HERMES: a molecular-formula-oriented method to target the metabolome View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-11-01

AUTHORS

Roger Giné, Jordi Capellades, Josep M. Badia, Dennis Vughs, Michaela Schwaiger-Haber, Theodore Alexandrov, Maria Vinaixa, Andrea M. Brunner, Gary J. Patti, Oscar Yanes

ABSTRACT

Comprehensive metabolome analyses are essential for biomedical, environmental, and biotechnological research. However, current MS1- and MS2-based acquisition and data analysis strategies in untargeted metabolomics result in low identification rates of metabolites. Here we present HERMES, a molecular-formula-oriented and peak-detection-free method that uses raw LC/MS1 information to optimize MS2 acquisition. Investigating environmental water, Escherichia coli, and human plasma extracts with HERMES, we achieved an increased biological specificity of MS2 scans, leading to improved mass spectral similarity scoring and identification rates when compared with a state-of-the-art data-dependent acquisition (DDA) approach. Thus, HERMES improves sensitivity, selectivity, and annotation of metabolites. HERMES is available as an R package with a user-friendly graphical interface for data analysis and visualization. More... »

PAGES

1370-1376

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41592-021-01307-z

DOI

http://dx.doi.org/10.1038/s41592-021-01307-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1142293185

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/34725482


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/10", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Technology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Algorithms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Chromatography, Liquid", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Escherichia coli", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Metabolome", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Metabolomics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Plasma", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tandem Mass Spectrometry", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Water Pollutants, Chemical", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain", 
          "id": "http://www.grid.ac/institutes/grid.410367.7", 
          "name": [
            "Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gin\u00e9", 
        "givenName": "Roger", 
        "id": "sg:person.010422546153.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010422546153.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain", 
          "id": "http://www.grid.ac/institutes/grid.413448.e", 
          "name": [
            "Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain", 
            "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Capellades", 
        "givenName": "Jordi", 
        "id": "sg:person.01247304215.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01247304215.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain", 
          "id": "http://www.grid.ac/institutes/grid.413448.e", 
          "name": [
            "Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain", 
            "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Badia", 
        "givenName": "Josep M.", 
        "id": "sg:person.016376352153.21", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016376352153.21"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "KWR Water Research Institute, Nieuwegein, the Netherlands", 
          "id": "http://www.grid.ac/institutes/grid.419022.c", 
          "name": [
            "KWR Water Research Institute, Nieuwegein, the Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vughs", 
        "givenName": "Dennis", 
        "id": "sg:person.01131644636.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01131644636.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medicine, Washington University, St. Louis, MO, USA", 
          "id": "http://www.grid.ac/institutes/grid.4367.6", 
          "name": [
            "Department of Chemistry, Washington University, St. Louis, MO, USA", 
            "Department of Medicine, Washington University, St. Louis, MO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Schwaiger-Haber", 
        "givenName": "Michaela", 
        "id": "sg:person.010274155775.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010274155775.20"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.266100.3", 
          "name": [
            "Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany", 
            "Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, Heidelberg, Germany", 
            "Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alexandrov", 
        "givenName": "Theodore", 
        "id": "sg:person.01204640152.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01204640152.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain", 
          "id": "http://www.grid.ac/institutes/grid.413448.e", 
          "name": [
            "Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain", 
            "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vinaixa", 
        "givenName": "Maria", 
        "id": "sg:person.01155212160.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01155212160.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "KWR Water Research Institute, Nieuwegein, the Netherlands", 
          "id": "http://www.grid.ac/institutes/grid.419022.c", 
          "name": [
            "KWR Water Research Institute, Nieuwegein, the Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Brunner", 
        "givenName": "Andrea M.", 
        "id": "sg:person.01204132211.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01204132211.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medicine, Washington University, St. Louis, MO, USA", 
          "id": "http://www.grid.ac/institutes/grid.4367.6", 
          "name": [
            "Department of Chemistry, Washington University, St. Louis, MO, USA", 
            "Department of Medicine, Washington University, St. Louis, MO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Patti", 
        "givenName": "Gary J.", 
        "id": "sg:person.01277526735.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277526735.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain", 
          "id": "http://www.grid.ac/institutes/grid.413448.e", 
