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Related Experiment Video

Updated: Jun 24, 2026

The C. elegans Intestine As a Model for Intercellular Lumen Morphogenesis and In Vivo Polarized Membrane Biogenesis at the Single-cell Level: Labeling by Antibody Staining, RNAi Loss-of-function Analysis and Imaging

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Published on: October 3, 2017

Lung evolution as a cipher for physiology.

J S Torday¹, V K Rehan

¹Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA. jtorday@labiomed.org

Physiological Genomics

|April 16, 2009

Summary

A new algorithm translates genes into physiologic principles by focusing on cells as the fundamental unit. This approach, unlike prior systems biology efforts, aims to reconstruct physiology and predict disease from gene networks.

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Area of Science:

Genomics
Physiology
Systems Biology
Evolutionary Biology

Background:

The Human Genome Project (HGP) promised advances in systems biology for reconstructing physiology from genes, but this has not been fully realized.
Current approaches often overlook the cell as the smallest functional unit, hindering progress in functional genomics.

Purpose of the Study:

To develop an algorithm that translates genes into fundamental physiologic principles.
To establish a framework for functional genomics that accurately reflects biological complexity.

Main Methods:

Treating the cell, not the gene, as the smallest functional unit of biology.
Applying cell-cell communication mechanisms to understand lung development, homeostasis, and repair.
Reducing complex physiological traits to hierarchical gene regulatory networks.

Main Results:

Gene regulatory networks common across lung biology processes predict ontogeny, phylogeny, and disease.
The proposed algorithm elucidates vertebrate physiology as emergent cellular adaptational responses.
A hierarchical, self-organizing map of gene networks is proposed, analogous to the periodic table.

Conclusions:

A cell-centric algorithmic approach is necessary for advancing functional genomics and understanding physiology.
This framework offers a path toward discovering the first principles of physiology from gene regulatory networks.