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Predictive Immune Modeling of Solid Tumors

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Published on: February 25, 2020

Predictive Modeling and Integrative Physiology: The Physiome Projects.

James B Bassingthwaighte¹

¹Department of Bioengineering, University of Washington, 'Box 35-5061, 1705 NE Pacific St., Seattle, WA 98195-5061, USA.

The Open Pacing, Electrophysiology & Therapy Journal

|August 25, 2012

Summary

This summary is machine-generated.

Researchers are developing the human Physiome, a quantitative organism model, to improve healthcare by integrating biological data. This project aims to link genes to traits for a comprehensive understanding of health and disease.

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Area of Science:

Physiological research
Computational biology
Systems biology

Background:

Physiological research emphasizes integration of complex biological systems.
The concept of a Physiome—a quantitative, all-encompassing model of an organism—is emerging.
Existing knowledge is fragmented across various databases and research areas.

Purpose of the Study:

To define and develop a mathematical construct for the human Physiome.
To improve healthcare through a deep, systems-level understanding of the human organism.
To establish clear linkages between the genome and observable traits (phenotype).

Main Methods:

Systematic gathering and integration of existing and new biological knowledge into shared databases.
Development of self-consistent, reproducible mathematical models of biological systems.
Utilizing multiscale modeling, starting from the cellular level and extending to the organism and gene levels.

Main Results:

A framework for creating an all-encompassing quantitative model of an organism (Physiome).
Strategies for integrating diverse biological data into cohesive mathematical models.
A plan to build multiscale models connecting genes to organism-level functions.

Conclusions:

The human Physiome project represents a paradigm shift towards integrated, quantitative physiological research.
Understanding organismal function from genes to phenotype through mathematical modeling will enhance healthcare.
This approach promises to reconcile contradictions and clarify cause-and-effect relationships in biology.