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inFRank: a ranking-based identification of influential genes in biological networks
Capturing the predominant driver genes is critical in the analysis of high-throughput experimental data; however, existing methods scarcely include the unique characters of biological networks. Herein we introduced a ranking-based computational framework (inFRank) to rank the proteins by their influ...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Impact Journals LLC
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5546442/ https://www.ncbi.nlm.nih.gov/pubmed/27623074 http://dx.doi.org/10.18632/oncotarget.11878 |