Name
Title | ||
|---|---|---|
SlopeMiner: An Improved Method for Mining Subtle Signals in Time Course Microarray Data |
Abstract | ||
|---|---|---|
This paper presents an improved method, SlopeMiner, for analyzing time course microarray data by identifying genes that undergo gradual transitions in expression level. The algorithm calculates the slope for the slow transition between the expression levels of data, matching the sequence of expression level for each gene against temporal patterns having one transition between two expression levels. The method, when used along with StepMiner -an existing method for extracting binary signals, significantly increases the annotation accuracy. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-69311-6_6 | FAW |
Keywords | Field | DocType |
binary signal,mining subtle signals,improved method,slow transition,existing method,time course microarray data,gradual transition,expression level,annotation accuracy,temporal pattern,dna microarray,microarray data,regression,data mining | Data mining,Gene,Annotation,Regression,Biology,Microarray analysis techniques,Computational biology,Gene chip analysis,DNA microarray,Binary number | Conference |
Volume | ISSN | Citations |
5059 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kevin Mccormick | 1 | 0 | 0.34 |
| Roli Shrivastava | 2 | 0 | 0.34 |
| Li Liao | 3 | 364 | 34.05 |