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...

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Detalles Bibliográficos
Autores principales: Cui, Xiuliang, Li, Xiaofeng, Li, Jing, Wang, Xue, Sun, Wen, Cheng, Zhuo, Ding, Jin, Wang, Hongyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Research Paper
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

Internet

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

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