europepmc tutorial
for v0.1.4
Europe PMC covers life science literature and gives access to open access full texts. Europe PMC ingests all PubMed content and extends its index with other sources, including Agricola, a bibliographic database of citations to the agricultural literature, or Biological Patents.
For more background on Europe PMC, see:
Europe PMC: a full-text literature database for the life sciences and platform for innovation. (2014). Nucleic Acids Research, 43(D1), D1042–D1048. https://doi.org/10.1093/nar/gku1061
Installation
install.packages("europepmc")
Or development version from GitHub
install.packages("devtools")
devtools::install_github("ropensci/europepmc")
library("europepmc")
Implemented API methods
This client supports the following API methods:
| API-Method | Description | R functions |
|---|---|---|
| search | Search Europe PMC and get detailed metadata | epmc_search(), epmc_details() |
| profile | Obtain a summary of hit counts for several Europe PMC databases | epmc_profile() |
| citations | Load metadata representing citing articles for a given publication | epmc_citations() |
| references | Retrieve the reference section of a pubication | epmc_refs() |
| databaseLinks | Get links to biological databases such as UniProt or ENA | epmc_db(), epmc_db_count() |
| labslinks | Access links to Europe PMC provided by third parties | epmc_lablinks(), epmc_lablinks_count() |
| textMinedTerms | Retrieve text-mined terms | epmc_tm(), epmc_tm_count() |
| fullTextXML | Fetch full-texts deposited in PMC | epmc_ftxt() |
| bookXML | retrieve book XML formatted full text for the Open Access subset of the Europe PMC bookshelf | epmc_ftxt_book() |
Search Europe PMC
The search covers both metadata (e.g. abstracts or title) and full texts. To
build your query, please refer to the comprehensive guidance on how to search
Europe PMC: http://europepmc.org/help. Simply provide your query in the Europe
PMC search syntax to epmc_search().
By default, epmc_search returns 100 records. To adjust the limit, simply use
the limit parameter.
Examples
For instance, search for abstracts and full texts that mention
Gabi-Kat, a Flanking Sequence Tag
(FST)-based database for T-DNA insertion mutants:
epmc_search(query = 'Gabi-Kat')
#> # A tibble: 100 x 27
#> id source pmid pmcid doi
#> <chr> <chr> <chr> <chr> <chr>
#> 1 28013277 MED 28013277 PMC5444572 10.1093/pcp/pcw205
#> 2 22080561 MED 22080561 PMC3245140 10.1093/nar/gkr1047
#> 3 17062622 MED 17062622 PMC1781121 10.1093/nar/gkl753
#> 4 14756321 MED 14756321 <NA> 10.1023/b:plan.0000009297.37235.4a
#> 5 12874060 MED 12874060 <NA> 10.1093/bioinformatics/btg170
#> 6 25324895 MED 25324895 PMC4169229 10.1186/1746-4811-10-28
#> 7 26343971 MED 26343971 <NA> 10.1016/j.molp.2015.08.011
#> 8 27117628 MED 27117628 PMC4846993 10.1038/srep24971
#> 9 28636198 MED 28636198 PMC5519931 10.1111/nph.14655
#> 10 26493293 MED 26493293 PMC4737287 10.1111/tpj.13062
#> # ... with 90 more rows, and 22 more variables: title <chr>,
#> # authorString <chr>, journalTitle <chr>, issue <chr>,
#> # journalVolume <chr>, pubYear <chr>, journalIssn <chr>, pageInfo <chr>,
#> # pubType <chr>, isOpenAccess <chr>, inEPMC <chr>, inPMC <chr>,
#> # hasPDF <chr>, hasBook <chr>, hasSuppl <chr>, citedByCount <int>,
#> # hasReferences <chr>, hasTextMinedTerms <chr>,
#> # hasDbCrossReferences <chr>, hasLabsLinks <chr>,
#> # hasTMAccessionNumbers <chr>, firstPublicationDate <chr>
Get PLOS Genetics (ISSN:1553-7404) articles that cross-reference EMBL:
epmc_search(query = 'ISSN:1553-7404 HAS_EMBL:y')
#> # A tibble: 100 x 27
#> id source pmid pmcid doi
#> <chr> <chr> <chr> <chr> <chr>
#> 1 28628615 MED 28628615 PMC5495485 10.1371/journal.pgen.1006847
#> 2 28594826 MED 28594826 PMC5481146 10.1371/journal.pgen.1006838
#> 3 28222092 MED 28222092 PMC5340410 10.1371/journal.pgen.1006596
