Anatomy of an AI-Driven Molecular Design Workflow
Published:
How generative models, scoring and chemical filters come together into a practical loop that turns a target into testable molecules.
Posts by Tags
AI
Cheatsheet
My RDKit Cheatsheet
Published:
Cheatsheet for RDKit package in python: (1) Draw molecules in jupyter enviroment; (2) use with Pandas Dataframe (3) Descriptors/Fingerprints and (4) Similarity Search etc.
DGL
DGL Walkthrough 01: Data
Published:
A walk through of DGL library. Deep Graph library (DGL) is a Python package built for easy implementation of graph neural network model family on top of existing deep learning framework (e.g., Pytorch, MXNet etc.). More detials can be found on the official website.
Drug Design
Explainable AI in Drug Discovery: Why “Why” Matters
Published:
A model that predicts activity is useful. A model that tells a chemist which substructure drives that activity is something you can act on.
Anatomy of an AI-Driven Molecular Design Workflow
Published:
How generative models, scoring and chemical filters come together into a practical loop that turns a target into testable molecules.
Explainable AI
Explainable AI in Drug Discovery: Why “Why” Matters
Published:
A model that predicts activity is useful. A model that tells a chemist which substructure drives that activity is something you can act on.
Generative Models
Anatomy of an AI-Driven Molecular Design Workflow
Published:
How generative models, scoring and chemical filters come together into a practical loop that turns a target into testable molecules.
Graph Neural Networks
DGL Walkthrough 01: Data
Published:
A walk through of DGL library. Deep Graph library (DGL) is a Python package built for easy implementation of graph neural network model family on top of existing deep learning framework (e.g., Pytorch, MXNet etc.). More detials can be found on the official website.
Highlights of the Month
Highlights of the Month: May 2020
Published:
Keywords: ICLR 2020; multitask learning with fastai; fastai + huggingface; learn2learn
Highlights of the Month: April 2020
Published:
Key words: JupyterLab; NMR; WSL; NLP tutorial/recipes
Highlights of the Month: March 2020
Published:
Key words Sub-Word Tokenization; Ligand-Based Virtual Screening; Meta Learning; ELECTRA;
Highlights of the Month: February 2020
Published:
Key words for this month: Reformer; TMAP; libmolgrid;
Highlights of the Month: January 2020
Published:
Key words for this month: Functional Groups; Unsupervised/Self-supervised representation leaning; Generative Models;
Machine Learning
Explainable AI in Drug Discovery: Why “Why” Matters
Published:
A model that predicts activity is useful. A model that tells a chemist which substructure drives that activity is something you can act on.
RDKit
My RDKit Cheatsheet
Published:
Cheatsheet for RDKit package in python: (1) Draw molecules in jupyter enviroment; (2) use with Pandas Dataframe (3) Descriptors/Fingerprints and (4) Similarity Search etc.
TMAP
A walkthrough of TMAP
Published:
The notebook version is here.