RAFTS(3)G: an efficient and versatile clustering software to analyses in large protein datasets

BACKGROUND: Clustering methods are essential to partitioning biological samples being useful to minimize the information complexity in large datasets. Tools in this context usually generates data with greed algorithms that solves some Data Mining difficulties which can degrade biological relevant in...

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Detalles Bibliográficos
Autores principales: de Lima Nichio, Bruno Thiago, de Oliveira, Aryel Marlus Repula, de Pierri, Camilla Reginatto, Santos, Leticia Graziela Costa, Lejambre, Alexandre Quadros, Vialle, Ricardo Assunção, da Rocha Coimbra, Nilson Antônio, Guizelini, Dieval, Marchaukoski, Jeroniza Nunes, de Oliveira Pedrosa, Fabio, Raittz, Roberto Tadeu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631606/
https://www.ncbi.nlm.nih.gov/pubmed/31307371
http://dx.doi.org/10.1186/s12859-019-2973-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631606/
https://www.ncbi.nlm.nih.gov/pubmed/31307371
http://dx.doi.org/10.1186/s12859-019-2973-4

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