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EPIK: precise and scalable evolutionary placement with informative k-mers.
Bioinformatics. 2023 Dec 1;39(12):btad692. doi: 10.1093/bioinformatics/btad692.
Bioinformatics. 2023.
PMID: 37975872
Free PMC article.
Computing Phylo- k-Mers.
Romashchenko N, Linard B, Rivals E, Pardi F.
Romashchenko N, et al.
IEEE/ACM Trans Comput Biol Bioinform. 2023 Sep-Oct;20(5):2889-2897. doi: 10.1109/TCBB.2023.3278049. Epub 2023 Oct 9.
IEEE/ACM Trans Comput Biol Bioinform. 2023.
PMID: 37204943
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Rapid screening and detection of inter-type viral recombinants using phylo-k-mers.
Scholz GE, Linard B, Romashchenko N, Rivals E, Pardi F.
Scholz GE, et al. Among authors: romashchenko n.
Bioinformatics. 2021 Apr 1;36(22-23):5351-5360. doi: 10.1093/bioinformatics/btaa1020.
Bioinformatics. 2021.
PMID: 33331849
Free PMC article.
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PEWO: a collection of workflows to benchmark phylogenetic placement.
Linard B, Romashchenko N, Pardi F, Rivals E.
Linard B, et al. Among authors: romashchenko n.
Bioinformatics. 2021 Jan 29;36(21):5264-5266. doi: 10.1093/bioinformatics/btaa657.
Bioinformatics. 2021.
PMID: 32697844
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Generalising better: Applying deep learning to integrate deleteriousness prediction scores for whole-exome SNV studies.
Korvigo I, Afanasyev A, Romashchenko N, Skoblov M.
Korvigo I, et al. Among authors: romashchenko n.
PLoS One. 2018 Mar 14;13(3):e0192829. doi: 10.1371/journal.pone.0192829. eCollection 2018.
PLoS One. 2018.
PMID: 29538399
Free PMC article.
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