Fangping Wan
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  • Publications
    • 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
    • Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning
    • Tutorial: guidelines for the use of machine learning methods to mine genomes and proteomes for antibiotic discovery
    • Improving functional protein generation via foundation model-derived latent space likelihood optimization
    • Design of multimodal antibiotics against intracellular infections using deep learning
    • A generative artificial intelligence approach for antibiotic optimization
    • 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
    • Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth
    • Crowdsourced mapping of unexplored target space of kinase inhibitors
    • An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19
    • A novel machine learning based framework for modeling transcription elongation
    • MoTSE: an interpretable task similarity estimator for small molecular property prediction tasks
    • A novel machine learning framework for automated biomedical relation extraction from large-scale literature repositories
    • Secure multiparty computation for privacy-preserving drug discovery
    • 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
    • DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening
    • NeoDTI: neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
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MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Anities

Mar 5, 2020·
Shuya Li*
,
Fangping Wan*
,
Hantao Shu
,
Tao Jiang
,
Dan Zhao
,
Jianyang Zeng
· 0 min read
Site
Type
Journal article
Publication
Cell Systems, 2020 (also in RECOMB 2020)
Last updated on Mar 5, 2020
← Secure multiparty computation for privacy-preserving drug discovery May 1, 2020
EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality Prediction Feb 27, 2020 →