Cargando…
RegNetB: Predicting Relevant Regulator-Gene Relationships in Localized Prostate Tumor Samples
BACKGROUND: A central question in cancer biology is what changes cause a healthy cell to form a tumor. Gene expression data could provide insight into this question, but it is difficult to distinguish between a gene that causes a change in gene expression from a gene that is affected by this change....
Autores principales: | Alvarez, Angel, Woolf, Peter J |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3128037/ https://www.ncbi.nlm.nih.gov/pubmed/21682879 http://dx.doi.org/10.1186/1471-2105-12-243 |
Ejemplares similares
-
ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate
por: Shao, Wei, et al.
Publicado: (2020) -
Linking Cytoscape and the corynebacterial reference database CoryneRegNet
por: Baumbach, Jan, et al.
Publicado: (2008) -
CoRegNet: reconstruction and integrated analysis of co-regulatory networks
por: Nicolle, Rémy, et al.
Publicado: (2015) -
netReg: network-regularized linear models for biological association studies
por: Dirmeier, Simon, et al.
Publicado: (2018) -
CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks
por: Baumbach, Jan, et al.
Publicado: (2006)