Title
Systematic Gene Function Prediction Using a Fuzzy Nearest-Cluster Method on Gene Expression Data
Abstract
Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarrays. However, there are still gaps toward whole-genome functional annotation of genes using gene expression data. In this paper, we propose a novel technique called fuzzy nearest clusters for functional annotation of unclassified genes. The technique consists of two steps: a hierarchical clustering step to detect homogeneous co-expressed gene clusters in each possibly heterogeneous functional class; followed by a classification step to predict the functional roles of unclassified genes based on their similarities to these clusters. Our experimental results with yeast gene expression data showed that the proposed method can accurately predict the genes' functions, even those with multiple functional roles, and the performance is most independent of the heterogeneity of the complex functional classes, as compared to other approaches
Year
DOI
Venue
2006
10.1109/IMSCCS.2006.131
Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums
Keywords
Field
DocType
microarray technology,fuzzy set theory,wholegenome functional annotation,homogeneous co-expressed gene cluster,pattern clustering,expression level,genetics,multiple functional role,functional annotation,functional role,biology computing,fuzzy nearest-cluster method,complex functional class,yeast gene expression data,gene expression data,systematic gene function prediction,heterogeneous functional class,unclassified gene,hierarchical clustering,genomics,classification algorithms,gene cluster,bioinformatics,couplings,biology,throughput,fuzzy systems,clustering algorithms,gene expression,prediction algorithms
Hierarchical clustering,Data mining,Gene,Computer science,Genomics,Fuzzy set,Gene chip analysis,Computational biology,Cluster analysis,Statistical classification,DNA microarray
Conference
Volume
ISBN
Citations 
1
0-7695-2581-4
9
PageRank 
References 
Authors
0.56
14
3
Name
Order
Citations
PageRank
Minh Nhut Nguyen11837112.04
Cheston Tan215515.27
See-Kiong Ng365747.82