#> 4 27780204 MED 27780204 PMC5079590 10.1371/journal.pgen.1006397
#> 5 27541862 MED 27541862 PMC4991801 10.1371/journal.pgen.1006270
#> 6 27385107 MED 27385107 PMC4934787 10.1371/journal.pgen.1006155
#> 7 27149082 MED 27149082 PMC4858218 10.1371/journal.pgen.1006030
#> 8 27327578 MED 27327578 PMC4915694 10.1371/journal.pgen.1006110
#> 9 27203426 MED 27203426 PMC4874600 10.1371/journal.pgen.1006063
#> 10 27120580 MED 27120580 PMC4847869 10.1371/journal.pgen.1005987
#> # ... with 90 more rows, and 22 more variables: title <chr>,
#> # authorString <chr>, journalTitle <chr>, issue <chr>,
#> # journalVolume <chr>, pubYear <chr>, journalIssn <chr>, pageInfo <chr>,
#> # pubType <chr>, isOpenAccess <chr>, inEPMC <chr>, inPMC <chr>,
#> # hasPDF <chr>, hasBook <chr>, hasSuppl <chr>, citedByCount <int>,
#> # hasReferences <chr>, hasTextMinedTerms <chr>,
#> # hasDbCrossReferences <chr>, hasLabsLinks <chr>,
#> # hasTMAccessionNumbers <chr>, firstPublicationDate <chr>
Use ORCID to search for personal publications:
epmc_search(query = 'AUTHORID:"0000-0002-7635-3473"', limit = 1000)
#> # A tibble: 134 x 27
#> id source pmid pmcid doi
#> <chr> <chr> <chr> <chr> <chr>
#> 1 28585529 MED 28585529 PMC5467160 10.1038/ncomms15708
#> 2 28284041 MED 28284041 <NA> 10.1515/znc-2016-0221
#> 3 28013277 MED 28013277 PMC5444572 10.1093/pcp/pcw205
#> 4 27230558 MED 27230558 PMC4881148 10.1186/s12870-016-0805-5
#> 5 26980001 MED 26980001 PMC4791833 10.1186/s12864-016-2566-9
#> 6 26676716 MED 26676716 <NA> 10.1111/tpj.13103
#> 7 27557761 MED 27557761 <NA> 10.1007/978-1-4939-6396-6_5
#> 8 26343971 MED 26343971 <NA> 10.1016/j.molp.2015.08.011
#> 9 26328666 MED 26328666 PMC4556409 10.1186/s13059-015-0729-7
#> 10 25891958 MED 25891958 <NA> 10.1111/tpj.12854
#> # ... with 124 more rows, and 22 more variables: title <chr>,
#> # authorString <chr>, journalTitle <chr>, journalVolume <chr>,
#> # pubYear <chr>, journalIssn <chr>, pageInfo <chr>, pubType <chr>,
#> # isOpenAccess <chr>, inEPMC <chr>, inPMC <chr>, hasPDF <chr>,
#> # hasBook <chr>, hasSuppl <chr>, citedByCount <int>,
#> # hasReferences <chr>, hasTextMinedTerms <chr>,
#> # hasDbCrossReferences <chr>, hasLabsLinks <chr>,
#> # hasTMAccessionNumbers <chr>, firstPublicationDate <chr>, issue <chr>
Include MeSH and UniProt synonyms
You may also want to include synonyms when searching Europe PMC. If
synonym = TRUE MeSH and UniProt synonyms are searched as well.
# with snyonyms
epmc_search('aspirin', synonym = TRUE)
#> # A tibble: 100 x 27
#> id source pmid doi
#> <chr> <chr> <chr> <chr>
#> 1 28942878 MED 28942878 10.1016/j.ijcard.2017.06.052
#> 2 28942879 MED 28942879 10.1016/j.ijcard.2017.08.013
#> 3 28990263 MED 28990263 10.1111/ctr.13133
#> 4 28937039 MED 28937039 10.4103/0366-6999.215330
#> 5 29024912 MED 29024912 10.1016/j.ejogrb.2017.10.004
#> 6 29026148 MED 29026148 10.1038/s41598-017-13430-z
#> 7 28993349 MED 28993349 10.1136/bcr-2017-220483
#> 8 28969559 MED 28969559 10.2174/1871527316666171002115633
#> 9 28965180 MED 28965180 10.1007/s10565-017-9412-y
#> 10 28974502 MED 28974502 10.1161/jaha.117.006328
#> # ... with 90 more rows, and 23 more variables: title <chr>,
#> # authorString <chr>, journalTitle <chr>, journalVolume <chr>,
#> # pubYear <chr>, journalIssn <chr>, pageInfo <chr>, pubType <chr>,
#> # isOpenAccess <chr>, inEPMC <chr>, inPMC <chr>, hasPDF <chr>,
#> # hasBook <chr>, citedByCount <int>, hasReferences <chr>,
#> # hasTextMinedTerms <chr>, hasDbCrossReferences <chr>,
#> # hasLabsLinks <chr>, hasTMAccessionNumbers <chr>,
#> # firstPublicationDate <chr>, pmcid <chr>, issue <chr>, hasSuppl <chr>
# without synonyms
epmc_search('aspirin', synonym = FALSE)
#> # A tibble: 100 x 27
#> id source pmid doi
#> <chr> <chr> <chr> <chr>
#> 1 28942878 MED 28942878 10.1016/j.ijcard.2017.06.052
#> 2 28937039 MED 28937039 10.4103/0366-6999.215330
#> 3 28969559 MED 28969559 10.2174/1871527316666171002115633
