Ontology type: schema:ScholarlyArticle Open Access: True
2018-05
AUTHORSJessica J. Y. Lee, Michael M. Gottlieb, Jake Lever, Steven J. M. Jones, Nenad Blau, Clara D. M. van Karnebeek, Wyeth W. Wasserman
ABSTRACTPhenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources. More... »
PAGES555-562
http://scigraph.springernature.com/pub.10.1007/s10545-017-0125-4
DOIhttp://dx.doi.org/10.1007/s10545-017-0125-4
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1100424605
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/29340838
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/2008/0604",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Genetics",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Biological Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of British Columbia",
"id": "https://www.grid.ac/institutes/grid.17091.3e",
"name": [
"Centre for Molecular Medicine and Therapeutics, BC Children\u2019s Hospital Research Institute, University of British Columbia, Room 3109, 950 West 28th Avenue, V5Z 4H4, Vancouver, BC, Canada"
],
"type": "Organization"
},
"familyName": "Lee",
"givenName": "Jessica J. Y.",
"id": "sg:person.011251512717.98",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011251512717.98"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of British Columbia",
"id": "https://www.grid.ac/institutes/grid.17091.3e",
"name": [
"Centre for Molecular Medicine and Therapeutics, BC Children\u2019s Hospital Research Institute, University of British Columbia, Room 3109, 950 West 28th Avenue, V5Z 4H4, Vancouver, BC, Canada"
],
"type": "Organization"
},
"familyName": "Gottlieb",
"givenName": "Michael M.",
"id": "sg:person.0764773472.70",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764773472.70"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "BC Cancer Agency",
"id": "https://www.grid.ac/institutes/grid.248762.d",
"name": [
"Canada\u2019s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC, Canada"
],
"type": "Organization"
},
"familyName": "Lever",
"givenName": "Jake",
"id": "sg:person.015322256334.16",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015322256334.16"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of British Columbia",
"id": "https://www.grid.ac/institutes/grid.17091.3e",
"name": [
"Canada\u2019s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC, Canada",
"Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada"
],
"type": "Organization"
},
"familyName": "Jones",
"givenName": "Steven J. M.",
"id": "sg:person.011076371162.80",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011076371162.80"
],
"type": "Person"
},
{
"affiliation": {
"name": [
"Dietmar-Hopp Metabolic Center, Department of General Pediatrics, University Hospital, Heidelberg, Germany"
],
"type": "Organization"
},
"familyName": "Blau",
"givenName": "Nenad",
"id": "sg:person.0625016530.03",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0625016530.03"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Academic Medical Center",
"id": "https://www.grid.ac/institutes/grid.5650.6",
"name": [
"Centre for Molecular Medicine and Therapeutics, BC Children\u2019s Hospital Research Institute, University of British Columbia, Room 3109, 950 West 28th Avenue, V5Z 4H4, Vancouver, BC, Canada",
"Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada",
"Departments of Pediatrics and Clinical Genetics, Emma Children\u2019s Hospital, Academic Medical Centre, Amsterdam, The Netherlands"
],
"type": "Organization"
},
"familyName": "van Karnebeek",
"givenName": "Clara D. M.",
"id": "sg:person.01037477313.40",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01037477313.40"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of British Columbia",
"id": "https://www.grid.ac/institutes/grid.17091.3e",
"name": [
"Centre for Molecular Medicine and Therapeutics, BC Children\u2019s Hospital Research Institute, University of British Columbia, Room 3109, 950 West 28th Avenue, V5Z 4H4, Vancouver, BC, Canada",
"Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada"
],
"type": "Organization"
},
"familyName": "Wasserman",
"givenName": "Wyeth W.",
"id": "sg:person.01164162122.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01164162122.26"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1093/nar/gku1205",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001175538"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/humu.21466",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002708729"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1542/peds.102.6.e69",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003261112"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ajhg.2009.09.003",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008228824"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrg2897",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008283990",
"https://doi.org/10.1038/nrg2897"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrg2897",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008283990",
"https://doi.org/10.1038/nrg2897"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ajhg.2015.06.009",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011302959"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13073-015-0199-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011378546",
"https://doi.org/10.1186/s13073-015-0199-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13073-015-0199-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011378546",
"https://doi.org/10.1186/s13073-015-0199-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkw1040",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013999124"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1056/nejmoa1515792",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020152170"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/humu.22858",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020622625"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btu393",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022334505"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkw1128",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027518192"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3390/ijms17091555",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028490605"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/humu.22048",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029961486"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1651-2227.2006.tb02172.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030455012"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1651-2227.2006.tb02172.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030455012"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/humu.22772",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032645935"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.2656",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034101760",
"https://doi.org/10.1038/nmeth.2656"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng0404-323",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037567670",
"https://doi.org/10.1038/ng0404-323"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng0404-323",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037567670",
"https://doi.org/10.1038/ng0404-323"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrg1383",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038372929",
"https://doi.org/10.1038/nrg1383"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrg1383",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038372929",
"https://doi.org/10.1038/nrg1383"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/gim.2015.137",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038384356",
"https://doi.org/10.1038/gim.2015.137"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkw1039",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038586231"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/humu.22080",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1039065531"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/humu.22347",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044142673"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pbio.1002033",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053684353"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1080/08035250500349413",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1058341423"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1080/08035250500349413",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1058341423"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btw763",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059415126"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1076626377",
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ajhg.2017.04.003",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085175044"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/gim.2017.108",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1090829209",
"https://doi.org/10.1038/gim.2017.108"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btx613",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091964335"
],
"type": "CreativeWork"
}
],
"datePublished": "2018-05",
"datePublishedReg": "2018-05-01",
"description": "Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources.",
"genre": "research_article",
"id": "sg:pub.10.1007/s10545-017-0125-4",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1090550",
"issn": [
"0141-8955",
"1573-2665"
],
"name": "Journal of Inherited Metabolic Disease",
"type": "Periodical"
},
{
"issueNumber": "3",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "41"
}
],
"name": "Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis",
"pagination": "555-562",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"62a3a19a0b2eff795343bc5452e9198e3f0676a3082f58b68bff559e12769776"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"29340838"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"7910918"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s10545-017-0125-4"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1100424605"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s10545-017-0125-4",
"https://app.dimensions.ai/details/publication/pub.1100424605"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-10T18:33",
"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/v90/0000000001_0000000264/records_8675_00000603.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs10545-017-0125-4"
}
]
Download the RDF metadata as: 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.10.1007/s10545-017-0125-4'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10545-017-0125-4'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10545-017-0125-4'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10545-017-0125-4'
This table displays all metadata directly associated to this object as RDF triples.
219 TRIPLES
21 PREDICATES
59 URIs
21 LITERALS
9 BLANK NODES