          "name": [
            "Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain", 
            "CIBER de Diabetes y Enfermedades Metab\u00f3licas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yanes", 
        "givenName": "Oscar", 
        "id": "sg:person.01112740060.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01112740060.70"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/nbt.2377", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041207870", 
          "https://doi.org/10.1038/nbt.2377"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.4260", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085072336", 
          "https://doi.org/10.1038/nmeth.4260"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.3959", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017141397", 
          "https://doi.org/10.1038/nmeth.3959"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41592-019-0344-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1112858205", 
          "https://doi.org/10.1038/s41592-019-0344-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s13321-018-0324-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111159678", 
          "https://doi.org/10.1186/s13321-018-0324-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41596-020-0317-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1127540344", 
          "https://doi.org/10.1038/s41596-020-0317-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41587-020-0740-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1132841620", 
          "https://doi.org/10.1038/s41587-020-0740-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s42256-020-00234-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1131638979", 
          "https://doi.org/10.1038/s42256-020-00234-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.2551", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051249218", 
          "https://doi.org/10.1038/nmeth.2551"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13361-017-1608-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084036995", 
          "https://doi.org/10.1007/s13361-017-1608-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.3393", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011230739", 
          "https://doi.org/10.1038/nmeth.3393"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.4072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023732847", 
          "https://doi.org/10.1038/nmeth.4072"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2021-11-01", 
    "datePublishedReg": "2021-11-01", 
    "description": "Comprehensive metabolome analyses are essential for biomedical, environmental, and biotechnological research. However, current MS1- and MS2-based acquisition and data analysis strategies in untargeted metabolomics result in low identification rates of metabolites. Here we present HERMES, a molecular-formula-oriented and peak-detection-free method that uses raw LC/MS1 information to optimize MS2 acquisition. Investigating environmental water, Escherichia coli, and human plasma extracts with HERMES, we achieved an increased biological specificity of MS2 scans, leading to improved mass spectral similarity scoring and identification rates when compared with a state-of-the-art data-dependent acquisition (DDA) approach. Thus, HERMES improves sensitivity, selectivity, and annotation of metabolites. HERMES is available as an R package with a user-friendly graphical interface for data analysis and visualization.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/s41592-021-01307-z", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.5495629", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.7027052", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1033763", 
        "issn": [
          "1548-7091", 
          "1548-7105"
        ], 
        "name": "Nature Methods", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "11", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "18"
      }
    ], 
    "keywords": [
      "biotechnological research", 
      "comprehensive metabolome analysis", 
      "metabolome analysis", 
      "Escherichia coli", 
      "biological specificity", 
      "data-dependent acquisition approach", 
      "MS2 acquisition", 
      "annotation of metabolites", 
      "R package", 
      "untargeted metabolomics", 
      "metabolites", 
      "MS2 scans", 
      "data analysis strategies", 
      "coli", 
      "low identification rate", 
      "metabolome", 
      "annotation", 
      "user-friendly graphical interface", 
      "MS1", 
      "metabolomics", 
      "analysis strategy", 
      "environmental water", 
      "specificity", 
      "extract", 
      "analysis", 
      "acquisition", 
      "identification rate", 
      "water", 
      "rate", 
      "strategies", 
      "graphical interface", 
      "sensitivity", 
      "selectivity", 
      "information", 
      "data analysis", 
      "similarity scoring", 
      "visualization", 
      "acquisition approach", 
      "approach", 
      "state", 
      "research", 
      "method", 
      "free method", 
      "human plasma extracts", 
      "interface", 
      "package", 
      "plasma extracts", 
      "scoring", 
      "scans", 
      "HERMES"
    ], 
    "name": "HERMES: a molecular-formula-oriented method to target the metabolome", 
    "pagination": "1370-1376", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1142293185"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41592-021-01307-z"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "34725482"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41592-021-01307-z", 
      "https://app.dimensions.ai/details/publication/pub.1142293185"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-10-01T06:48", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/article/article_888.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/s41592-021-01307-z"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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.10.1038/s41592-021-01307-z'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41592-021-01307-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41592-021-01307-z'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41592-021-01307-z'


 

This table displays all metadata directly associated to this object as RDF triples.

