Gene Regulatory Networks Reconstruction Using the Flooding-Pruning Hill-Climbing Algorithm

The explosion of genomic data provides new opportunities to improve the task of gene regulatory network reconstruction. Because of its inherent probability character, the Bayesian network is one of the most promising methods. However, excessive computation time and the requirements of a large number...

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Detalles Bibliográficos
Autores principales: Xing, Linlin, Guo, Maozu, Liu, Xiaoyan, Wang, Chunyu, Zhang, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6071145/
https://www.ncbi.nlm.nih.gov/pubmed/29986472
http://dx.doi.org/10.3390/genes9070342

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6071145/
https://www.ncbi.nlm.nih.gov/pubmed/29986472
http://dx.doi.org/10.3390/genes9070342

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