Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs

BACKGROUND: Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the interpretation of these networks. While most research focuses on the unipartite or bipartite case, we address the more general...

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Detalles Bibliográficos
Autores principales: Hartsperger, Mara L, Blöchl, Florian, Stümpflen, Volker, Theis, Fabian J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3247861/
https://www.ncbi.nlm.nih.gov/pubmed/20961418
http://dx.doi.org/10.1186/1471-2105-11-522

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3247861/
https://www.ncbi.nlm.nih.gov/pubmed/20961418
http://dx.doi.org/10.1186/1471-2105-11-522

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