282 TRIPLES      21 PREDICATES      97 URIs      76 LITERALS      16 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41592-021-01307-z schema:about N1506c65b56b04ef4992ee825c0d393da
2 N2f6104e4ab48473086c04d3a2062d1e9
3 N34caf7edfb194d828123ec1c454cc80b
4 N391dd9dcacc84fc8bdc6a51391bfd8e5
5 N62314a9b31464b2b9a2ac7a58fd04bf8
6 N8788be4e31774563a7205eefd9b9fee2
7 N8d499f1204e6490481d01480748fa497
8 Nc9f7c71416ca45cfbcbb179e46b13998
9 Ndde0f212e0e3476889c2a0ef3dd48264
10 anzsrc-for:06
11 anzsrc-for:10
12 anzsrc-for:11
13 schema:author N8cc9ad688ee14947a2ab9bec0ee21802
14 schema:citation sg:pub.10.1007/s13361-017-1608-0
15 sg:pub.10.1038/nbt.2377
16 sg:pub.10.1038/nmeth.2551
17 sg:pub.10.1038/nmeth.3393
18 sg:pub.10.1038/nmeth.3959
19 sg:pub.10.1038/nmeth.4072
20 sg:pub.10.1038/nmeth.4260
21 sg:pub.10.1038/s41587-020-0740-8
22 sg:pub.10.1038/s41592-019-0344-8
23 sg:pub.10.1038/s41596-020-0317-5
24 sg:pub.10.1038/s42256-020-00234-6
25 sg:pub.10.1186/s13321-018-0324-5
26 schema:datePublished 2021-11-01
27 schema:datePublishedReg 2021-11-01
28 schema:description Comprehensive metabolome analyses are essential for biomedical, environmental, and biotechnological research. However, current MS1- and MS2-based acquisition and data analysis strategies in untargeted metabolomics result in low identification rates of metabolites. Here we present HERMES, a molecular-formula-oriented and peak-detection-free method that uses raw LC/MS1 information to optimize MS2 acquisition. Investigating environmental water, Escherichia coli, and human plasma extracts with HERMES, we achieved an increased biological specificity of MS2 scans, leading to improved mass spectral similarity scoring and identification rates when compared with a state-of-the-art data-dependent acquisition (DDA) approach. Thus, HERMES improves sensitivity, selectivity, and annotation of metabolites. HERMES is available as an R package with a user-friendly graphical interface for data analysis and visualization.
29 schema:genre article
30 schema:isAccessibleForFree true
31 schema:isPartOf N06cf38423ef5448ebe321709dcd794d8
32 N4b9849b9e6cb4afcac1eff6dcaec964a
33 sg:journal.1033763
34 schema:keywords Escherichia coli
35 HERMES
36 MS1
37 MS2 acquisition
38 MS2 scans
39 R package
40 acquisition
41 acquisition approach
42 analysis
43 analysis strategy
44 annotation
45 annotation of metabolites
46 approach
47 biological specificity
48 biotechnological research
49 coli
50 comprehensive metabolome analysis
51 data analysis
52 data analysis strategies
53 data-dependent acquisition approach
54 environmental water
55 extract
56 free method
57 graphical interface
58 human plasma extracts
59 identification rate
60 information
61 interface
62 low identification rate
63 metabolites
64 metabolome
65 metabolome analysis
66 metabolomics
67 method
68 package
69 plasma extracts
70 rate
71 research
72 scans
73 scoring
74 selectivity
75 sensitivity
76 similarity scoring
77 specificity
78 state
79 strategies
80 untargeted metabolomics
81 user-friendly graphical interface
82 visualization
83 water
84 schema:name HERMES: a molecular-formula-oriented method to target the metabolome
85 schema:pagination 1370-1376
86 schema:productId Na1c2f726bb03422f8352bb614cb3575e
87 Nbfa5b9869b4d4d5aa1519f53342641f5
88 Nf2945f13c6db4390aa8c40a95d594cd9
89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1142293185
90 https://doi.org/10.1038/s41592-021-01307-z
91 schema:sdDatePublished 2022-10-01T06:48
92 schema:sdLicense https://scigraph.springernature.com/explorer/license/
93 schema:sdPublisher N86641fbde52c48bf942e5f7ffa1b3602
94 schema:url https://doi.org/10.1038/s41592-021-01307-z
95 sgo:license sg:explorer/license/
96 sgo:sdDataset articles
97 rdf:type schema:ScholarlyArticle
98 N06cf38423ef5448ebe321709dcd794d8 schema:volumeNumber 18
99 rdf:type schema:PublicationVolume
100 N1506c65b56b04ef4992ee825c0d393da schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
101 schema:name Tandem Mass Spectrometry
102 rdf:type schema:DefinedTerm
103 N2f6104e4ab48473086c04d3a2062d1e9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Plasma
105 rdf:type schema:DefinedTerm
106 N34caf7edfb194d828123ec1c454cc80b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Algorithms
108 rdf:type schema:DefinedTerm
109 N386719e7489949c9908403b2feccdb96 rdf:first sg:person.01247304215.35
110 rdf:rest N3e7e50ca1135405b8c44e7002bc852a4
111 N38f6089b0ce54166a1ad36ea11fa56ed rdf:first sg:person.01112740060.70
112 rdf:rest rdf:nil
