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DNetPRO: A network approach for low-dimensional signatures from high-throughput data

View ORCID ProfileNico Curti, Enrico Giampieri, Giuseppe Levi, Gastone Castellani, Daniel Remondini
doi: https://doi.org/10.1101/773622
Nico Curti
1Department of Physics and Astronomy, University of Bologna
3INFN Bologna
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  • ORCID record for Nico Curti
  • For correspondence: nico.curti2@unibo.it
Enrico Giampieri
2Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna
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Giuseppe Levi
1Department of Physics and Astronomy, University of Bologna
3INFN Bologna
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Gastone Castellani
1Department of Physics and Astronomy, University of Bologna
3INFN Bologna
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Daniel Remondini
1Department of Physics and Astronomy, University of Bologna
3INFN Bologna
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  • https://github.com/Nico-Curti/DNetPRO

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Posted September 19, 2019.
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DNetPRO: A network approach for low-dimensional signatures from high-throughput data
Nico Curti, Enrico Giampieri, Giuseppe Levi, Gastone Castellani, Daniel Remondini
bioRxiv 773622; doi: https://doi.org/10.1101/773622
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DNetPRO: A network approach for low-dimensional signatures from high-throughput data
Nico Curti, Enrico Giampieri, Giuseppe Levi, Gastone Castellani, Daniel Remondini
bioRxiv 773622; doi: https://doi.org/10.1101/773622

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