Bioc pmc api
Access PMC Open Access articles in BioC format for text miningFrom its SKILL.md
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BioC API for PMC Open Access
Overview
The BioC API provides full-text articles from PubMed Central (PMC) in the BioC format — a simplified XML/JSON structure designed specifically for biomedical text mining. Unlike the standard PMC OAI service (which returns JATS XML), BioC pre-segments text into passages with offset annotations, making it ideal for NLP pipelines, named entity recognition, relation extraction, and other text mining tasks. Free, no authentication required.
API Endpoints
Base URL
https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_json/{PMCID}/unicode
Retrieve by PMC ID
# JSON format (recommended for programmatic use)
curl "https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_json/PMC6267067/unicode"
# XML format
curl "https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_xml/PMC6267067/unicode"
# ASCII encoding (strips non-ASCII characters)
curl "https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_json/PMC6267067/ascii"
Retrieve by PubMed ID
# Convert PMID to PMCID first, then query
curl "https://www.ncbi.nlm.nih.gov/pmc/utils/idconv/v1.0/?ids=29346600&format=json"
# Returns: {"records": [{"pmid": "29346600", "pmcid": "PMC6267067", ...}]}
BioC JSON Structure
{
"source": "PMC",
"date": "2024-01-15",
"key": "collection.key",
"documents": [
{
"id": "PMC6267067",
"passages": [
{
"infons": {
"section_type": "TITLE",
"type": "title"
},
"offset": 0,
"text": "Article Title Here"
},
{
"infons": {
"section_type": "ABSTRACT",
"type": "abstract"
},
"offset": 25,
"text": "Background: This study investigates..."
},
{
"infons": {
"section_type": "INTRO",
"type": "paragraph"
},
"offset": 350,
"text": "The introduction text..."
}
]
}
]
}
Key fields:
passages[].infons.section_type: TITLE, ABSTRACT, INTRO, METHODS, RESULTS, DISCUSS, CONCL, REF, FIG, TABLEpassages[].offset: Character offset from document startpassages[].text: Plain text content of the passage
Python Usage
import requests
import json
def get_bioc_article(pmcid: str, fmt: str = "json") -> dict:
"""Fetch a PMC article in BioC format."""
url = f"https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_{fmt}/{pmcid}/unicode"
resp = requests.get(url, timeout=30)
resp.raise_for_status()
return resp.json() if fmt == "json" else resp.text
def extract_sections(bioc_doc: dict) -> dict:
"""Extract text organized by section type."""
sections = {}
for doc in bioc_doc.get("documents", []):
for passage in doc.get("passages", []):
section = passage.get("infons", {}).get("section_type", "OTHER")
text = passage.get("text", "")
sections.setdefault(section, []).append(text)
return {k: "\n".join(v) for k, v in sections.items()}
# Example: fetch and parse
article = get_bioc_article("PMC6267067")
sections = extract_sections(article)
print(f"Title: {sections.get('TITLE', 'N/A')}")
print(f"Abstract length: {len(sections.get('ABSTRACT', ''))} chars")
print(f"Sections found: {list(sections.keys())}")
Data Coverage
- PMC Open Access Subset: ~4M+ articles with CC licenses
- Author Manuscript Collection: NIH-funded author manuscripts
- Updates: New articles added daily
Rate Limits
- Follow NCBI standard: 3 requests per second
- For bulk access, use the PMC FTP service instead
- Add
tool=your_tool_name&[email protected]to requests for priority queue
Citation
When using this API in publications, cite:
Comeau DC, Wei CH, Islamaj Dogan R, Lu Z. PMC text mining subset in BioC: about 3 million full text articles and growing. Bioinformatics, btz070, 2019.
References
What ships with it
Read from the repository
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