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SIBiLS PMC customizable search API


This API allows to perform a fully customizable search for valuable annotated full-texts in PubMed Central. The power of SIBiLS is based on the efficiency of Elasticsearch engines, and on the rich Lucene query language, which allows to investigate a large panel of searching strategies. For example: basic search with keywords or entity identifiers (“ZBED1” or “NP_NX_O96006”), searches in specified fields (“figures_captions: ZBED1” or “annotations_str: genes”), boosting fields or query parts, Boolean, exploiting identified concepts or identified concept types...) The input is thus a Lucene json query. The output is the Elasticsearch ranked result set, ranked by relevance, in its native json format; for each retrieved full-text (up to 10,000 per request), a relevance score and the indexed content are included.

API endpoint :

Mandatory input : keywords (&keywords=) for simple search, or json_query (&json_query=) for customizable search.

Example : simple search (&keywords) for PMC full-texts containing the "BRCA2" keyword in full-text

Example : customizable search (&json_query) with a Lucene style json query

{"query": {"bool" : {"must": {"match" : { "figures_capations" : "Digitoxin metabolism" }},"should" : {"match" : { "annotations_str" : "GO" }},"boost": 1}}}

Code sample : a python script for demonstrating POST calls to the API, with multiple examples of Lucene style queries, is available at

Query language : json queries for Elasticsearch are described in


Output is an Elasticsearch response (json formatted), and includes retrieval scores for each citation.

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