A computational model of planarian regeneration. Issue 4 (4th July 2017)

• Record Type: Journal Article
• Authors: De, Abhishek; Chakravarthy, V. Srinivasa; Levin, Michael
• Is Part Of: International journal of parallel, emergent and distributed systems. Volume 32:Issue 4(2017)
• Page Start: 331
• Page End: 347
• Publication Date: 2017-07-04
• Subjects: Planaria -- regeneration -- modeling -- in silico; Parallel computers -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Computer algorithms -- Periodicals; 004.35
• DOI: 10.1080/17445760.2016.1185521
• Languages: English
• ISSNs: 1744-5760

Abstract

Abstract: Regeneration of complex anatomical structures is an emergent phenomenon arising from complex interplay between various underlying cellular components and processes. It is still largely unclear how coordination among cells leads to accurate regeneration of the organism, preserving the location, shape, and composition of the parts with respect to the whole. Here, we examine at the global interaction of cells in a computational model of planarian regeneration. A key feature of our model is the integration of multiple organizational levels of an organism – from cells, to network, to global shape. The computational model is able to replicate most of the experimental observations thereby facilitating study of the putative mechanisms. We observe that a hierarchical interplay between local and long range signaling acts as a positional map that guides the cellular fate at any position. Furthermore, we have quantified the quality of regeneration using a metric that provides a sense of how well the regenerated organism resembles its original shape. Abstract : Planaria are complex bilaterian animals with a remarkable capability. They regenerate after almost any sort of surgical damage, re-growing precisely the needed structures at the correct locations and stopping growth and remodeling after their target morphology is complete. Understanding the dynamic regulation of biological patterning is key to transformative advances in regenerative medicine and synthetic bioengineering. Here, we propose a connectionist model of pattern memory during planarian regeneration.