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Prospects for recurrent neural network models to learn RNA biophysics from high-throughput data
View ORCID ProfileMichelle J Wu, Johan OL Andreasson, Wipapat Kladwang, William J Greenleaf, Eterna participants, Rhiju Das
doi: https://doi.org/10.1101/227611
Michelle J Wu
1Biomedical Informatics Training Program, Stanford University School of Medicine
Johan OL Andreasson
2Department of Biochemistry, Stanford University School of Medicine
3Department of Genetics, Stanford University School of Medicine
Wipapat Kladwang
2Department of Biochemistry, Stanford University School of Medicine
William J Greenleaf
3Department of Genetics, Stanford University School of Medicine
4Department of Applied Physics, Stanford University
Rhiju Das
2Department of Biochemistry, Stanford University School of Medicine
5Department of Physics, Stanford University
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Posted December 01, 2017.
Prospects for recurrent neural network models to learn RNA biophysics from high-throughput data
Michelle J Wu, Johan OL Andreasson, Wipapat Kladwang, William J Greenleaf, Eterna participants, Rhiju Das
bioRxiv 227611; doi: https://doi.org/10.1101/227611
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