#> 4 28910305 MED 28910305 10.1371/journal.pone.0184027
#> 5 28965180 MED 28965180 10.1007/s10565-017-9412-y
#> 6 29024912 MED 29024912 10.1016/j.ejogrb.2017.10.004
#> 7 28993349 MED 28993349 10.1136/bcr-2017-220483
#> 8 28974502 MED 28974502 10.1161/jaha.117.006328
#> 9 28968454 MED 28968454 10.1371/journal.pone.0185847
#> 10 28900541 MED 28900541 10.1038/cddiscovery.2017.58
#> # ... with 90 more rows, and 23 more variables: title <chr>,
#> # authorString <chr>, journalTitle <chr>, journalVolume <chr>,
#> # pubYear <chr>, journalIssn <chr>, pageInfo <chr>, pubType <chr>,
#> # isOpenAccess <chr>, inEPMC <chr>, inPMC <chr>, hasPDF <chr>,
#> # hasBook <chr>, citedByCount <int>, hasReferences <chr>,
#> # hasTextMinedTerms <chr>, hasDbCrossReferences <chr>,
#> # hasLabsLinks <chr>, hasTMAccessionNumbers <chr>,
#> # firstPublicationDate <chr>, pmcid <chr>, issue <chr>, hasSuppl <chr>
Output types
epmc_search() supports the following output types :
Parsed key metadata (default)
Key metadata parsed as non-nested tibble:
epmc_search('Gabi-Kat', output = 'parsed')
#> # A tibble: 100 x 27
#> id source pmid pmcid doi
#> <chr> <chr> <chr> <chr> <chr>
#> 1 28013277 MED 28013277 PMC5444572 10.1093/pcp/pcw205
#> 2 22080561 MED 22080561 PMC3245140 10.1093/nar/gkr1047
#> 3 17062622 MED 17062622 PMC1781121 10.1093/nar/gkl753
#> 4 14756321 MED 14756321 <NA> 10.1023/b:plan.0000009297.37235.4a
#> 5 12874060 MED 12874060 <NA> 10.1093/bioinformatics/btg170
#> 6 25324895 MED 25324895 PMC4169229 10.1186/1746-4811-10-28
#> 7 26343971 MED 26343971 <NA> 10.1016/j.molp.2015.08.011
#> 8 27117628 MED 27117628 PMC4846993 10.1038/srep24971
#> 9 28636198 MED 28636198 PMC5519931 10.1111/nph.14655
#> 10 26493293 MED 26493293 PMC4737287 10.1111/tpj.13062
#> # ... with 90 more rows, and 22 more variables: title <chr>,
#> # authorString <chr>, journalTitle <chr>, issue <chr>,
#> # journalVolume <chr>, pubYear <chr>, journalIssn <chr>, pageInfo <chr>,
#> # pubType <chr>, isOpenAccess <chr>, inEPMC <chr>, inPMC <chr>,
#> # hasPDF <chr>, hasBook <chr>, hasSuppl <chr>, citedByCount <int>,
#> # hasReferences <chr>, hasTextMinedTerms <chr>,
#> # hasDbCrossReferences <chr>, hasLabsLinks <chr>,
#> # hasTMAccessionNumbers <chr>, firstPublicationDate <chr>
In addition to fetch bibliographic metadata, the parsed output also helps you
to get a general overview about additional information types that are offered by
Europe PMC and which can be retrieved through other europepmc-functions.
Columns inform whether open access full texts (isOpenAccess), cross-links to
other EBI databases (hasDbCrossReferences), text-mined terms (hasTextMinedTerms)
or references (hasReferences) are available.
IDs
List of literature database identifier including PMID:
epmc_search('Gabi-Kat', output = 'id_list')
#> # A tibble: 100 x 4
#> id source pmid pmcid
#> <chr> <chr> <chr> <chr>
#> 1 28013277 MED 28013277 PMC5444572
#> 2 22080561 MED 22080561 PMC3245140
#> 3 17062622 MED 17062622 PMC1781121
#> 4 14756321 MED 14756321 <NA>
#> 5 12874060 MED 12874060 <NA>
#> 6 25324895 MED 25324895 PMC4169229
#> 7 26343971 MED 26343971 <NA>
#> 8 27117628 MED 27117628 PMC4846993
#> 9 28636198 MED 28636198 PMC5519931
#> 10 26493293 MED 26493293 PMC4737287
#> # ... with 90 more rows
Record details
Full metadata as list. Please be aware that these lists can become very large, and fetching these data from Europe PMC therefore takes some time.
my_list <- epmc_search('Gabi-Kat', output = 'raw', limit = 10)
# display the structure for one list element
str(my_list[[10]])
#> List of 43
#> $ id : chr "26493293"
#> $ source : chr "MED"
#> $ pmid : chr "26493293"
#> $ pmcid : chr "PMC4737287"
#> $ doi : chr "10.1111/tpj.13062"
#> $ title : chr "The RNA helicase, eIF4A-1, is required for ovule development and cell size homeostasis in Arabidopsis."
#> $ authorString : chr "Bush MS, Crowe N, Zheng T, Doonan JH."
