Build a Biomedical Knowledge Graph from Literature

Created by

Ryan Clinton

Actor

Europe PMC — Biomedical Knowledge Graph & Literature Mining

Turn a biomedical topic into a co-occurrence knowledge graph: genes, diseases, chemicals and datasets as nodes and edges, with Neo4j and Gephi CSV.

Try for free

Europe PMC — Biomedical Knowledge Graph & Literature Miningryanclinton/europe-pmc-search

Status

Access

Paper Title

Year

+6 fields

Input

Search Query(required):CRISPR gene editing

Entity co-occurrence network:true

Output fields

Status

Access

Paper Title

Year

Citations

Accessions

Entities

Journal

DOI

Europe PMC Link

How it works

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The Europe PMC — Biomedical Knowledge Graph & Literature Mining Actor is ready to run with the inputs already set for "Build a Biomedical Knowledge Graph from Literature". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Build a Biomedical Knowledge Graph from Literature" task

The Europe PMC — Biomedical Knowledge Graph & Literature Mining Actor will start running based on the input automatically. You can also change all the input fields, like search query and entity co-occurrence network, to match your specific use case.

Receive the "Build a Biomedical Knowledge Graph from Literature" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as status, access, paper title, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Build a Biomedical Knowledge Graph from Literature" task via API.