Extension of the viral ecology in humans using viral profile hidden Markov models.
Extension of the viral ecology in humans using viral profile hidden Markov models.
复制标题
使用病毒剖面隐藏的马尔可夫模型在人类中的病毒生态扩展。
DOI:
10.1371/journal.pone.0190938
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发表时间:
2018
期刊:
影响因子:
3.7
通讯作者:
Dillner J
中科院分区:
文献类型:
--
作者:
Bzhalava Z;Hultin E;Dillner J
When human samples are sequenced, many assembled contigs are “unknown”, as conventional alignments find no similarity to known sequences. Hidden Markov models (HMM) exploit the positions of specific nucleotides in protein-encoding codons in various microbes. The algorithm HMMER3 implements HMM using a reference set of sequences encoding viral proteins, “vFam”. We used HMMER3 analysis of “unknown” human sample-derived sequences and identified 510 contigs distantly related to viruses (Anelloviridae (n = 1), Baculoviridae (n = 34), Circoviridae (n = 35), Caulimoviridae (n = 3), Closteroviridae (n = 5), Geminiviridae (n = 21), Herpesviridae (n = 10), Iridoviridae (n = 12), Marseillevirus (n = 26), Mimiviridae (n = 80), Phycodnaviridae (n = 165), Poxviridae (n = 23), Retroviridae (n = 6) and 89 contigs related to described viruses not yet assigned to any taxonomic family). In summary, we find that analysis using the HMMER3 algorithm and the “vFam” database greatly extended the detection of viruses in biospecimens from humans.
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影响因子:
3.4
作者:
Delaroque, Nicolas;Boland, Wilhelm
通讯作者:
Boland, Wilhelm
影响因子:
5.5
作者:
Koonin, Eugene V.;Senkevich, Tatiana G.;Dolja, Valerian V.
通讯作者:
Dolja, Valerian V.
影响因子:
5.6
作者:
KROGH, A;BROWN, M;HAUSSLER, D
通讯作者:
HAUSSLER, D
DOI:
10.1073/pnas.1110889108
发表时间:
2011-10-18
影响因子:
11.1
作者:
Arslan, Defne;Legendre, Matthieu;Claverie, Jean-Michel
通讯作者:
Claverie, Jean-Michel
影响因子:
3.7
作者:
Foulongne, Vincent;Sauvage, Virginie;Eloit, Marc
通讯作者:
Eloit, Marc