By Topic

Multicellular pattern formation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hohm, T. ; Comput. Eng. & Networks Lab., Zurich, Switzerland ; Zitzler, E.

Understanding the self-regulatory mechanisms controlling the spatial and temporal structure of multicellular organisms represents one of the major challenges in molecular biology. Although high-throughput data have become available with the advances in experimental technologies at a large scale, measuring gene expression levels at a high spatial resolution remains extremely difficult. As a result, the study of genetic regulatory networks in the light of spatial expression patterns still relies mainly on qualitative data. This leads to the question of how to fit the parameters of a gene regulatory network model such that a purely qualitatively defined pattern can be reproduced. This article addresses this issue and presents a general approach to generate patterns reflecting basic geometric shapes. In combination with an appropriate ordinary differential equation (ODE)-based modeling and simulation framework, a formalism to quantify qualitative patterns and integrate this concept into an evolutionary algorithm for parameter estimation is presented and tested for stripe-like patterns on two test systems.

Published in:

Engineering in Medicine and Biology Magazine, IEEE  (Volume:28 ,  Issue: 4 )