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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.

Original publication

DOI

10.1016/j.patter.2020.100178

Type

Journal article

Journal

Patterns (N Y)

Publication Date

08/01/2021

Volume

2

Keywords

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