Descriptive vs. mechanistic network models in plant development in the post-genomic era

Area of Science:

• Systems Biology
• Integrative Genomics
• Computational Biology

Background:

• Network modeling is crucial for systems biology and integrative genomics.
• A clear understanding of modeling approaches is needed for a quantitative, multidisciplinary biology.
• Two main approaches exist: inference-based and system dynamics.

Purpose of the Study:

• To describe and compare network inference and system dynamics approaches.
• To discuss their goals, utility, assumptions, and limitations.
• To apply both methods to a specific developmental module.

Main Methods:

• Network inference for discovering functional influences.
• System dynamics for mechanistic study of developmental processes.
• Comparative analysis using the Arabidopsis thaliana Root Stem Cell Niche GRN.

Main Results:

• Inference-based models identify potential molecular component interactions.
• System dynamics models are suited for studying developmental mechanisms.
• Descriptive models from functional genomics align with mechanistic GRN models.

Conclusions:

• Both network inference and system dynamics offer valuable, complementary insights.
• The comparative approach enhances understanding of biological networks.
• This rationale is applicable to other developmental modules in multicellular organisms.