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» Gene set analysis using principal components
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BMCBI
2008
158views more  BMCBI 2008»
13 years 11 months ago
Discovering gene annotations in biomedical text databases
Currently, most of the discovered biological and biomedical knowledge is available as textual data in scientific papers. And, locating and curating information about a genomic enti...
Ali Cakmak, Gultekin Özsoyoglu
ESANN
2008
14 years 7 days ago
Discrimination of regulatory DNA by SVM on the basis of over- and under-represented motifs
In this paper we apply three pattern recognition methods (support vector machine, cluster analysis and principal component analysis) to distinguish regulatory regions from coding a...
Rene te Boekhorst, Irina I. Abnizova, Lorenz Werni...
IJCNN
2000
IEEE
14 years 3 months ago
ICA for Noisy Neurobiological Data
ICA (Independent Component Analysis) is a new technique for analyzing multi-variant data. Lots of results are reported in the field of neurobiological data analysis such as EEG (...
Shiro Ikeda, Keisuke Toyama
BMCBI
2010
172views more  BMCBI 2010»
13 years 11 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
BMCBI
2011
13 years 5 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso