Given a uniprot ID, I am trying to automatically extract related pubmed IDs (PMIDs) from pubmed. I can map the UniProt ID to something NCBI can understand. For instance, UniProt ID O14733 can be mapped to GI:6831583 and then you can launch a search from http://www.ncbi.nlm.nih.gov/protein/O14733 to see the associated pubmed articles with the URL http://www.ncbi.nlm.nih.gov/pubmed?linkname=protein_pubmed_weighted&from_uid=6831583.
I have never used ncbi's e-utils, so it may be a very simple modification to be able to fetch these articles automatically, but I can't figure it out. My best guess was http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&LinkName=protein_pubmed_weighted&from_uid=6831583, but this returns nothing.
Basically, given an ID such as 683583, I want to return a list of PMIDs. I would rather do this in python if possible. Any suggestions?
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shelly.deforte
Thanks, that's what I needed!
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shelly.deforte
For completeness, here's what I worked out with David W's help. The construction of the URL is such:
This is how I was able to retrieve the records in Biopython:
protein_ID = "215274019"
handle = Entrez.elink(db="pubmed", dbfrom="protein", id=protein_id, linkname="protein_pubmed_weighted")
record = Entrez.read(handle)
for PMID in record[0]['LinkSetDb'][0]['Link']:
print PMID['Id']
Hey, I am trying to do the same thing basically. I have a q. D o you know the differences between the different linknames, i.e., protein_pubmed_weighted, protein_pubmed, and protein_pubmed_refseq?
Best,
Nils
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nils.rudqvist •
Depending on the scope of your project, you might want to directly download NCBI's look-up table between EntrezIDs and PubmedIDs and integrate this table into your workflow.
ftp://ftp.ncbi.nlm.nih.gov/gene/DATA/gene2pubmed.gz
I like this table because it enables easy (and computationally fast) filtering; e.g.: exclude papers, which cover 100s -1000s of different genes (and usually thus do not reveal gene-specific biology). e.g.: find genes, which are only mentioned together with your genes of interest
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asking.for.help •
This looks like a great resource, though I don't think I can easily map my UniProt IDs to genes, and I think it might change the coverage of the papers if I did. Still, I'm definitely going to bookmark this folder, thanks!
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