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LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2
View ORCID ProfileSizhen Li, View ORCID ProfileHe Zhang, View ORCID ProfileLiang Zhang, View ORCID ProfileKaibo Liu, View ORCID ProfileBoxiang Liu, View ORCID ProfileDavid H. Mathews, View ORCID ProfileLiang Huang
doi: https://doi.org/10.1101/2020.11.23.393488
Sizhen Li
aSchool of Electrical Engineering & Computer Science, Oregon State University, Corvallis, OR
He Zhang
bBaidu Research, Sunnyvale, CA
aSchool of Electrical Engineering & Computer Science, Oregon State University, Corvallis, OR
Liang Zhang
bBaidu Research, Sunnyvale, CA
aSchool of Electrical Engineering & Computer Science, Oregon State University, Corvallis, OR
Kaibo Liu
bBaidu Research, Sunnyvale, CA
Boxiang Liu
bBaidu Research, Sunnyvale, CA
David H. Mathews
dDepartment of Biochemistry & Biophysics, Center for RNA Biology, and Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, NY
Liang Huang
aSchool of Electrical Engineering & Computer Science, Oregon State University, Corvallis, OR
bBaidu Research, Sunnyvale, CA
Article usage
Posted September 29, 2021.
LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2
Sizhen Li, He Zhang, Liang Zhang, Kaibo Liu, Boxiang Liu, David H. Mathews, Liang Huang
bioRxiv 2020.11.23.393488; doi: https://doi.org/10.1101/2020.11.23.393488
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