Cluster analysis for gene expression data: a survey
University at Buffalo, State University of New York · New York University · +1 more institution
Abstract
DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increases the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural…
Citation impact
- FWCI
- 14.34
- Percentile
- 100%
- References
- 151
Authors
3- DJDaxin JiangCorresponding
University at Buffalo, State University of New York, New York University, State University of New York
- CTChun Tang
New York University, State University of New York, University at Buffalo, State University of New York
- AZAidong Zhang
University at Buffalo, State University of New York, New York University, State University of New York
Topics & keywords
- Cluster analysis
- Computer science
- Data mining
- Partition (number theory)
- Expression (computer science)
- Gene expression profiling
- Consensus clustering
- DNA microarray