2013/09/09 by Denis Menshykau, Srivathsan Adivarahan, Menshykau, Denis +7
Biochemistry, Genetics and Molecular Biology · #Developmental Biology and Gene Regulation #FOS: Biological sciences #Microtubule and mitosis dynamics #Molecular Networks (q-bio.MN) #Pluripotent Stem Cells Research #Quantitative Methods (q-bio.QM) #Renal and related cancers #Tissues and Organs (q-bio.TO)
paper · pdf · doi:10.48550/arxiv.1309.2232
openalex publication_date 2013/09/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Morphogenesis is a tightly regulated process that has been studied for\ndecades. We are developing data-based and image-basd mechanistic models for a\nrange of developmental processes with a view to integrate the available\nknowledge and to better understand the underlying regulatory logic. In our\nprevious papers on simulating organogenesis with COMSOL (German et al COMSOL\nConf Procedings 2011; Menshykau and Iber, COMSOL Conf Proceedings 2012) we\ndiscussed methods to efficiently solve such models on static and growing\ndomains. A further challenge in modeling morphogenesis is the parameterization\nof such models. Here we discuss COMSOL-based methods for parameter\noptimization. These routines can be used to determine parameter sets, for which\nthe simulations reproduce experimental data and constraints. Such data is often\nimage based, but may also come from classical biochemical or genetic\nexperiments.\n