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Turbocharge a PubMed literature search using citation data from the NIH

Project description

PubMed ID (PMID) Cite

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pmidcite summary

Turbocharge a PubMed literature search in biomedicine, biochemistry, chemistry, behavioral science, and other life sciences by linking citation data from the National Institutes of Health (NIH) with PubMed IDs (PMIDs) using the command line rather than clicking and clicking and clicking on Google Scholar "Cited by N" links.

This open-source project is part of a peer-reviewed commentary that was invited by the editors of Research Synthesis Methods. Please Cite if you use pmidcite in your research or literature search.

Contact: dvklopfenstein@protonmail.com

Table of Contents

1) Download citation counts and data for a research paper

$ icite -H 26032263

  • This paper (PMID 26032263) has 25 citations, 10 references, and 4 authors.
  • This paper is performing well (74th percentile in column %) compared to its peers.

Starting usage

NIH percentile

This paper is performing well (74th percentile) compared to its peers (column %).

The NIH percentile grouping (column G) helps to highlight the better performing papers in groups 2, 3, and 4 by sorting the citing papers by group first, then publication year.

The sort places the lower performing papers in groups 0 or 1 at the back.

New papers appear at the beginning of a sorted list, no matter how many citations they have to better facilitate researchers in finding the latest discoveries.

The grouping of papers by NIH percentile grouping is a novel feature created by dvklopfenstein for this project.

2) Forward citation search

pmidcite summary

Also known as following a paper's Cited by links or Forward snowballing

icite -H; icite 26032263 --load_citations | sort -k6 -r
or
icite -H; icite 26032263 -c | sort -k6 -r

3) Backward citation search

Also known as following links to a paper's references or Backward snowballing

pmidcite summary

$ icite -H; icite 26032263 --load_references | sort -k6 -r
or
$ icite -H; icite 26032263 -r | sort -k6 -r

4) Summarize a group of citations

  • 4a) Examine a paper with PMID 30022098. Print the column headers(-H):
    icite -H 30022098
  • 4b) Download the details about each paper(-c) that cites 30022098 into a file(-o goatools_cites.txt):
    icite 30022098 -c -o goatools_cites.txt
  • 4c) Summarize the overall performace of the 300+ citing papers contained in goatools_cites.txt
    summarize_papers goatools_cites.txt -p TOP CIT CLI

4a) Examine a paper with PMID 30022098. Print the column headers(-H):

$ icite -H 30022098
COL 2        3  4       5 6 7        8  9  10 au[11](authors)
TYP PMID     RP HAMCc   % G YEAR   cit cli ref au[00](authors) title
TOP 30022098 R. .A..c 100 4 2018   318  1  23 au[14](D V Klopfenstein) GOATOOLS: A Python library for Gene Ontology analyses.

Paper with PMID 30022098 is cited by 318(cit) other research papers and 1(cli) clinical study. It has 23 references(ref).

4b) Download the details about each paper(-c) that cites 30022098 into a file(-o goatools_cites.txt):

$ icite 30022098 -c -o goatools_cites.txt

The requested paper (PMID=30022098) is described in one one line in goatools_cites.txt:

$ grep TOP goatools_cites.txt
TOP 30022098 R. .A..c 100 4 2018   318  1  23 au[14](D V Klopfenstein) GOATOOLS: A Python library for Gene Ontology analyses.

The paper (PMID=30022098) is cited by 381(CIT) research papers plus 1(CLI) clinical study:

$ grep CIT goatools_cites.txt | wc -l
318

$ grep CLI goatools_cites.txt | wc -l
1

4c) Summarize all the papers in goatools_cites.txt

NEW FUNCTIONALITY; INPUT REQUESTED: What would you like to see? Open an issue to comment.

$ summarize_papers goatools_cites.txt -p TOP CIT CLI
i=033.4% 4=003.4% 3=020.9% 2=021.9% 1=015.9% 0=004.4%   4 years:2018-2022   320 papers goatools_cites.txt
  • Output is on one line so many files containing sets of PMIDs may be compared. TBD: Add multiline verbose option.
  • The groups are from newest(i) to top-performing(4), great(3), very good(2), and overlooked(1 and 0)
  • The percentages of papers in goatools_citations.txt in each group follow the group name

5) Download citations for all papers returned from a PubMed search

  1. Do a search in PubMed
  2. Save all results into a file containing all PMIDs found by the search
  3. Download the list of PMIDs
  4. Run icite to analyze all the PMIDs

1. Do a search in PubMed

pmidcite summary

2. Save all results into a list of PMIDs

pmidcite summary

3. Download the list of PMIDs

pmidcite summary

4. Run icite to analyze all the PMIDs

$ icite -i pmid-HIVANDDNAm-set.txt -o pmid-HIVANDDNAm-icite.txt
$ grep TOP pmid-HIVANDDNAm-icite.txt | sort -k6

Command Line Interface (CLI)

A Command-Line Interface (CLI) can be preferable to a Graphical User Interface (GUI) because:

  • processing can be automated from a script
  • time-consuming mouse clicking is reduced
  • more data can be seen at once on a text screen than in a browser, giving the researcher a better overall impression of the full set of information [1]

Researchers who use Linux or Mac already work from the command line. Researchers who use Windows can get that Linux-like command line feeling while still running native Windows programs by downloading Cygwin from https://www.cygwin.com/ [1].