#> $ authorList :List of 1
#> ..$ author:List of 4
#> .. ..$ :List of 5
#> .. .. ..$ fullName : chr "Bush MS"
#> .. .. ..$ firstName : chr "Maxwell S"
#> .. .. ..$ lastName : chr "Bush"
#> .. .. ..$ initials : chr "MS"
#> .. .. ..$ affiliation: chr "Department of Cell and Developmental Biology, John Innes Centre, Colney Lane, Norwich, NR4 7UH, UK."
#> .. ..$ :List of 5
#> .. .. ..$ fullName : chr "Crowe N"
#> .. .. ..$ firstName : chr "Natalie"
#> .. .. ..$ lastName : chr "Crowe"
#> .. .. ..$ initials : chr "N"
#> .. .. ..$ affiliation: chr "Department of Cell and Developmental Biology, John Innes Centre, Colney Lane, Norwich, NR4 7UH, UK."
#> .. ..$ :List of 5
#> .. .. ..$ fullName : chr "Zheng T"
#> .. .. ..$ firstName : chr "Tao"
#> .. .. ..$ lastName : chr "Zheng"
#> .. .. ..$ initials : chr "T"
#> .. .. ..$ affiliation: chr "Department of Cell and Developmental Biology, John Innes Centre, Colney Lane, Norwich, NR4 7UH, UK."
#> .. ..$ :List of 6
#> .. .. ..$ fullName : chr "Doonan JH"
#> .. .. ..$ firstName : chr "John H"
#> .. .. ..$ lastName : chr "Doonan"
#> .. .. ..$ initials : chr "JH"
#> .. .. ..$ authorId :List of 2
#> .. .. .. ..$ type : chr "ORCID"
#> .. .. .. ..$ value: chr "0000-0001-6027-1919"
#> .. .. ..$ affiliation: chr "Institute of Biological, Environmental & Rural Sciences, Aberystwyth University, Gogerddan Campus, Aberystwyth, SY23 3EE, UK."
#> $ authorIdList :List of 1
#> ..$ authorId:List of 1
#> .. ..$ :List of 2
#> .. .. ..$ type : chr "ORCID"
#> .. .. ..$ value: chr "0000-0001-6027-1919"
#> $ journalInfo :List of 8
#> ..$ issue : chr "5"
#> ..$ volume : chr "84"
#> ..$ journalIssueId : int 2363412
#> ..$ dateOfPublication : chr "2015 Dec"
#> ..$ monthOfPublication : int 12
#> ..$ yearOfPublication : int 2015
#> ..$ printPublicationDate: chr "2015-12-01"
#> ..$ journal :List of 6
#> .. ..$ title : chr "The Plant journal : for cell and molecular biology"
#> .. ..$ medlineAbbreviation: chr "Plant J"
#> .. ..$ essn : chr "1365-313X"
#> .. ..$ issn : chr "0960-7412"
#> .. ..$ isoabbreviation : chr "Plant J."
#> .. ..$ nlmid : chr "9207397"
#> $ pubYear : chr "2015"
#> $ pageInfo : chr "989-1004"
#> $ abstractText : chr "eIF4A is a highly conserved RNA-stimulated ATPase and helicase involved in the initiation of mRNA translation. "| __truncated__
#> $ affiliation : chr "Department of Cell and Developmental Biology, John Innes Centre, Colney Lane, Norwich, NR4 7UH, UK."
#> $ language : chr "eng"
#> $ pubModel : chr "Print"
#> $ pubTypeList :List of 1
#> ..$ pubType: chr [1:3] "Research Support, Non-U.S. Gov't" "research-article" "Journal Article"
#> $ grantsList :List of 1
#> ..$ grant:List of 1
#> .. ..$ :List of 3
#> .. .. ..$ grantId: chr "BB/C507988/1"
#> .. .. ..$ agency : chr "Biotechnology and Biological Sciences Research Council"
#> .. .. ..$ orderIn: int 0
#> $ meshHeadingList :List of 1
#> ..$ meshHeading:List of 14
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Arabidopsis"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 3
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "CY"
#> .. .. .. .. .. ..$ qualifierName: chr "cytology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "PH"
#> .. .. .. .. .. ..$ qualifierName: chr "physiology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "Y"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Flowers"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 3
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "CY"
#> .. .. .. .. .. ..$ qualifierName: chr "cytology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "PH"
#> .. .. .. .. .. ..$ qualifierName: chr "physiology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Meristem"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 3
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "CY"
#> .. .. .. .. .. ..$ qualifierName: chr "cytology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "PH"
#> .. .. .. .. .. ..$ qualifierName: chr "physiology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Plant Roots"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 3
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "CY"
#> .. .. .. .. .. ..$ qualifierName: chr "cytology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "ME"
#> .. .. .. .. .. ..$ qualifierName: chr "metabolism"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "PH"
#> .. .. .. .. .. ..$ qualifierName: chr "physiology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Eukaryotic Initiation Factor-4A"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 3
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "ME"
#> .. .. .. .. .. ..$ qualifierName: chr "metabolism"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "PH"
#> .. .. .. .. .. ..$ qualifierName: chr "physiology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "Y"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Arabidopsis Proteins"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 2
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "PH"
#> .. .. .. .. .. ..$ qualifierName: chr "physiology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "Y"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Protein Isoforms"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 3
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "ME"
#> .. .. .. .. .. ..$ qualifierName: chr "metabolism"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "PH"
#> .. .. .. .. .. ..$ qualifierName: chr "physiology"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Cell Cycle"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 1
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Mitosis"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 1
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GE"
#> .. .. .. .. .. ..$ qualifierName: chr "genetics"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> .. ..$ :List of 2
#> .. .. ..$ majorTopic_YN : chr "Y"
#> .. .. ..$ descriptorName: chr "Cell Size"
#> .. ..$ :List of 2
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName: chr "Homeostasis"
#> .. ..$ :List of 2
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName: chr "Mutation"
#> .. ..$ :List of 2
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName: chr "Genome, Plant"
#> .. ..$ :List of 3
#> .. .. ..$ majorTopic_YN : chr "N"
#> .. .. ..$ descriptorName : chr "Ovule"
#> .. .. ..$ meshQualifierList:List of 1
#> .. .. .. ..$ meshQualifier:List of 2
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "GD"
#> .. .. .. .. .. ..$ qualifierName: chr "growth & development"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "Y"
#> .. .. .. .. ..$ :List of 3
#> .. .. .. .. .. ..$ abbreviation : chr "ME"
#> .. .. .. .. .. ..$ qualifierName: chr "metabolism"
#> .. .. .. .. .. ..$ majorTopic_YN: chr "N"
#> $ keywordList :List of 1
#> ..$ keyword: chr [1:7] "Arabidopsis thaliana" "Cell cycle" "Plant growth" "RNA helicase" ...
