Title
Cell Trajectory Clustering: Towards The Automated Identification Of Morphogenetic Fields In Animal Embryogenesis
Abstract
The recent availability of complete cell lineages from live imaging data opens the way to novel methodologies for the automated analysis of cell dynamics in animal embryogenesis. We propose a method for the calculation of measure-based dissimilarities between cells. These dissimilarity measures allow the use of clustering algorithms for the inference of time-persistent patterns. The method is applied to the digital cell lineages reconstructed from live zebrafish embryos imaged from 6 to 13 hours post fertilization. We show that the position and velocity of cells are sufficient to identify relevant morphological features including bilateral symmetry and coherent cell domains. The method is flexible enough to readily integrate larger sets of measures opening the way to the automated identification of morphogenetic fields.
Year
DOI
Venue
2017
10.5220/0006259407460752
ICPRAM: PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS
Keywords
Field
DocType
Animal Embryogenesis, Cell Lineage, Clustering, Path Integrals
Morphogenetic field,Pattern recognition,Computer science,Inference,Zebrafish,Trajectory clustering,Cell,Artificial intelligence,Cluster analysis,Embryogenesis,Live cell imaging
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Juan Raphael Diaz Simões100.34
Paul Bourgine218026.10
Denis Grebenkov300.34
Nadine Peyriéras451.72