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Bioinformatics Advance Access published online on March 7, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl082
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received September 23, 2005
Revised March 1, 2006
Accepted March 3, 2006

Article

Constructing quantitative models from qualitative mutant phenotypes: preferences in selecting sensory organ precursors

Chao-Ping Hsu 1 *, Pei-Hsuan Lee 2, Ching-Wei Chang 2, and Cheng-Tsung Lee 2

1 Institute of Chemistry, Academia Sinica, 128 Section 2 Academia Road, Nankang, Taipei, 115 Taiwan; Institute of Molecular Sciences, National Chiao-Tung University, 1001 Ta Hsueh Road, Hsinchu, 300 Taiwan
2 Institute of Chemistry, Academia Sinica, 128 Section 2 Academia Road, Nankang, Taipei, 115 Taiwan

* To whom correspondence should be addressed.
Chao-Ping Hsu, E-mail: cherri{at}sinica.edu.tw


  Abstract

Motivation: To study biology from the systems level, mathematical models that describe the time-evolution of the system offer useful insights. Quantitative information is required for constructing such models, but such information is rarely provided.

Results: We propose a scheme -- based on random searches over a parameter space, according to criteria set by qualitative experimental observations -- for inferring quantitative parameters from qualitative experimental results. We used five mutant constraints toconstruct genetic network models for sensory organ precursor formation in Drosophila development. Most of the models were capable of generating expression patterns for the gene Enhancer of split that were compatible with experimental observations for wild type and two Notch mutants. We further examined factors differentiating the neural fate among cells in a proneural cluster, and found two opposite driving forces that bias the choice between middle cells and the peripheral cells. Therefore, it is possible to build numerical models from mutant screening and to study mechanisms behind the complicated network.

Associate Editor: Alfonso Valencia
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