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SAC
2004
ACM
14 years 1 months ago
Time-frequency feature detection for time-course microarray data
Gene clustering based on microarray data provides useful functional information to the working biologists. Many current gene-clustering algorithms rely on Euclidean-based distance...
Jiawu Feng, Paolo Emilio Barbano, Bud Mishra
BMCBI
2008
259views more  BMCBI 2008»
13 years 7 months ago
DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcripti
Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted w...
Evert-Jan Blom, Sacha A. F. T. van Hijum, Klaas J....
BMCBI
2011
12 years 11 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence
BMCBI
2006
140views more  BMCBI 2006»
13 years 7 months ago
Feature selection using Haar wavelet power spectrum
Background: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical m...
Prabakaran Subramani, Rajendra Sahu, Shekhar Verma
BMCBI
2007
135views more  BMCBI 2007»
13 years 7 months ago
Measuring similarities between gene expression profiles through new data transformations
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...