Name
Abstract | ||
|---|---|---|
Discovered gene regulation networks are very helpful to predict unknown gene functions. Microarray gene expression data reveals activation and deactivation relations among genes. There are evidences showing that multiple time units delay exist in a gene regulation process. Association rule mining technique is very suitable for finding regulation relations among genes. However, current association rule mining techniques can not handle temporally ordered transactions. We propose a modified association rule mining technique for efficiently discovering time-delayed regulation relationships among genes. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/HIS.2009.31 | HIS (1) |
Keywords | Field | DocType |
microarray gene expression data,pixel coloring,pseudo coloring,multiple time unit delay,color reference image,monochrome input image,gene regulation,finding time-delayed gene regulation,biology computing,apriori algorithm,microarray data,gene regulation process,luminance matching,time-delayed gene regulation pattern,data handling,data mining,modified association rule mining technique,dna,association rule mining,microarray,dna microarray data,proteins,association rules,gene expression | Data mining,Gene Regulation Process,Gene,Microarray,Biology,Apriori algorithm,Gene expression,Regulation of gene expression,Association rule learning,Microarray analysis techniques,Computational biology | Conference |
Volume | ISBN | Citations |
1 | 978-0-7695-3745-0 | 2 |
PageRank | References | Authors |
0.36 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huang-Cheng Kuo | 1 | 42 | 23.87 |
| Pei-Cheng Tsai | 2 | 2 | 0.36 |
| Jen-Peng Huang | 3 | 57 | 6.45 |