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» Analyzing time series gene expression data
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CIBCB
2005
IEEE
14 years 1 months ago
Artificial Neural Network Analysis of DNA Microarray-based Prostate Cancer Recurrence
— DNA microarray-based gene expression profiles have been established for a variety of adult cancers. This paper addresses application of an artificial neural network (ANN) wit...
Leif E. Peterson, Mustafa Ozen, Halime Erdem, Andr...
BMCBI
2010
135views more  BMCBI 2010»
13 years 7 months ago
Efficient genome-scale phylogenetic analysis under the duplication-loss and deep coalescence cost models
Background: Genomic data provide a wealth of new information for phylogenetic analysis. Yet making use of this data requires phylogenetic methods that can efficiently analyze extr...
Mukul S. Bansal, J. Gordon Burleigh, Oliver Eulens...
BMCBI
2008
130views more  BMCBI 2008»
13 years 7 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...
BMCBI
2010
121views more  BMCBI 2010»
13 years 2 months ago
G-stack modulated probe intensities on expression arrays - sequence corrections and signal calibration
Background: The brightness of the probe spots on expression microarrays intends to measure the abundance of specific mRNA targets. Probes with runs of at least three guanines (G) ...
Mario Fasold, Peter F. Stadler, Hans Binder
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