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CIBCB
2007
IEEE
13 years 11 months ago
Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Ji He, Xinbin Dai, Xuechun Zhao
BMCBI
2007
126views more  BMCBI 2007»
13 years 7 months ago
Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation
Background: Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation...
Gunnar Schramm, Marc Zapatka, Roland Eils, Rainer ...
MICCAI
2004
Springer
14 years 8 months ago
Landmark-Driven, Atlas-Based Segmentation of Mouse Brain Tissue Images Containing Gene Expression Data
To better understand the development and function of the mammalian brain, researchers have begun to systematically collect a large number of gene expression patterns throughout the...
Ioannis A. Kakadiaris, Musodiq Bello, Shiva Arunac...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
APBC
2004
138views Bioinformatics» more  APBC 2004»
13 years 9 months ago
Whole-Genome Functional Classification of Genes by Latent Semantic Analysis on Microarray Data
Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. The resulti...
See-Kiong Ng, Zexuan Zhu, Yew-Soon Ong