06/01/2022
ChEMBL is an open database with over 18 million bioactivity measurements. It manually curates bioactivity data that is typically published in an unstructured, often unsearchable format.
ChEMBL makes data collection for machine learning less labor-intensive, but do you know how to handle this tool through an API? π€
The benefit of using the ChEMBL API in Python is the possibility to manipulate data with libraries like , , and , gain insights, and build machine learning models.
If you don't know how to use this tool, check out this tutorial for beginners.
Here are the topics covered in the article:
𧬠How to install the ChEMBL API on Colab
π― To perform a biological target search
π‘ A Data Exploratory example
How to get started on ChEMBL Database. In this tutorial: how to install the ChEMBL API on Colab, perform a target search and a data exploratory example.