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In Patterns (New York, N.Y.)

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.

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


artificial intelligence, autoML, bioinformatics, computational biology, data mining, data science, machine learning, software, systems biology