Mock sample for your project: Open States API v3

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Open States API v3

openstates.org

Version: 2021.08.02


Use this API in your project

Integrate third-party APIs faster by using "Open States API v3" ready-to-use mock sample. Mocking this API will help you accelerate your development lifecycles and improves your integration tests' quality and reliability by accounting for random failures, slow response time, etc.
It also helps reduce your dependency on third-party APIs: no more accounts to create, API keys to provision, accesses to configure, unplanned downtime, etc.

Description

More documentation
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As of August 2021 we are working to restore experimental support for committees.
During this period please note that data is not yet available for all states
and the exact format of the committees endpoints may change slightly depending on user feedback.
If you have any issues or questions use our
GitHub Issues to give feedback.

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About CROssBAR & data
CROssBAR: Comprehensive Resource of Biomedical Relations with Deep Learning Applications and Knowledge Graph Representations
CROssBAR is a comprehensive system that integrates large-scale biomedical data from various resources e.g UniProt, ChEMBL, Drugbank, EFO, HPO, InterPro & PubChem and stores them in a new NoSQL database, enrich these data with deep learning based prediction of relations between numerous biomedical entities, rigorously analyse the enriched data to obtain biologically meaningful modules and display them to the user via easy to interpret, interactive and heterogeneous knowledge graphs.
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Knowledge graphs
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An example for the part of the background queries on the CROssBAR API during the construction of a knowledge graph,
(with the aim of keeping the example simple, we have only included the processes related to pathways, genes/proteins and drugs/compounds)
In this example, we would like to find bio-active compounds (with a pChEMBL value threshold of at least 6.0) & drugs targeting all proteins belonging to "WNT ligand biogenesis and trafficking" pathway (based on Reactome pathway annotations).
This can be achieved by using endpoints listed on this swagger documentation as illustrated in following steps-
Find bio-active compounds (with a pChEMBL value threshold of at least 6.0) & drugs targeting all proteins belonging to "WNT ligand biogenesis and trafficking" pathway (based on Reactome annotations)
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From the collection of ’moleculechemblid’s obtained in step3, we query “/molecules” endpoint to get the compounds that are interacting with the genes/proteins belonging to the “WNT ligand biogenesis and trafficking” pathway.

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