Topological data analysis distinguishes parameter regimes in the Anderson-Chaplain model of angiogenesis

Autor: Heather A. Harrington, Helen M. Byrne, Kevin B. Flores, Bernadette J. Stolz, John T. Nardini
Rok vydání: 2021
Předmět:
0301 basic medicine
Computer science
Physiology
Vector Spaces
Parameter space
Cardiovascular Physiology
Quantitative Biology - Quantitative Methods
Topology
Field (computer science)
Epithelium
0302 clinical medicine
Development (topology)
Animal Cells
Neoplasms
Medicine and Health Sciences
Biology (General)
Quantitative Methods (q-bio.QM)
Topology (chemistry)
Ecology
Neovascularization
Pathologic
Chemotaxis
Simulation and Modeling
Physics
Models
Cardiovascular
Computational mathematics
Cell Motility
Computational Theory and Mathematics
030220 oncology & carcinogenesis
Modeling and Simulation
Physical Sciences
Anatomy
Cellular Types
Biological system
Algorithms
Research Article
Biophysical Simulations
QH301-705.5
Biophysics
Neovascularization
Physiologic
Research and Analysis Methods
Synthetic data
03 medical and health sciences
Cellular and Molecular Neuroscience
Spatio-Temporal Analysis
Genetics
Animals
Humans
Computer Simulation
Molecular Biology
Ecology
Evolution
Behavior and Systematics
Experimental data
Computational Biology
Biology and Life Sciences
Endothelial Cells
Epithelial Cells
Cell Biology
030104 developmental biology
Biological Tissue
Algebra
Linear Algebra
FOS: Biological sciences
Cardiovascular Anatomy
Blood Vessels
Topological data analysis
Angiogenesis
Mathematics
Developmental Biology
Zdroj: PLoS Computational Biology
PLoS Computational Biology, Vol 17, Iss 6, p e1009094 (2021)
ISSN: 1553-7358
Popis: Angiogenesis is the process by which blood vessels form from pre-existing vessels. It plays a key role in many biological processes, including embryonic development and wound healing, and contributes to many diseases including cancer and rheumatoid arthritis. The structure of the resulting vessel networks determines their ability to deliver nutrients and remove waste products from biological tissues. Here we simulate the Anderson-Chaplain model of angiogenesis at different parameter values and quantify the vessel architectures of the resulting synthetic data. Specifically, we propose a topological data analysis (TDA) pipeline for systematic analysis of the model. TDA is a vibrant and relatively new field of computational mathematics for studying the shape of data. We compute topological and standard descriptors of model simulations generated by different parameter values. We show that TDA of model simulation data stratifies parameter space into regions with similar vessel morphology. The methodologies proposed here are widely applicable to other synthetic and experimental data including wound healing, development, and plant biology.
Author summary Vascular networks play a key role in many physiological processes, by delivering nutrition to, and removing waste from, biological tissues. In cancer, tumors stimulate the growth of new blood vessels, via a process called angiogenesis. The resulting vascular structure comprises many inter-connected vessels which lead to emergent morphologies that influence the rate of tumor growth and treatment efficacy. In this work, we consider several approaches to summarize the morphology of synthetic vascular networks generated from a mathematical model of tumor-induced angiogenesis. We find that a topological approach can be used quantify vascular morphology of model simulations and group the simulations into biologically interpretable clusters. This methodology may be useful for the diagnosis of abnormal blood vessel networks and quantifying the efficacy of vascular-targeting treatments.
Databáze: OpenAIRE
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