#> $ chemicalList :List of 1
#> ..$ chemical:List of 3
#> .. ..$ :List of 2
#> .. .. ..$ name : chr "Protein Isoforms"
#> .. .. ..$ registryNumber: chr "0"
#> .. ..$ :List of 2
#> .. .. ..$ name : chr "Eukaryotic Initiation Factor-4A"
#> .. .. ..$ registryNumber: chr "EC 2.7.7.-"
#> .. ..$ :List of 2
#> .. .. ..$ name : chr "Arabidopsis Proteins"
#> .. .. ..$ registryNumber: chr "0"
#> $ subsetList :List of 1
#> ..$ subset:List of 1
#> .. ..$ :List of 2
#> .. .. ..$ code: chr "IM"
#> .. .. ..$ name: chr "Index Medicus"
#> $ fullTextUrlList :List of 1
#> ..$ fullTextUrl:List of 3
#> .. ..$ :List of 5
#> .. .. ..$ availability : chr "Open access"
#> .. .. ..$ availabilityCode: chr "OA"
#> .. .. ..$ documentStyle : chr "pdf"
#> .. .. ..$ site : chr "Europe_PMC"
#> .. .. ..$ url : chr "http://europepmc.org/articles/PMC4737287?pdf=render"
#> .. ..$ :List of 5
#> .. .. ..$ availability : chr "Open access"
#> .. .. ..$ availabilityCode: chr "OA"
#> .. .. ..$ documentStyle : chr "html"
#> .. .. ..$ site : chr "Europe_PMC"
#> .. .. ..$ url : chr "http://europepmc.org/articles/PMC4737287"
#> .. ..$ :List of 5
#> .. .. ..$ availability : chr "Subscription required"
#> .. .. ..$ availabilityCode: chr "S"
#> .. .. ..$ documentStyle : chr "doi"
#> .. .. ..$ site : chr "DOI"
#> .. .. ..$ url : chr "https://doi.org/10.1111/tpj.13062"
#> $ isOpenAccess : chr "Y"
#> $ inEPMC : chr "Y"
#> $ inPMC : chr "N"
#> $ hasPDF : chr "Y"
#> $ hasBook : chr "N"
#> $ hasSuppl : chr "Y"
#> $ citedByCount : int 0
#> $ hasReferences : chr "Y"
#> $ hasTextMinedTerms : chr "Y"
#> $ hasDbCrossReferences : chr "N"
#> $ hasLabsLinks : chr "Y"
#> $ license : chr "cc by"
#> $ authMan : chr "N"
#> $ epmcAuthMan : chr "N"
#> $ nihAuthMan : chr "N"
#> $ hasTMAccessionNumbers: chr "N"
#> $ dateOfCompletion : chr "2016-12-13"
#> $ dateOfCreation : chr "2016-01-16"
#> $ dateOfRevision : chr "2016-12-30"
#> $ firstPublicationDate : chr "2015-10-23"
Get results number
Count hits before with epmc_hits to define limit. For example, get list of ids
that represent articles referencing DataCite DOIs:
query <- "ACCESSION_TYPE:doi"
epmc_hits(query)
#> [1] 9054
# set limit to 10 records
my_data <- epmc_search(query = query, limit = 10)
head(my_data)
#> # A tibble: 6 x 27
#> id source pmid pmcid doi
#> <chr> <chr> <chr> <chr> <chr>
#> 1 28994823 MED 28994823 PMC5634324 10.1038/sdata.2017.144
#> 2 28993608 MED 28993608 PMC5634421 10.1038/s41467-017-00565-w
#> 3 28972575 MED 28972575 PMC5625552 10.1038/sdata.2017.141
#> 4 28972570 MED 28972570 PMC5625556 10.1038/sdata.2017.139
#> 5 28970545 MED 28970545 PMC5624899 10.1038/s41598-017-12757-x
#> 6 28983202 MED 28983202 PMC5624428 10.5195/jmla.2017.176
#> # ... with 22 more variables: title <chr>, authorString <chr>,
#> # journalTitle <chr>, journalVolume <chr>, pubYear <chr>,
#> # journalIssn <chr>, pageInfo <chr>, pubType <chr>, isOpenAccess <chr>,
#> # inEPMC <chr>, inPMC <chr>, hasPDF <chr>, hasBook <chr>,
#> # hasSuppl <chr>, citedByCount <int>, hasReferences <chr>,
#> # hasTextMinedTerms <chr>, hasDbCrossReferences <chr>,
#> # hasLabsLinks <chr>, hasTMAccessionNumbers <chr>,
#> # firstPublicationDate <chr>, issue <chr>
attr(my_data, "hit_count")
#> [1] 9054
You may also use epmc_profile to retrieve a summary of hit counts.
