Output details
11 - Computer Science and Informatics
University of Oxford
Article title
A Bayesian model predicts the response of axons to molecular gradients
Type
D - Journal article
Title of journal
Proceedings of the National Academy of Sciences of the United States of America
Article number
-
Volume number
106
Issue number
25
First page of article
10296
ISSN of journal
0027-8424
Year of publication
2009
Number of additional authors
9
Additional information
<28>
Axon guidance by molecular gradients plays a crucial role in wiring the nervous system, but mechanisms are largely unknown. This article in PNAS, featured as a cover image, develops for the first time a Bayesian “ideal observer” analysis of axon gradient detection. Experiments and simulations demonstrate a degree of sensitivity much higher than previously reported for chemotacting systems, revealing the quantitative constraints needed for effective axonal guidance and the computational principles used by signal transduction pathways.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
40
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
