CROssBAR Data API

Ebi

Ebi - CROssBAR Data API

CROssBAR is a comprehensive system that integrates large-scale biomedical data from various resources and enriches them with deep learning predictions to provide biologically meaningful modules displayed through interactive knowledge graphs. The API offers 12 endpoints for querying data stored in the CROssBAR database, enabling users to find information on proteins, activities, drugs, pathways, genes, and compounds. Additionally, the API supports the construction of knowledge graphs by linking nodes programmatically, allowing users to drive biological networks from different perspectives such as drug-centric, disease-centric, and gene-centric.

API Management

AI Tools

Data Management

Application Security

Analytics

Personas

Data Scientist

Easily query and analyze vast biomedical data from multiple sources like UniProt, ChEMBL, and Drugbank using our AI assistant. Seamlessly navigate through complex relationships between proteins, diseases, and drugs to uncover valuable insights for improving software products and making informed business decisions.

Use cases

Unlock Insights from Biomedical Data with Ease

Chat examples

Can you provide me with a list of proteins associated with a specific disease?

Sure! Based on your query, I have extracted a list of proteins related to the specified disease from our integrated databases. Here is the detailed information on their interactions, functions, and more. Is there anything else you would like to explore?

Machine Learning Engineer

Empower your machine learning projects by constructing dynamic knowledge graphs using our AI assistant. Connect nodes like proteins, diseases, and drugs programmatically to visualize intricate biological networks. Gain a deeper understanding of complex relationships within biomedical data for more accurate model training and predictions.

Use cases

Build Dynamic Knowledge Graphs for Enhanced Data Visualization

Chat examples

How can I link proteins, diseases, and drugs to create a comprehensive knowledge graph?

To construct a comprehensive knowledge graph, you can start by querying the 'proteins' endpoint to gather protein data related to specific diseases. Then, use the obtained information to identify targets and bio-activity measurements from the 'targets' endpoint. By following these steps and leveraging our API endpoints, you can seamlessly build a detailed knowledge graph. Would you like further assistance in this process?

Transforming user intents to actions with a genie touch