113 N391dd9dcacc84fc8bdc6a51391bfd8e5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Humans
115 rdf:type schema:DefinedTerm
116 N3e7e50ca1135405b8c44e7002bc852a4 rdf:first sg:person.016376352153.21
117 rdf:rest Nf98ab6de7a704070af2befe242dfbbc6
118 N4b9849b9e6cb4afcac1eff6dcaec964a schema:issueNumber 11
119 rdf:type schema:PublicationIssue
120 N62314a9b31464b2b9a2ac7a58fd04bf8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Metabolome
122 rdf:type schema:DefinedTerm
123 N79d5b4cd9db1476aab0af69be8296d6e rdf:first sg:person.01204132211.07
124 rdf:rest Nbb9e478cd7614ca39632a34aabddf1e8
125 N86641fbde52c48bf942e5f7ffa1b3602 schema:name Springer Nature - SN SciGraph project
126 rdf:type schema:Organization
127 N8788be4e31774563a7205eefd9b9fee2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Chromatography, Liquid
129 rdf:type schema:DefinedTerm
130 N89e1615312774c2ca80e7dff5713a1e4 rdf:first sg:person.01155212160.29
131 rdf:rest N79d5b4cd9db1476aab0af69be8296d6e
132 N8cc9ad688ee14947a2ab9bec0ee21802 rdf:first sg:person.010422546153.61
133 rdf:rest N386719e7489949c9908403b2feccdb96
134 N8d499f1204e6490481d01480748fa497 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name Escherichia coli
136 rdf:type schema:DefinedTerm
137 Na1c2f726bb03422f8352bb614cb3575e schema:name doi
138 schema:value 10.1038/s41592-021-01307-z
139 rdf:type schema:PropertyValue
140 Na7b0b33bda1a4b61a8bf0f8e4f373999 rdf:first sg:person.01204640152.10
141 rdf:rest N89e1615312774c2ca80e7dff5713a1e4
142 Nbb9e478cd7614ca39632a34aabddf1e8 rdf:first sg:person.01277526735.83
143 rdf:rest N38f6089b0ce54166a1ad36ea11fa56ed
144 Nbedd30d134124c17bfaab2a3d5f3c10f rdf:first sg:person.010274155775.20
145 rdf:rest Na7b0b33bda1a4b61a8bf0f8e4f373999
146 Nbfa5b9869b4d4d5aa1519f53342641f5 schema:name pubmed_id
147 schema:value 34725482
148 rdf:type schema:PropertyValue
149 Nc9f7c71416ca45cfbcbb179e46b13998 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
150 schema:name Water Pollutants, Chemical
151 rdf:type schema:DefinedTerm
152 Ndde0f212e0e3476889c2a0ef3dd48264 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
153 schema:name Metabolomics
154 rdf:type schema:DefinedTerm
155 Nf2945f13c6db4390aa8c40a95d594cd9 schema:name dimensions_id
156 schema:value pub.1142293185
157 rdf:type schema:PropertyValue
158 Nf98ab6de7a704070af2befe242dfbbc6 rdf:first sg:person.01131644636.53
159 rdf:rest Nbedd30d134124c17bfaab2a3d5f3c10f
160 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
161 schema:name Biological Sciences
162 rdf:type schema:DefinedTerm
163 anzsrc-for:10 schema:inDefinedTermSet anzsrc-for:
164 schema:name Technology
165 rdf:type schema:DefinedTerm
166 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
167 schema:name Medical and Health Sciences
168 rdf:type schema:DefinedTerm
169 sg:grant.5495629 http://pending.schema.org/fundedItem sg:pub.10.1038/s41592-021-01307-z
170 rdf:type schema:MonetaryGrant
171 sg:grant.7027052 http://pending.schema.org/fundedItem sg:pub.10.1038/s41592-021-01307-z
172 rdf:type schema:MonetaryGrant
173 sg:journal.1033763 schema:issn 1548-7091
174 1548-7105
175 schema:name Nature Methods
176 schema:publisher Springer Nature
177 rdf:type schema:Periodical
178 sg:person.010274155775.20 schema:affiliation grid-institutes:grid.4367.6
179 schema:familyName Schwaiger-Haber
180 schema:givenName Michaela
181 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010274155775.20
182 rdf:type schema:Person
183 sg:person.010422546153.61 schema:affiliation grid-institutes:grid.410367.7
184 schema:familyName Giné
185 schema:givenName Roger
186 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010422546153.61
187 rdf:type schema:Person
188 sg:person.01112740060.70 schema:affiliation grid-institutes:grid.413448.e
189 schema:familyName Yanes
190 schema:givenName Oscar
191 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01112740060.70
192 rdf:type schema:Person
193 sg:person.01131644636.53 schema:affiliation grid-institutes:grid.419022.c
194 schema:familyName Vughs
195 schema:givenName Dennis
196 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01131644636.53
197 rdf:type schema:Person
198 sg:person.01155212160.29 schema:affiliation grid-institutes:grid.413448.e
199 schema:familyName Vinaixa
200 schema:givenName Maria
201 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01155212160.29
202 rdf:type schema:Person
203 sg:person.01204132211.07 schema:affiliation grid-institutes:grid.419022.c
204 schema:familyName Brunner