epmc_profile(query = 'malaria')
#> $source
#> # A tibble: 10 x 2
#> name count
#> * <chr> <int>
#> 1 AGR 121
#> 2 CBA 113
#> 3 CTX 7
#> 4 ETH 179
#> 5 HIR 4
#> 6 MED 122218
#> 7 PAT 2252
#> 8 CIT 0
#> 9 PMC 13740
#> 10 PPR 3
#>
#> $pubType
#> # A tibble: 5 x 2
#> name count
#> * <chr> <int>
#> 1 ALL 138637
#> 2 FULL TEXT 88064
#> 3 OPEN ACCESS 42550
#> 4 REVIEW 16950
#> 5 BOOKS AND DOCUMENTS 117
#>
#> $subset
#> # A tibble: 1 x 2
#> name count
#> * <chr> <int>
#> 1 BL 3
Get article details
In addition to key metadata, epmc_details also returns full metadata
providing more comprehensive information on the article-level. By default,
PubMed / Medline index is searched.
epmc_details(ext_id = '24270414')
#> $basic
#> # A tibble: 1 x 32
#> id source pmid pmcid doi
#> * <chr> <chr> <chr> <chr> <chr>
#> 1 24270414 MED 24270414 PMC3859427 10.1172/jci73168
#> # ... with 27 more variables: title <chr>, authorString <chr>,
#> # pubYear <chr>, pageInfo <chr>, abstractText <chr>, language <chr>,
#> # pubModel <chr>, isOpenAccess <chr>, inEPMC <chr>, inPMC <chr>,
#> # hasPDF <chr>, hasBook <chr>, hasSuppl <chr>, citedByCount <int>,
#> # hasReferences <chr>, hasTextMinedTerms <chr>,
#> # hasDbCrossReferences <chr>, hasLabsLinks <chr>, authMan <chr>,
#> # epmcAuthMan <chr>, nihAuthMan <chr>, hasTMAccessionNumbers <chr>,
#> # dateOfCompletion <chr>, dateOfCreation <chr>, dateOfRevision <chr>,
#> # electronicPublicationDate <chr>, firstPublicationDate <chr>
#>
#> $author_details
#> # A tibble: 2 x 6
#> fullName firstName lastName initials authorId.type
#> * <chr> <chr> <chr> <chr> <chr>
#> 1 Malaga-Dieguez L Laura Malaga-Dieguez L ORCID
#> 2 Susztak K Katalin Susztak K <NA>
#> # ... with 1 more variables: authorId.value <chr>
#>
#> $journal_info
#> # A tibble: 1 x 13
#> issue volume journalIssueId dateOfPublication monthOfPublication
#> * <chr> <chr> <int> <chr> <int>
#> 1 12 123 2099360 2013 Dec 12
#> # ... with 8 more variables: yearOfPublication <int>,
#> # printPublicationDate <chr>, journal.title <chr>,
#> # journal.medlineAbbreviation <chr>, journal.essn <chr>,
#> # journal.issn <chr>, journal.isoabbreviation <chr>, journal.nlmid <chr>
#>
#> $ftx
#> # A tibble: 5 x 5
#> availability availabilityCode documentStyle site
#> * <chr> <chr> <chr> <chr>
#> 1 Free F pdf Europe_PMC
#> 2 Free F html Europe_PMC
#> 3 Free F pdf PubMedCentral
#> 4 Free F html PubMedCentral
#> 5 Subscription required S doi DOI
#> # ... with 1 more variables: url <chr>
#>
#> $chemical
#> # A tibble: 4 x 2
#> name registryNumber
#> * <chr> <chr>
#> 1 Ubiquinone 1339-63-5
#> 2 Protein Kinases EC 2.7.-
#> 3 aarF domain containing kinase 4, human EC 2.7.-
#> 4 coenzyme Q10 EJ27X76M46
#>
#> $mesh_topic
#> # A tibble: 5 x 2
#> majorTopic_YN descriptorName
#> * <chr> <chr>
#> 1 N Animals
#> 2 N Humans
#> 3 N Nephrotic Syndrome
#> 4 N Ubiquinone
#> 5 N Protein Kinases
#>
#> $mesh_qualifiers
#> # A tibble: 4 x 4
#> descriptorName abbreviation qualifierName majorTopic_YN
#> <chr> <chr> <chr> <chr>
#> 1 Nephrotic Syndrome GE genetics Y
#> 2 Ubiquinone AA analogs & derivatives Y
#> 3 Ubiquinone BI biosynthesis N
#> 4 Protein Kinases PH physiology Y
#>
#> $comments
#> # A tibble: 1 x 5
#> id source reference type
#> * <chr> <chr> <chr> <chr>
