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SIMON: Open-Source Knowledge Discovery Platform
Author(s) -
Adriana Tomić,
Ivan Tomic,
Levi Waldron,
Ludwig Geistlinger,
Max Kühn,
Rachel L. Spreng,
Lindsay C. Dahora,
Kelly E. Seaton,
Georgia D. Tomaras,
Jennifer Hill,
Niharika A. Duggal,
Ross D. Pollock,
Norman R. Lazarus,
Stephen D. R. Harridge,
Janet M. Lord,
Purvesh Khatri,
Andrew J. Pollard,
Mark M. Davis
Publication year - 2021
Publication title -
patterns
Language(s) - English
Resource type - Journals
ISSN - 2666-3899
DOI - 10.1016/j.patter.2020.100178
Subject(s) - computer science , data science , modular design , open source , software , resource (disambiguation) , interface (matter) , machine learning , artificial intelligence , software engineering , programming language , bubble , maximum bubble pressure method , parallel computing , computer network
Summary 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.

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