205 schema:givenName Andrea M.
206 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01204132211.07
207 rdf:type schema:Person
208 sg:person.01204640152.10 schema:affiliation grid-institutes:grid.266100.3
209 schema:familyName Alexandrov
210 schema:givenName Theodore
211 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01204640152.10
212 rdf:type schema:Person
213 sg:person.01247304215.35 schema:affiliation grid-institutes:grid.413448.e
214 schema:familyName Capellades
215 schema:givenName Jordi
216 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01247304215.35
217 rdf:type schema:Person
218 sg:person.01277526735.83 schema:affiliation grid-institutes:grid.4367.6
219 schema:familyName Patti
220 schema:givenName Gary J.
221 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277526735.83
222 rdf:type schema:Person
223 sg:person.016376352153.21 schema:affiliation grid-institutes:grid.413448.e
224 schema:familyName Badia
225 schema:givenName Josep M.
226 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016376352153.21
227 rdf:type schema:Person
228 sg:pub.10.1007/s13361-017-1608-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084036995
229 https://doi.org/10.1007/s13361-017-1608-0
230 rdf:type schema:CreativeWork
231 sg:pub.10.1038/nbt.2377 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041207870
232 https://doi.org/10.1038/nbt.2377
233 rdf:type schema:CreativeWork
234 sg:pub.10.1038/nmeth.2551 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051249218
235 https://doi.org/10.1038/nmeth.2551
236 rdf:type schema:CreativeWork
237 sg:pub.10.1038/nmeth.3393 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011230739
238 https://doi.org/10.1038/nmeth.3393
239 rdf:type schema:CreativeWork
240 sg:pub.10.1038/nmeth.3959 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017141397
241 https://doi.org/10.1038/nmeth.3959
242 rdf:type schema:CreativeWork
243 sg:pub.10.1038/nmeth.4072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023732847
244 https://doi.org/10.1038/nmeth.4072
245 rdf:type schema:CreativeWork
246 sg:pub.10.1038/nmeth.4260 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085072336
247 https://doi.org/10.1038/nmeth.4260
248 rdf:type schema:CreativeWork
249 sg:pub.10.1038/s41587-020-0740-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1132841620
250 https://doi.org/10.1038/s41587-020-0740-8
251 rdf:type schema:CreativeWork
252 sg:pub.10.1038/s41592-019-0344-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112858205
253 https://doi.org/10.1038/s41592-019-0344-8
254 rdf:type schema:CreativeWork
255 sg:pub.10.1038/s41596-020-0317-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1127540344
256 https://doi.org/10.1038/s41596-020-0317-5
257 rdf:type schema:CreativeWork
258 sg:pub.10.1038/s42256-020-00234-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1131638979
259 https://doi.org/10.1038/s42256-020-00234-6
260 rdf:type schema:CreativeWork
261 sg:pub.10.1186/s13321-018-0324-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111159678
262 https://doi.org/10.1186/s13321-018-0324-5
263 rdf:type schema:CreativeWork
264 grid-institutes:grid.266100.3 schema:alternateName Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
265 schema:name Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, Heidelberg, Germany
266 Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
267 Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
268 rdf:type schema:Organization
269 grid-institutes:grid.410367.7 schema:alternateName Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain
270 schema:name Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain
271 rdf:type schema:Organization
272 grid-institutes:grid.413448.e schema:alternateName CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
273 schema:name CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
274 Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain
275 rdf:type schema:Organization
276 grid-institutes:grid.419022.c schema:alternateName KWR Water Research Institute, Nieuwegein, the Netherlands
277 schema:name KWR Water Research Institute, Nieuwegein, the Netherlands
278 rdf:type schema:Organization
279 grid-institutes:grid.4367.6 schema:alternateName Department of Medicine, Washington University, St. Louis, MO, USA
280 schema:name Department of Chemistry, Washington University, St. Louis, MO, USA
281 Department of Medicine, Washington University, St. Louis, MO, USA
282 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...