Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Pablo Millán Arias"'
Autor:
Pablo Millán Arias, Joseph Butler, Gurjit S. Randhawa, Maximillian P. M. Soltysiak, Kathleen A. Hill, Lila Kari
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-17 (2023)
Abstract This study provides comprehensive quantitative evidence suggesting that adaptations to extreme temperatures and pH imprint a discernible environmental component in the genomic signature of microbial extremophiles. Both supervised and unsuper
Externí odkaz:
https://doaj.org/article/56fb5a049eb646439b7bb451d9bde39e
Publikováno v:
PLoS ONE, Vol 17, Iss 1 (2022)
We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of prim
Externí odkaz:
https://doaj.org/article/ba2a0c335f55448cbd8c032665b42db1
SummaryWe present aninteractiveDeep Learning-based software tool for Unsupervised Clustering of DNA Sequences (iDeLUCS), that detects genomic signatures and uses them to cluster DNA sequences, without the need for sequence alignment or taxonomic iden
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8086223f538d1b592d5c01f3399bf62d
https://doi.org/10.1101/2023.05.17.541163
https://doi.org/10.1101/2023.05.17.541163
Publikováno v:
PLoS ONE, Vol 17, Iss 1 (2022)
PLoS ONE
PLoS ONE, Vol 17, Iss 1, p e0261531 (2022)
PLoS ONE
PLoS ONE, Vol 17, Iss 1, p e0261531 (2022)
We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of prim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54cb0bb7339acfce18ab71a0cc18c9ee
https://doi.org/10.1371/journal.pone.0261531
https://doi.org/10.1371/journal.pone.0261531