MAGUS+eHMMs: Improved Multiple Sequence Alignment Accuracy for Fragmentary Sequences
Citation:
Shen, Chengze; Zaharias, Paul; Warnow, Tandy (2021): MAGUS+eHMMs: Improved Multiple Sequence Alignment Accuracy for Fragmentary Sequences. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2419626_V1
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Dataset Description

This dataset contains 1) the cleaned version of 11 CRW datasets, 2) RNASim10k dataset in high fragmentation and 3) three CRW datasets (16S.3, 16S.T, 16S.B.ALL) in high fragmentation.
Subject Life Sciences
Keywords MAGUS;UPP;Multiple Sequence Alignment;PASTA;eHMMs
License CC0
Funder U.S. National Science Foundation (NSF) - Grant: 2006069
Funder U.S. National Science Foundation (NSF) - Grant: 1458652
Corresponding Creator Chengze Shen
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Related Materials:
   Article Chengze Shen, Paul Zaharias, Tandy Warnow, MAGUS+eHMMs: Improved Multiple Sequence Alignment Accuracy for Fragmentary Sequences, Bioinformatics, 2021;, btab788, https://doi.org/10.1093/bioinformatics/btab788
   Article Shen, Chengze, Minhyuk Park, and Tandy Warnow. 2022. “WITCH: Improved Multiple Sequence Alignment Through Weighted Consensus Hidden Markov Model Alignment.” Journal of Computational Biology : A Journal of Computational Molecular Cell Biology, May. doi:10.1089/cmb.2021.0585.
Version DOI Comment Publication Date
1 10.13012/B2IDB-2419626_V1 2021-06-28
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