Cargando…
EnRICH: Extraction and Ranking using Integration and Criteria Heuristics
BACKGROUND: High throughput screening technologies enable biologists to generate candidate genes at a rate that, due to time and cost constraints, cannot be studied by experimental approaches in the laboratory. Thus, it has become increasingly important to prioritize candidate genes for experiments....
Autores principales: | Zhang, Xia, Greenlee, M Heather West, Serb, Jeanne M |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3564850/ https://www.ncbi.nlm.nih.gov/pubmed/23320748 http://dx.doi.org/10.1186/1752-0509-7-4 |
Ejemplares similares
-
Mouse Retinal Development: a Dark Horse Model for Systems Biology Research
por: Zhang, Xia, et al.
Publicado: (2011) -
GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
por: Eden, Eran, et al.
Publicado: (2009) -
RankAggreg, an R package for weighted rank aggregation
por: Pihur, Vasyl, et al.
Publicado: (2009) -
Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries
por: Serb, Jeanne M., et al.
Publicado: (2010) -
SuRankCo: supervised ranking of contigs in de novo assemblies
por: Kuhring, Mathias, et al.
Publicado: (2015)