Richard Gordon

The paper introduces a differentiation waves model to explain developmental processes across species, validated using C. elegans and other organisms.

The paper combines quantitative analysis of C. elegans embryonic development with theory-building to link emergent properties and developmental processes.

The paper develops a digital model of Bacillaria paradoxa using image processing and deep learning to analyze morphology and movement dynamics.

The paper uses computational modeling to analyze ommatidia formation in the Drosophila eye imaginal disc, identifying spatial patterns and spatiotemporal features.

The paper introduces an information isometry technique to quantify and visualize organizational features in developmental cell lineages using binary classification and isometric graphs.

This paper reinterprets C. elegans embryogenesis through a theoretical framework and develops an RDF-based computational tool to visualize differentiation waves and their role in development.