Nested Inheritance Dynamics

TL;DR

This paper introduces a multiscale model called Nested Inheritance Dynamics Algorithm (NIDA) that extends the nested Dirichlet Process to analyze how biological processes are inherited, stable, or modified across generations.

Contribution

It presents a novel multiscale framework and algorithm for modeling biological inheritance and development processes across different levels of biological organization.

Findings

NIDA effectively models process inheritance across scales.

The framework integrates with existing biological models.

It provides insights into process stability and change over generations.

Abstract

The idea of the inheritance of biological processes, such as the developmental process or the life cycle of an organism, has been discussed in the biology literature, but formal mathematical descriptions and plausible data analysis frameworks are lacking. We introduce an extension of the nested Dirichlet Process (nDP) to a multiscale model to aid in understanding the mechanisms by which biological processes are inherited, remain stable, and are modified across generations. To address these issues, we introduce Nested Inheritance Dynamics Algorithm (NIDA). At its primary level, NIDA encompasses all processes unfolding within an individual organism's lifespan. The secondary level delineates the dynamics through which these processes evolve or remain stable over time. This framework allows for the specification of a physical system model at either scale, thus promoting seamless integration with established models of development and heredity.