PubMed vs Google Scholar

Google Scholar vs PubMed

In 2013, Boeker et al. [6] recommended that a scientific search interface contain five integrated search criteria. PubMed implements all five, while Google did not in 2013 or today.

Google's highly popular implementation of the forward citation search through their ubiquitous "Cited by N" links is a "Better" experience than the PubMed's "forward citation search" implementation.

But if your research is in the health sciences and you are amenable to working from the command line, you can use PubMed in your browser plus citation data downloaded from the NIH using the command-line using pmidcite. The NIH's citation data includes a paper's ranking among its co-citation network.

What is in PubMed? Take a quick tour

PubMed Contents

PubMed is a search interface and toolset used to access over 30.5 million article records from databases such as:

  • MEDLINE: a highly selective database started in the 1960s
  • PubMed Central (PMC): an open-access database for full-text papers that are free of cost
  • Additional content such as books and articles published before the 1960s

Installation

To install from PyPI
$ pip3 install pmidcite

To install locally

$ git clone https://github.com/dvklopfenstein/pmidcite.git
$ cd ./pmidcite
$ pip3 install .

Setup

Save your literature search in a GitHub repo.

1. Add a pmidcite init file

Add a .pmidciterc init file to a non-git managed directory, such as home (~)

$ icite --generate-rcfile | tee ~/.pmidciterc
[pmidcite]
email = myname@email.edu
# To download PubMed search results, get an NCBI API key here:
# https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities
apikey = MY_LONG_HEX_NCBI_API_KEY
tool = my_scripts
$ export PMIDCITECONF=~/.pmidciterc

Do not version manage the .pmidciterc using a tool such as GitHub because it contains your personal email and your private NCBI API key.

2. NCBI E-Utils API key

To download PubMed abstracts and PubMed search results using NCBI's E-Utils, get an NCBI API key using these instructions:
https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities

Set the apikey value in the config file: ~/.pmidciterc

Contributing

See the contributing guide for detailed instructions on how to get started contributing to the pmidcite project.

Contact

email: dvklopfenstein@protonmail.com
https://orcid.org/0000-0003-0161-7603

How to Cite

If you use pmidcite in your research or literature search, please cite paper 1 (pmidcite) and paper 3 (NIH citation data).

Please also consider reading and citing Gusenbauer's response (paper 2) about improving search for all during the information avalanche of these times:

  1. The pmidcite paper:
    Commentary to Gusenbauer and Haddaway 2020: Evaluating Retrieval Qualities of PubMed and Google Scholar
    Klopfenstein DV and Dampier W
    2020 | Research Synthesis Methods | PMID: 33031632 | DOI: 10.1002/jrsm.1456 | pdf

  2. Gusenbauer's response to the pmidcite paper:
    What every Researcher should know about Searching – Clarified Concepts, Search Advice, and an Agenda to improve Finding in Academia
    Gusenbauer M and Haddaway N
    2020 | Research Synthesis Methods | PMID: 33031639 | DOI: 10.1002/jrsm.1457 | pdf

  3. The NIH citation data used by pmidcite -- Scientific Influence, Translation, and Citation counts:
    The NIH Open Citation Collection: A public access, broad coverage resource
    Hutchins BI ... Santangelo GM
    2019 | PLoS Biology | PMID: 31600197 | DOI: 10.1371/journal.pbio.3000385

References

Please consider reading and citing the paper [4] which inspired the creation of pmidcite [1] and the authors' response to our paper [2]:

  1. Which Academic Search Systems are Suitable for Systematic Reviews or Meta-Analyses? Evaluating Retrieval Qualities of Google Scholar, PubMed and 26 other Resources
    Gusenbauer M and Haddaway N
    2019 | Research Synthesis Methods | PMID: 31614060 | DOI: 10.1002/jrsm.1378

Mentioned in this README are also these outstanding contributions:

  1. Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level
    Hutchins BI, Xin Yuan, Anderson JM, and Santangelo, George M.
    2016 | PLoS Biology | PMID: 27599104 | DOI: 10.1371/journal.pbio.1002541

  2. Google Scholar as replacement for systematic literature searches: good relative recall and precision are not enough
    Boeker M et al.
    2013 | BMC Medical Research Methodology | PMID: 24160679 | DOI: 10.1186/1471-2288-13-131

  3. Best Match: New relevance search for PubMed
    Fiorini N ... Lu Zhiyong
    2018 | PLoS Biology | PMID: 30153250 | DOI: 10.1371/journal.pbio.2005343

PDFs

Contact

dvklopfenstein@protonmail.com
https://orcid.org/0000-0003-0161-7603

Copyright (C) 2019-present pmidcite, DV Klopfenstein, PhD. All rights reserved.

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