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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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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2010
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3247861/ https://ncbi.nlm.nih.gov/pubmed/20961418 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-11-522 |
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