Name
Title | ||
|---|---|---|
Interactive knowledge discovery and data mining on genomic expression data with numeric formal concept analysis. |
Abstract | ||
|---|---|---|
The GED analysis problem gets transformed into the exploration of a sequence of lattices enabling the visualization of the hierarchical structure of the biclusters with a certain degree of granularity. The ability of FCA-based bi-clustering methods to index external databases such as GO allows us to obtain a quality measure of the biclusters, to observe the evolution of a gene throughout the different biclusters it appears in, to look for relevant biclusters-by observing their genes and what their persistence is-to infer, for instance, hypotheses on their function. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12859-016-1234-z | BMC bioinformatics |
Keywords | Field | DocType |
Biclustering,Data mining,Exploratory data analysis,Formal concept analysis,Gene expression data,Gene set enrichment,Knowledged discovery | Data science,Data mining,Gene ontology,Computer science,Genomics,Knowledge extraction,Biclustering,Bioinformatics,Exploratory data analysis,Formal concept analysis | Journal |
Volume | Issue | ISSN |
17 | 1 | 1471-2105 |
Citations | PageRank | References |
1 | 0.36 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José María Fernández-Calabozo | 1 | 1 | 0.36 |
| Francisco J. Valverde-Albacete | 2 | 116 | 20.84 |
| Carmen Peláez-moreno | 3 | 130 | 22.07 |