#> 1 24270420 MED J Clin Invest. 2013 Dec;123(12):5179-89 Comment on
#> # ... with 1 more variables: orderIn <int>
#>
#> $grants
#> # A tibble: 3 x 4
#> grantId agency acronym orderIn
#> * <chr> <chr> <chr> <int>
#> 1 R01 DK076077 NIDDK NIH HHS DK 0
#> 2 R01DK076077 NIDDK NIH HHS DK 0
#> 3 R01 DK087635 NIDDK NIH HHS DK 0
Show author details including ORCID:
epmc_details(ext_id = '14756321')$author_details
#> # A tibble: 6 x 6
#> fullName firstName lastName initials authorId.type
#> * <chr> <chr> <chr> <chr> <chr>
#> 1 Rosso MG Mario G Rosso MG <NA>
#> 2 Li Y Yong Li Y <NA>
#> 3 Strizhov N Nicolai Strizhov N <NA>
#> 4 Reiss B Bernd Reiss B ORCID
#> 5 Dekker K Koen Dekker K <NA>
#> 6 Weisshaar B Bernd Weisshaar B ORCID
#> # ... with 1 more variables: authorId.value <chr>
Get citation counts and citing publications
Citing publications from the Europe PMC index can be retrieved like this:
my_cites <- epmc_citations('9338777')
my_cites
#> # A tibble: 100 x 12
#> id source
#> <chr> <chr>
#> 1 10221475 MED
#> 2 10342317 MED
#> 3 10440384 MED
#> 4 9696842 MED
#> 5 9703304 MED
#> 6 9728974 MED
#> 7 9728985 MED
#> 8 9728986 MED
#> 9 9728987 MED
#> 10 11134319 MED
#> # ... with 90 more rows, and 10 more variables: citationType <chr>,
#> # title <chr>, authorString <chr>, journalAbbreviation <chr>,
#> # pubYear <int>, volume <chr>, issue <chr>, pageInfo <chr>,
#> # citedByCount <int>, text <chr>
# hits:
attr(my_cites, 'hit_count')
#> [1] 208
Please note, that citation counts are often smaller than those held by toll- access services such as Web of Science or Scopus because the number of reference sections indexed for Europe PMC considerably differs due to the lack of full text accessibility.
Get reference section
Europe PMC indexes more than 5 million reference sections.
epmc_refs('PMC3166943', data_src = 'pmc')
#> # A tibble: 18 x 16
#> id source citationType
#> <chr> <chr> <chr>
#> 1 10802651 MED JOURNAL ARTICLE
#> 2 <NA> <NA> <NA>
#> 3 18077472 MED JOURNAL ARTICLE
#> 4 15642104 MED JOURNAL ARTICLE
#> 5 18460184 MED JOURNAL ARTICLE
#> 6 17989687 MED JOURNAL ARTICLE
#> 7 20848809 MED JOURNAL ARTICLE
#> 8 20139945 MED JOURNAL ARTICLE
#> 9 <NA> <NA> <NA>
#> 10 17267433 MED JOURNAL ARTICLE
#> 11 15199967 MED JOURNAL ARTICLE
#> 12 14681407 MED JOURNAL ARTICLE
#> 13 16756499 MED JOURNAL ARTICLE
#> 14 16959967 MED JOURNAL ARTICLE
#> 15 16518471 MED JOURNAL ARTICLE
#> 16 11901169 MED JOURNAL ARTICLE
#> 17 15892874 MED JOURNAL ARTICLE
#> 18 <NA> <NA> <NA>
#> # ... with 13 more variables: title <chr>, authorString <chr>,
#> # journalAbbreviation <chr>, issue <chr>, pubYear <int>, volume <chr>,
#> # pageInfo <chr>, citedOrder <int>, match <chr>, essn <chr>, issn <chr>,
#> # publicationTitle <chr>, externalLink <chr>
Tip: add has_reflist:y to your search string in epmc_search to make sure
you only get publications whose reference sections are accessible through
Europe PMC.
Retrieve links to other EBI databases
Cross-links to EBI databases are either manually curated (ENA, InterPro, PDB, IntAct, ChEMBL, ChEBI and ArrayExpress) or automatically gathered through text-mining (European Nucleotide Archive, UniProt, PDB, OMIM, RefSNP, RefSeq, Pfam, InterPro, Ensembl, ArrayExpress and data DOIs).
