Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Computational Approaches to Supporting Large-Scale Analysis of Photoreceptor-Enriched Gene Expression

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

3 Author(s)
Haiying Wang ; Sch. of Comput. & Mathematics, Ulster Univ. ; Huiru Zheng ; Azuaje, F.

Retinal photoreceptor cells are responsible for light detection and phototransduction. The understanding of molecular mechanisms regulating photoreceptor gene expression during retinal development may have important implications in clinical neuroscience. Using self-adaptive neural networks and pattern validation statistical tools, this paper explores large-scale analysis of photoreceptor gene expression. Based on the analysis of data generated by serial analysis of gene expression (SA GE) in the developing mouse retina, significant expression patterns for the in silico detection of photoreceptor-enriched genes were revealed. This study demonstrates how machine learning and statistical techniques may be effectively combined to detect key complex relationships encoded in SA GE data. Such approaches may support inexpensive functional predictions prior to the application of experimental methodologies

Published in:

Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on

Date of Conference:

0-0 0