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SIMON: Open-Source Knowledge Discovery Platform

delete2021-01-01
delete12
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OA
AI
A
Adriana Tomić *
I
Ivan Tomic *
L
Levi Waldron
L
Ludwig Geistlinger
M
Max Kühn
R
Rachel L. Spreng
L
Lindsay C. Dahora
K
Kelly E. Seaton
G
Georgia D. Tomaras
J
Jennifer Hill
N
Niharika A. Duggal
R
Ross D. Pollock
N
Norman R. Lazarus
S
Stephen D. R. Harridge
J
Janet M. Lord
P
Purvesh Khatri
A
Andrew J. Pollard
M
Mark M. Davis *
DOI:10.1016/j.patter.2020.100178delete
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Abstract

Abstract

En 中文
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 indepth 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-touse 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.
Keywords:
MACHINE LEARNING APPLICATIONS
SALMONELLA-TYPHI
MASS CYTOMETRY
EXPRESSION
PREDICTION
VACCINE
IMMUNE

Journal

Patterns cover
Patterns
IF:
7.4
Papers:
954
Citations:
5.5K

Organization

S
Stanford University
Scholars:
5.8K
Papers: 1.9K
Citations: 7.9W
D
Duke University
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2.1K
Papers: 820
Citations: 3.6W
U
University of Oxford
Scholars:
5.6K
Papers: 2.0K
Citations: 6.7W
C
city university of new york (cuny) system
Scholars:
0
Papers: 428
Citations: 8.0K
U
University of London
Scholars:
1.7K
Papers: 724
Citations: 12.5W
U
University of Birmingham
Scholars:
1.6K
Papers: 731
Citations: 2.4W
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Cited Papers

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