Before retrieving the links, please check availability and sources first:
epmc_db_count('12368864')
#> # A tibble: 3 x 2
#> dbName count
#> * <chr> <int>
#> 1 EMBL 10
#> 2 INTERPRO 1
#> 3 UNIPROT 5588
Add has_xrefs:y or to your search string in epmc_search to make sure
you only get publications with cross-references to EBI databases.
Select database and get links:
epmc_db('12368864', db = 'embl')
#> # A tibble: 10 x 4
#> info1 info2
#> <chr> <chr>
#> 1 AE014187 Plasmodium falciparum 3D7 chromosome 14, complete sequence.
#> 2 AE014186 Plasmodium falciparum 3D7 chromosome 11, complete sequence.
#> 3 LN999943 Plasmodium falciparum 3D7 chromosome 2, complete sequence.
#> 4 AE001362 Plasmodium falciparum 3D7 chromosome 2, complete sequence.
#> 5 LN999947 Plasmodium falciparum 3D7 chromosome 12, complete sequence.
#> 6 AE014185 Plasmodium falciparum 3D7 chromosome 10, complete sequence.
#> 7 LN999944 Plasmodium falciparum 3D7 chromosome 10, complete sequence.
#> 8 LN999945 Plasmodium falciparum 3D7 chromosome 11, complete sequence.
#> 9 LN999946 Plasmodium falciparum 3D7 chromosome 14, complete sequence.
#> 10 AE014188 Plasmodium falciparum 3D7 chromosome 12, complete sequence.
#> # ... with 2 more variables: info3 <chr>, info4 <chr>
Get text-mined terms
Text-mined terms that can be accessed via Europe PMC are mapped against controlled vocabularies like Gene Ontology.
Before retrieving these terms, please check availability and vocabularies first:
epmc_tm_count('25249410')
#> # A tibble: 7 x 2
#> name count
#> * <chr> <int>
#> 1 accession 1
#> 2 chemical 25
#> 3 disease 1
#> 4 efo 28
#> 5 gene_protein 51
#> 6 go_term 17
#> 7 organism 27
Select vocabulary to retrieve the terms:
epmc_tm('25249410', semantic_type = 'GO_TERM')
#> term count altName dbName dbId
#> 1 chromosome 25 chromosomes GO 0005694
#> 2 biosynthesis 16 formation, synthesis GO 0009058
#> 3 binding 9 GO 0005488
#> 4 cells 5 cell GO 0005623
#> 5 growth 4 Growth GO 0040007
#> 6 flavonoid biosynthesis 3 GO 0009813
#> 7 gene expression 2 GO 0010467
#> 8 secondary metabolism 2 GO 0019748
#> 9 metabolism 2 GO 0008152
#> 10 defense responses 1 GO 0006952
#> 11 cell cycle control 1 GO 1901987
#> 12 regulation of gene expression 1 GO 0010468
#> 13 glucosinolate biosynthesis 1 GO 0019761
#> 14 cell development 1 GO 0048468
#> 15 root hairs 1 GO 0035618
#> 16 anthocyanin biosynthesis 1 GO 0009718
#> 17 enzyme activities 1 GO 0003824
Links to external sources
With the External Link services, Europe PMC allows third parties to publish links from Europe PMC to other webpages. Current External Link providers, whose id can be found through Europe PMC’s Advanced Search interface, include Wikipedia, Dryad Digital Repository or the institutional repo of Bielefeld University. For more information, see http://europepmc.org/labslink.
Check availability and number of links:
epmc_lablinks_count('PMC3986813', data_src = 'pmc')
#> # A tibble: 5 x 2
#> providerName linksCount
#> * <chr> <int>
#> 1 EBI Train Online 1
#> 2 Wikipedia 1
#> 3 BioStudies 1
#> 4 Publons 1
#> 5 Altmetric 1
Get links from Wikipedia (lab_id = '1507')
epmc_lablinks('20301687', lab_id = '1507')
#> # A tibble: 2 x 6
#> title
#> <chr>
#> 1 Werner_syndrome
#> 2 Werner_syndrome_ATP-dependent_helicase
#> # ... with 5 more variables: url <chr>, imgUrl <lgl>, lab_id <int>,
#> # lab_name <fctr>, lab_description <fctr>
Full text access
Full texts are in XML format and are only provided for the Open Access subset of Europe PMC. They can be retrieved by the PMCID.
epmc_ftxt('PMC3257301')
#> {xml_document}
#> <article article-type="research-article" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML">
#> [1] <front>\n <journal-meta>\n <journal-id journal-id-type="nlm-ta"> ...
#> [2] <body>\n <sec id="s1">\n <title>Introduction</title>\n <p>Atm ...
#> [3] <back>\n <ack>\n <p>We would like to thank Dr. C. Gourlay and Dr ...
Books, fetched through the PMID or the ‘NBK’ book number, can also be loaded
as XML into R for further text-mining activities using epmc_ftxt_book().
Please check full-text availability before calling this method either with epmc_search() or epmc_details().
Citing
To cite europepmc in publications use:
Najko Jahn (2017). europepmc: R Interface to the Europe PubMed Central RESTful Web Service. R package version 0.1.4. https://cran.rstudio.com/package=europepmc
License and bugs
- License: MIT
- Report bugs at our Github repo for europepmc
