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RECOMB
2002
Springer
14 years 6 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
BIBE
2001
IEEE
188views Bioinformatics» more  BIBE 2001»
13 years 9 months ago
Interrelated Two-way Clustering: An Unsupervised Approach for Gene Expression Data Analysis
DNA arrays can be used to measure the expression levels of thousands of genes simultaneously. Currently most research focuses on the interpretation of the meaning of the data. How...
Chun Tang, Li Zhang, Aidong Zhang, Murali Ramanath...
KDD
2003
ACM
152views Data Mining» more  KDD 2003»
14 years 6 months ago
Interactive exploration of coherent patterns in time-series gene expression data
Discovering coherent gene expression patterns in time-series gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we pr...
Daxin Jiang, Jian Pei, Aidong Zhang
BIODATAMINING
2008
178views more  BIODATAMINING 2008»
13 years 5 months ago
Clustering-based approaches to SAGE data mining
Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical appli...
Haiying Wang, Huiru Zheng, Francisco Azuaje
BMCBI
2011
13 years 24 days ago
Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in i
Background: In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focuse...
Paolo G. V. Martini, Davide Risso, Gabriele Sales,...