Ontology type: schema:ScholarlyArticle
2019-12
AUTHORSMatthew Z. DeMaere, Aaron E. Darling
ABSTRACTMost microbes cannot be easily cultured, and metagenomics provides a means to study them. Current techniques aim to resolve individual genomes from metagenomes, so-called metagenome-assembled genomes (MAGs). Leading approaches depend upon time series or transect studies, the efficacy of which is a function of community complexity, target abundance, and sequencing depth. We describe an unsupervised method that exploits the hierarchical nature of Hi-C interaction rates to resolve MAGs using a single time point. We validate the method and directly compare against a recently announced proprietary service, ProxiMeta. bin3C is an open-source pipeline and makes use of the Infomap clustering algorithm ( https://github.com/cerebis/bin3C ). More... »
PAGES46
http://scigraph.springernature.com/pub.10.1186/s13059-019-1643-1
DOIhttp://dx.doi.org/10.1186/s13059-019-1643-1
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1112389646
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30808380
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Artificial Intelligence and Image Processing",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information and Computing Sciences",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Computer Simulation",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Feces",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Genome, Bacterial",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Metagenomics",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Microbiota",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Sequence Analysis, DNA",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Software",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of Technology Sydney",
"id": "https://www.grid.ac/institutes/grid.117476.2",
"name": [
"The ithree institute, University of Technology Sydney, 15 Broadway, 2007, Ultimo, NSW, Australia"
],
"type": "Organization"
},
"familyName": "DeMaere",
"givenName": "Matthew Z.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Technology Sydney",
"id": "https://www.grid.ac/institutes/grid.117476.2",
"name": [
"The ithree institute, University of Technology Sydney, 15 Broadway, 2007, Ultimo, NSW, Australia"
],
"type": "Organization"
},
"familyName": "Darling",
"givenName": "Aaron E.",
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.7717/peerj.2676",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000740872"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1128/aem.68.5.2391-2396.2002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001407349"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ncomms6695",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004047595",
"https://doi.org/10.1038/ncomms6695"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.2728",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006668184",
"https://doi.org/10.1038/nbt.2728"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13059-015-0834-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007001582",
"https://doi.org/10.1186/s13059-015-0834-7"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1126/science.1181369",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007401642"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1126/science.1181369",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007401642"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.tig.2015.10.003",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007648177"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btr708",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008059544"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1103/physrevx.5.011027",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009464573"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1103/physrevx.5.011027",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009464573"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.2727",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009746211",
"https://doi.org/10.1038/nbt.2727"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1146/annurev.mi.39.100185.001541",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009812939"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1146/annurev.micro.57.030502.090759",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013011587"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1574-6976.2011.00292.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013179409"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.7717/peerj.603",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014653830"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0159161",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014781725"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.186072.114",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015107573"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkv424",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019590763"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btv351",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021132933"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1128/aem.70.8.4748-4755.2004",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021705132"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btp352",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023014918"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.7717/peerj.415",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023546388"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.0605965104",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028061681"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.113985.110",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029998681"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.252529799",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030789781"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkw992",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032430080"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/2049-2618-2-26",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033360565",
"https://doi.org/10.1186/2049-2618-2-26"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1046/j.1462-2920.2002.00352.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035061557"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1088/1742-5468/2008/10/p10008",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037912856"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10791-008-9066-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1039636189",
"https://doi.org/10.1007/s10791-008-9066-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1140/epjst/e2010-01179-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041361554",
"https://doi.org/10.1140/epjst/e2010-01179-1"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/g3.114.011825",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042116097"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/g3.114.011825",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042116097"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3115/980451.980859",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042254245"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrmicro3378",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042860154",
"https://doi.org/10.1038/nrmicro3378"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1103/physreve.91.012809",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043403050"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1103/physreve.91.012809",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043403050"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3329",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044309870",
"https://doi.org/10.1038/nbt.3329"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1103/physreve.80.016118",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046173962"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1103/physreve.80.016118",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046173962"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.7717/peerj.1165",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048540869"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/1553374.1553511",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048906649"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btv638",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059414543"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btw290",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059414767"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/imanum/drs019",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059689753"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.213462.116",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1060407507"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1126/science.1134196",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1062454858"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.213959.116",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1084197429"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/034793",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085115205"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/034793",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085115205"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/034793",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085115205"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3893",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091105392",
"https://doi.org/10.1038/nbt.3893"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3893",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091105392",
"https://doi.org/10.1038/nbt.3893"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3893",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091105392",
"https://doi.org/10.1038/nbt.3893"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3893",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091105392",
"https://doi.org/10.1038/nbt.3893"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3893",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091105392",
"https://doi.org/10.1038/nbt.3893"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.4458",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092065319",
"https://doi.org/10.1038/nmeth.4458"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.4458",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092065319",
"https://doi.org/10.1038/nmeth.4458"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/198713",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092128731"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/198713",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092128731"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/198713",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092128731"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/gigascience/gix103",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092697679"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/225342",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093061348"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/225342",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093061348"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/225342",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093061348"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/sbrn.2012.25",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1095190732"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.7717/peerj.4320",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100665940"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/256800",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100712726"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/256800",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100712726"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/256800",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100712726"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/261149",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100923467"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/261149",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100923467"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/261149",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100923467"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-12",
"datePublishedReg": "2019-12-01",
"description": "Most microbes cannot be easily cultured, and metagenomics provides a means to study them. Current techniques aim to resolve individual genomes from metagenomes, so-called metagenome-assembled genomes (MAGs). Leading approaches depend upon time series or transect studies, the efficacy of which is a function of community complexity, target abundance, and sequencing depth. We describe an unsupervised method that exploits the hierarchical nature of Hi-C interaction rates to resolve MAGs using a single time point. We validate the method and directly compare against a recently announced proprietary service, ProxiMeta. bin3C is an open-source pipeline and makes use of the Infomap clustering algorithm ( https://github.com/cerebis/bin3C ).",
"genre": "research_article",
"id": "sg:pub.10.1186/s13059-019-1643-1",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isFundedItemOf": [
{
"id": "sg:grant.7074425",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.5127178",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1023439",
"issn": [
"1474-760X",
"1465-6906"
],
"name": "Genome Biology",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "20"
}
],
"name": "bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes",
"pagination": "46",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"2ee3da568dd1629db7f343a3bf84331deeb1711f8487c2324f6268f56a279805"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"30808380"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"100960660"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/s13059-019-1643-1"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1112389646"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s13059-019-1643-1",
"https://app.dimensions.ai/details/publication/pub.1112389646"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T12:55",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000364_0000000364/records_72869_00000001.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1186%2Fs13059-019-1643-1"
}
]Download the RDF metadata as:Â json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1643-1'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1643-1'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1643-1'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1643-1'
This table displays all metadata directly associated to this object as RDF triples.
283 TRIPLES
21 PREDICATES
91 URIs
29 LITERALS
17 BLANK NODES