ML for protein engineering seminar series

A bi-weekly seminar series focused on recent work in machine learning for protein engineering.

For information on this seminar series and upcoming speakers, visit our website and twitter!

https://www.ml4proteinengineering.com/
https://twitter.com/ml4proteins

All seminars will be recorded and released on YouTube following the live Zoom session.

Early Career Seminar Series #6: Prof. Pranam Chatterjee
Early Career Seminar Series #6: Prof. Pranam Chatterjee
Early Career Seminar Series #5: Prof. Possu Huang
Early Career Seminar Series #5: Prof. Possu Huang
Early Career Seminar Series #4: Prof. Wengong Jin
Early Career Seminar Series #4: Prof. Wengong Jin
Functional alignment of protein language models via reinforcement learning
Functional alignment of protein language models via reinforcement learning
Серия семинаров по ранней карьере №3: Профессор Брайан Хай
Серия семинаров по ранней карьере №3: Профессор Брайан Хай
Flexible Antibody Design with Multimodal Bayesian Flow Networks
Flexible Antibody Design with Multimodal Bayesian Flow Networks
Early Career Seminar Series #2: Prof. Noelia Ferruz
Early Career Seminar Series #2: Prof. Noelia Ferruz
Early Career Seminar Series #1: Prof. Mohammed AlQuraishi
Early Career Seminar Series #1: Prof. Mohammed AlQuraishi
Deep learning guided design of protease substrates
Deep learning guided design of protease substrates
Atom level enzyme active site scaffolding using RFdiffusion2
Atom level enzyme active site scaffolding using RFdiffusion2
Computational design of serine hydrolases
Computational design of serine hydrolases
Learning millisecond protein dynamics from what is missing in NMR spectra
Learning millisecond protein dynamics from what is missing in NMR spectra
MotifBench: A standardized protein design benchmark for motif-scaffolding problems
MotifBench: A standardized protein design benchmark for motif-scaffolding problems
Genome modeling and design across all domains of life with Evo 2
Genome modeling and design across all domains of life with Evo 2
Targeting protein–ligand neosurfaces with a generalizable deep learning tool
Targeting protein–ligand neosurfaces with a generalizable deep learning tool
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
Proteina: Scaling Flow-based Protein Structure Generative Models
Proteina: Scaling Flow-based Protein Structure Generative Models
Concept Bottleneck Language Models for Protein Design
Concept Bottleneck Language Models for Protein Design
InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders
InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders
Mapping the combinatorial coding between olfactory receptors and perception with deep learning
Mapping the combinatorial coding between olfactory receptors and perception with deep learning
Multistate and functional protein design using RoseTTAFold sequence space diffusion
Multistate and functional protein design using RoseTTAFold sequence space diffusion
ProTrek: Navigating the Protein Universe through Tri-Modal Contrastive Learning
ProTrek: Navigating the Protein Universe through Tri-Modal Contrastive Learning
AI-driven de novo Enzyme Design
AI-driven de novo Enzyme Design
The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling
The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling
Template-based protein editing using Raygun
Template-based protein editing using Raygun
Lessons from implementing AlphaFold3 in the wild
Lessons from implementing AlphaFold3 in the wild
Tokenized and Continuous Embedding Compressions of Protein Sequence and Structure (CHEAP)
Tokenized and Continuous Embedding Compressions of Protein Sequence and Structure (CHEAP)
Adapting protein language models for structure-conditioned design
Adapting protein language models for structure-conditioned design
Rapid protein evolution by few-shot learning with a protein language model
Rapid protein evolution by few-shot learning with a protein language model