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BMCBI
2010
143views more  BMCBI 2010»
14 years 9 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 3 months ago
A Computational Approach to Reconstructing Gene Regulatory Networks
Reverse-engineering of gene networks using linear models often results in an underdetermined system because of excessive unknown parameters. In addition, the practical utility of ...
Xutao Deng, Hesham H. Ali
BMCBI
2008
179views more  BMCBI 2008»
14 years 9 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao
KDD
2003
ACM
133views Data Mining» more  KDD 2003»
15 years 10 months ago
Interactive Analysis of Gene Interactions Using Graphical gaussian model
DNA microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Xintao Wu, Yong Ye, Kalpathi R. Subramanian
BMCBI
2010
172views more  BMCBI 2010»
14 years 9 months ago
Comparison of evolutionary algorithms in gene regulatory network model inference
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Alina Sîrbu, Heather J. Ruskin, Martin Crane