| Literature DB >> 33449345 |
Bradly Alicea1,2, Richard Gordon3,4, Thomas E Portegys5,6.
Abstract
Biological development is often described as a dynamic, emergent process. This is evident across a variety of phenomena, from the temporal organization of cell types in the embryo to compounding trends that affect large-scale differentiation. To better understand this, we propose combining quantitative investigations of biological development with theory-building techniques. This provides an alternative to the gene-centric view of development: namely, the view that developmental genes and their expression determine the complexity of the developmental phenotype. Using the model system Caenorhabditis elegans, we examine time-dependent properties of the embryonic phenotype and utilize the unique life-history properties to demonstrate how these emergent properties can be linked together by data analysis and theory-building. We also focus on embryogenetic differentiation processes, and how terminally-differentiated cells contribute to structure and function of the adult phenotype. Examining embryogenetic dynamics from 200 to 400 min post-fertilization provides basic quantitative information on developmental tempo and process. To summarize, theory construction techniques are summarized and proposed as a way to rigorously interpret our data. Our proposed approach to a formal data representation that can provide critical links across life-history, anatomy and function.Entities:
Keywords: Caenorhabditis elegans; Computational biology; Data science; Developmental biology; Theoretical models
Mesh:
Year: 2021 PMID: 33449345 DOI: 10.1007/s12021-020-09508-1
Source DB: PubMed Journal: Neuroinformatics ISSN: 1539-2791