Published inTowards Data Science·PinnedModeling Protein-Ligand Interactions with Atomic Convolutional Neural NetworksExploit local structure of three-dimensional molecular complexes to predict binding affinities — Nathan C. Frey This post was co-authored by Bharath Ramsundar from DeepChem. ACNNs learn chemical features from the three-dimensional structure of protein-ligand complexes. In this post, we show how to use the open-source implementation of ACNNs in DeepChem and the PDBbind dataset to predict protein-ligand binding affinities.Deep Learning6 min readDeep Learning6 min read
Published inTowards Data Science·Feb 14, 2022FastFlows: Flow-Based Models for Molecular Graph GenerationDeep learning invertible transformations for efficient generative modeling — Nathan C. Frey This post was co-authored by Bharath Ramsundar from Deep Forest Sciences. Normalizing flow-based deep generative models learn a transformation between a simple base distribution and a target distribution. In this post, we show how to use FastFlows to model a dataset of small molecules and generate new…Deep Learning8 min readDeep Learning8 min read
Published inTowards Data Science·May 17, 2021MoleculeNet Part 1: Datasets for Deep Learning in the Chemical and Life SciencesTowards an “ImageNet moment” in Molecular Machine Learning — This post was co-authored by Bharath Ramsundar from DeepChem. Benchmark datasets are an important driver of progress in machine learning. Unlike computer vision and natural language processing, the diversity and complexity of datasets in chemical and life sciences make these fields largely resistant to attempts to curate benchmarks that are…Deep Learning5 min readDeep Learning5 min read
Published inTowards Data Science·Apr 15, 2021How and Why to Share Scientific CodeA simple guide to reproducible research without becoming a software engineer — When you do an experiment, whether that’s in a lab or on a computer, you generate data that needs to be analyzed. If your analysis involves new methods, algorithms, or simulations, you probably wrote some code along the way. …Software Development6 min readSoftware Development6 min read
Feb 15, 2021What is Materials Science?Why materials science is a mystery to most people and why it’s important When I (used to) get a haircut or take an Uber, the #1 question I got is the same one everyone else gets: “What do you do?” If I’m feeling really adventurous, I might say “I’m a…Materials Science4 min readMaterials Science4 min read
Published inTowards Data Science·Jan 20, 2021Getting Started in Materials InformaticsHow to get started doing research in materials informatics (data science + materials science) — In this post I share resources and recommendations for getting involved in materials informatics research. As it becomes increasingly more expensive and time-consuming to discover and engineer new materials to address some of our most pressing global challenges (human health, food and water security, climate, etc.), we need materials scientists…Data Science6 min readData Science6 min read
Dec 14, 2020Quantum MOMsSearching for materials with multiple quantum properties What is a MOM? Patient, supportive, loving…no, not quite, in the cold world of materials physics, a MOM is a multi-order material. That means a material with two or more quantum “orders,” where electrons in the material are organized in some way because…Physics5 min readPhysics5 min read
Published inTowards Data Science·Nov 18, 2020Positive and Unlabeled Materials Machine LearningHow semi-supervised learning is used to accelerate materials synthesis — Nathan C. Frey This post was co-authored with Vishnu Harshith from IIT Madras Many real-world problems involve datasets where only some of the data is labeled and the rest is unlabeled. In this post, we discuss our implementation of semi-supervised learning for predicting the synthesizability of theoretical materials. When we…Machine Learning8 min readMachine Learning8 min read
Sep 18, 2020Quantum and brain-like technologies with “defective” materialsMachine learning and physics-based simulations to design materials with defects In this paper, published in ACS Nano, I show how machine learning and computer simulations can be used to design materials with defects for new types of computing and information storage. You might think that “defects” are always a bad…Machine Learning5 min readMachine Learning5 min read
Sep 2, 2020Book Review: Something Deeply HiddenSomething Deeply Hidden by Sean Carroll is really good and you should buy it. If you want to read a more concise and thoughtful review that was published when the book actually came out, I recommend Sabine Hossenfelder’s. …Books4 min readBooks4 min read
