Name
Title | ||
|---|---|---|
Multiobjective triclustering of time-series transcriptome data reveals key genes of biological processes. |
Abstract | ||
|---|---|---|
Exploratory analysis of multi-dimensional high-throughput datasets, such as microarray gene expression time series, may be instrumental in understanding the genetic programs underlying numerous biological processes. In such datasets, variations in the gene expression profiles are usually observed across replicates and time points. Thus mining the temporal expression patterns in such multi-dimensional datasets may not only provide insights into the key biological processes governing organs to grow and develop but also facilitate the understanding of the underlying complex gene regulatory circuits. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1186/s12859-015-0635-8 | BMC Bioinformatics |
Keywords | Field | DocType |
Microarray gene expression data, Developmental biology, Tricluster, Multi-objective optimization, Eigen gene, Affirmation score, TRANSFAC | Gene,Biology,Transcriptome,Datasets as Topic,Microarray gene expression,Bioinformatics,Genetics,Gene regulatory network,TRANSFAC,Gene expression profiling,DNA microarray | Journal |
Volume | Issue | ISSN |
16 | 1 | 1471-2105 |
Citations | PageRank | References |
4 | 0.42 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anirban Bhar | 1 | 12 | 1.25 |
| Martin Haubrock | 2 | 439 | 44.78 |
| Anirban Mukhopadhyay | 3 | 711 | 50.07 |
| Edgar Wingender | 4 | 1975 | 322.27 |