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Visual Data Mining of Biological Networks: One Size Does Not Fit All

High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often u...

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Detalles Bibliográficos
Autores principales: Pastrello, Chiara, Otasek, David, Fortney, Kristen, Agapito, Giuseppe, Cannataro, Mario, Shirdel, Elize, Jurisica, Igor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3547662/
https://www.ncbi.nlm.nih.gov/pubmed/23341759
http://dx.doi.org/10.1371/journal.pcbi.1002833
Descripción
Sumario:High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment. The resulting network needs to be able to focus on either the large-scale picture or on the more detailed small-scale subsets, depending on the research question and goals. In this tutorial, we illustrate a workflow useful to integrate, analyze, and visualize data from different sources, and highlight important features of tools to support such analyses.