Fangping Wan
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    • Generative latent diffusion language modeling yields anti-infective synthetic peptides
    • Deep learning reveals antibiotics in the archaeal proteome
    • Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
    • Predicting and generating antibiotics against future pathogens with ApexOracle
    • Large Scale Multi-Task Bayesian Optimization with Large Language Models
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    • Improving functional protein generation via foundation model-derived latent space likelihood optimization
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    • Analyzing Large-Scale Single-Cell RNA-Seq Data Using Coreset
    • Deep-learning-enabled antibiotic discovery through molecular de-extinction
    • Machine Learning for Antimicrobial Peptide Identification and Design
    • Deep learning tools to accelerate antibiotic discovery
    • Improving molecular property prediction through a task similarity enhanced transfer learning strategy
    • Deep generative models for peptide design
    • A community challenge for a pancancer drug mechanism of action inference from perturbational profile data
    • A deep-learning framework for multi-level peptide-protein interaction prediction
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    • A novel machine learning based framework for modeling transcription elongation
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    • MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Anities
    • EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality Prediction
    • ACME: pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks
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Deep-learning-enabled antibiotic discovery through molecular de-extinction

Jun 11, 2024·
Fangping Wan*
,
Marcelo D. T. Torres*
,
Jacqueline Peng
,
Cesar De La Fuente
· 0 min read
Site
Type
Journal article
Publication
Nature Biomedical Engineering, 2024
Last updated on Jun 11, 2024
← Analyzing Large-Scale Single-Cell RNA-Seq Data Using Coreset Jun 24, 2024
Machine Learning for Antimicrobial Peptide Identification and Design May 1, 2024 →