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eSTGt: a programming and simulation environment for population dynamics.

Adam Spiro¹, Ehud Shapiro²

¹Department of Computer Science and Applied Mathematics and Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.

BMC Bioinformatics

|April 28, 2016

Summary

This summary is machine-generated.

This study introduces eSTGt, a tool for modeling population dynamics using environment-dependent Stochastic Tree Grammars (eSTG). The software simulates lineage trees and individual states, aiding in hypothesis validation and prediction of biological system behavior.

Keywords:

Developmental modeling Lineage trees Population dynamics Stochastic simulation

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Area of Science:

Computational Biology
Systems Biology
Bioinformatics

Background:

Introduces environment-dependent Stochastic Tree Grammars (eSTG) for population dynamics.
eSTG models capture environmental effects and individual states abstracting inter-individual interactions.
Transition rules are context-free but probabilities/rates depend on global parameters like population size, generation count, and time.

Purpose of the Study:

To present eSTGt, a programming and simulation environment for eSTG.
To provide a tool for modeling and analyzing developmental processes and population dynamics.
To facilitate hypothesis testing and prediction of biological system behavior.

Main Methods:

Developed eSTGt, a MATLAB-based programming and simulation environment.
eSTGt generates lineage trees and internal state values during simulation.
Utilizes a formal language based on context-free stochastic tree grammars.

Main Results:

eSTGt generates lineage trees and associated internal state values.
Simulation outputs can be analyzed via a GUI or MATLAB's command-line interface.
The tool enables modeling of developmental processes influenced by environmental changes.

Conclusions:

eSTGt allows researchers to model and analyze population dynamics using biological knowledge.
Simulated lineage trees support in silico hypothesis validation and prediction of system behavior.
The MATLAB environment facilitates integration with existing user analysis pipelines.