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SIMON: Open-Source Knowledge Discovery Platform

Data analysis and knowledge discovery has become more and more important in biology and medicine with the increasing complexity of biological datasets, but the necessarily sophisticated programming skills and in-depth understanding of algorithms needed pose barriers to most biologists and clinicians...

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Detalles Bibliográficos
Autores principales: Tomic, Adriana, Tomic, Ivan, Waldron, Levi, Geistlinger, Ludwig, Kuhn, Max, Spreng, Rachel L., Dahora, Lindsay C., Seaton, Kelly E., Tomaras, Georgia, Hill, Jennifer, Duggal, Niharika A., Pollock, Ross D., Lazarus, Norman R., Harridge, Stephen D.R., Lord, Janet M., Khatri, Purvesh, Pollard, Andrew J., Davis, Mark M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815964/
https://www.ncbi.nlm.nih.gov/pubmed/33511368
http://dx.doi.org/10.1016/j.patter.2020.100178
Descripción
Sumario:Data analysis and knowledge discovery has become more and more important in biology and medicine with the increasing complexity of biological datasets, but the necessarily sophisticated programming skills and in-depth understanding of algorithms needed pose barriers to most biologists and clinicians to perform such research. We have developed a modular open-source software, SIMON, to facilitate the application of 180+ state-of-the-art machine-learning algorithms to high-dimensional biomedical data. With an easy-to-use graphical user interface, standardized pipelines, and automated approach for machine learning and other statistical analysis methods, SIMON helps to identify optimal algorithms and provides a resource that empowers non-technical and technical researchers to identify crucial patterns in biomedical data.