Document Detail

The simplicity of metazoan cell lineages.
MedLine Citation:
PMID:  15650738     Owner:  NLM     Status:  MEDLINE    
Developmental processes are thought to be highly complex, but there have been few attempts to measure and compare such complexity across different groups of organisms. Here we introduce a measure of biological complexity based on the similarity between developmental and computer programs. We define the algorithmic complexity of a cell lineage as the length of the shortest description of the lineage based on its constituent sublineages. We then use this measure to estimate the complexity of the embryonic lineages of four metazoan species from two different phyla. We find that these cell lineages are significantly simpler than would be expected by chance. Furthermore, evolutionary simulations show that the complexity of the embryonic lineages surveyed is near that of the simplest lineages evolvable, assuming strong developmental constraints on the spatial positions of cells and stabilizing selection on cell number. We propose that selection for decreased complexity has played a major role in moulding metazoan cell lineages.
Ricardo B R Azevedo; Rolf Lohaus; Volker Braun; Markus Gumbel; Muralikrishna Umamaheshwar; Paul-Michael Agapow; Wouter Houthoofd; Ute Platzer; Gaëtan Borgonie; Hans-Peter Meinzer; Armand M Leroi
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Nature     Volume:  433     ISSN:  1476-4687     ISO Abbreviation:  Nature     Publication Date:  2005 Jan 
Date Detail:
Created Date:  2005-01-14     Completed Date:  2005-01-24     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  0410462     Medline TA:  Nature     Country:  England    
Other Details:
Languages:  eng     Pagination:  152-6     Citation Subset:  IM    
Department of Biology and Biochemistry, University of Houston, Houston, Texas 77204-5001, USA.
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MeSH Terms
Caenorhabditis elegans / cytology,  embryology
Cell Lineage*
Computer Simulation
Models, Biological
Rhabditoidea / cytology*,  embryology*
Urochordata / cytology*,  embryology*

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