Paper Info
Title
A novel dynamic graph-based computational model for predicting salivary gland branching morphogenesis
Abstract
In this paper, we introduce a biologically motivated dynamic graph-based growth model to describe and predict the stages of cleft formation during the process of branching morphogenesis in the submandibular mouse gland (SMG) from 3 hrs after embryonic day E12 to 8 hrs after embryonic day E12, which can be considered as E12.5. Branching morphogenesis is the process by which many mammalian exocrine and endocrine glands undergo significant morphological transformations, from a primary bud to an adult organ. Although many studies have investigated the cellular and molecular mechanisms driving branching morphogenesis, it is not clear how the shape changes that are inherent to establishing organ structure are produced. Using morphological features extracted from sequential images of SMG organ cultures we were able to develop a dynamic graph-based predictive model that is able to mimic the process of cleft formation and predict the final state. In addition, we compare our model to a state-of-the-art Glazier-Graner-Hogeweg (GGH) simulative tool, and demonstrate that the dynamic graph-based predictive model has comparable accuracy in modeling growth of clefts across SMG developmental stages, as well as faster convergence to the target SMG morphology.
Year
DOI
Venue
2012
10.1109/BIBM.2012.6392680
BIBM
Keywords
DocType
Citations 
SMG developmental stage,organ structure,embryonic day E12,salivary gland,dynamic graph-based growth model,cleft formation,dynamic graph-based predictive model,embryonic day,target SMG morphology,SMG organ culture,adult organ,novel dynamic graph-based computational
Conference
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Lauren Bange100.34
Daniel Yuan281.14
Shayoni Ray381.48
Melinda Larsen481.14
Abiurami Baskaran500.34
Basak Oztan66410.31
Bülent Yener7107594.51
Nimit Dhulekar8143.08