Building machine learning models for ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) predictions puts you on the front lines of drug discovery. It’s exciting work—pushing the boundaries of what’s possible, using algorithms to predict how molecules behave in the body. But the part they don’t tell you? The real battle isn’t in designing models or…
All posts tagged machine learning
Nested Cross-Validation & Cross-Validation Series – Part 1
A few people have asked me to explain and share the code for Nested Cross-Validation. I think it makes sense for me to explain the basics of whats and whys in using the NeCV first before diving into the code, so I will be covering these topics in four separate blog posts. For part 1,…
Mordred_MRC_Descriptors in Python – Part 5
This is the last of the five-part series tutorial of the blog post, Computing Molecular Descriptors – Intro, in the context of drug discovery. The goal of this post to explain the python code on creating new descriptors such as MRC (developed in MacrolactoneDB study) and using Mordred descriptors. What are MRC descriptors? MRC descriptors were…