling of the Respiratory Tract, 9/1/04-8/31/09; as well as prior support from NIH/NCRR P41 RR01243 Simulation Resource in Circulatory Mass Transport and Exchange, 12/1/1980-11/30/01 and NIH/NIBIB R01 EB001973 JSim: A Simulation Analysis Platform, 3/1/02-2/28/07.