Simulated Adaptation Data for Genetic Network Motifs

Comprising simulation results modeling adaptation under divergent selection with gene flow across a set of two-node, two-phenotype genetic network motifs. It was created by Tyler D. Hether and published in 2020 to analyze how network interactions shape mutational (co)variance (M-matrix) and constrain evolutionary trajectories.

Use Cases

• Analyze patterns of mutational (co)variance (M-matrix) across different genetic network motifs to compare evolvability constraints.
• Simulate adaptive trajectories under divergent selection to study the curvature of phenotypic space influenced by the M-matrix.
• Model the relationship between standing genetic variation (G-matrix) and the M-matrix under weak selection scenarios.
• Investigate the effect of gene flow on migration-selection balance as constrained by network-derived mutational variance.

Strengths

• Covers a full range of regulatory interactions for two-node, two-phenotype network motifs, providing a systematic comparison.
• Data underpins a published study on evolutionary systems biology, offering a modeled perspective on genetic constraint.
• Released under a permissive CC0 1.0 license, allowing for unrestricted reuse and analysis.

Limitations

• Data is entirely simulated based on theoretical models, not derived from empirical biological measurements.
• The scope is limited to abstracted two-node network motifs, which simplifies real-world genetic complexity.
• Specific dataset dimensions (rows, columns, file size) and formats are not provided, complicating initial assessment.

Provenance

Source

Dryad digital repository.

Collection Method

Computational simulation of genetic network motifs and evolutionary adaptation models.

Freshness

Last updated in June 2020.