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Drug Discovery

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하위 태스크: 3
평가표: 28
보존된 평가 기록: 96

Drug discovery is the task of applying machine learning to discover new candidate drugs.

<span style="color:grey; opacity: 0.6">( Image credit: A Turing Test for Molecular Generators )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/csubiogroup/dtiam

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DTIAM: A unified framework for predicting drug-target interactions, binding affinities and activation/inhibition mechanisms

https://github.com/csubiogroup/pgmg

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PGMG: A Pharmacophore-Guided Deep Learning Approach for Bioactive Molecular Generation

https://github.com/cvignac/top-n

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Top-N: Equivariant set and graph generation without exchangeability

https://github.com/daenuprobst/anon_aichem

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Social and environmental impact of recent developments in machine learning on biology and chemistry research

https://github.com/dahuilangda/biocheminsight

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BioChemInsight: An Open-Source Toolkit for Automated Identification and Recognition of Optical Chemical Structures and Activity Data in Scientific Publications

https://github.com/dancewithDianTong/COMBOO

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Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimation

https://github.com/deargen/cmg

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Controlled Molecule Generator for Optimizing Multiple Chemical Properties

https://github.com/deepgraphlearning/torchdrug

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TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery

https://github.com/dengjianyuan/Survey_AI_Drug_Discovery

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Artificial Intelligence in Drug Discovery: Applications and Techniques

https://github.com/dengjianyuan/respite_mpp

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Unraveling Key Elements Underlying Molecular Property Prediction: A Systematic Study

https://github.com/deno-v/tgm-dlm

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Text-Guided Molecule Generation with Diffusion Language Model

https://github.com/deqiankong/sgds

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Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting

https://github.com/dhroth/c5t5

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C5T5: Controllable Generation of Organic Molecules with Transformers

https://github.com/diego-alvarado/nlp_for_pharma_manufacturing

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Natural Language Processing tools for Pharmaceutical Manufacturing Information Extraction from Patents

https://github.com/divelab/AIRS

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A Latent Diffusion Model for Protein Structure Generation

https://github.com/divelab/DIG

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Spherical Message Passing for 3D Graph Networks

https://github.com/divelab/MoleculeProp

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Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery

https://github.com/divelab/graphbp

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Generating 3D Molecules for Target Protein Binding

https://github.com/dkrlab/Heter-LP-code

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Heter-LP: A heterogeneous label propagation algorithm and its application in drug repositioning

https://github.com/dmamur/elembert

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Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties

https://github.com/dmis-lab/EquiCPI

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EquiCPI: SE(3)-Equivariant Geometric Deep Learning for Structure-Aware Prediction of Compound-Protein Interactions

https://github.com/dmis-lab/cradle-vae

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CRADLE-VAE: Enhancing Single-Cell Gene Perturbation Modeling with Counterfactual Reasoning-based Artifact Disentanglement

https://github.com/dockstring/dockstring

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DOCKSTRING: easy molecular docking yields better benchmarks for ligand design

https://github.com/dqwang122/eatlm

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On Pre-trained Language Models for Antibody

https://github.com/drigoni/ComparisonsDGM

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A Systematic Assessment of Deep Learning Models for Molecule Generation

https://github.com/drugd/msda

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Zero-shot Learning of Drug Response Prediction for Preclinical Drug Screening

https://github.com/edapinenut/ppflow

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PPFlow: Target-aware Peptide Design with Torsional Flow Matching

https://github.com/eigenvivek/grad-camo

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Grad-CAMO: Learning Interpretable Single-Cell Morphological Profiles from 3D Cell Painting Images

https://github.com/elucidator8918/Fed-ML-Chem

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Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data Sources

https://github.com/exalearn/covid-drug-design

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Evening the Score: Targeting SARS-CoV-2 Protease Inhibition in Graph Generative Models for Therapeutic Candidates

https://github.com/fabiankruger/molprivacy

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Publishing Neural Networks in Drug Discovery Might Compromise Training Data Privacy

https://github.com/facebookresearch/forwardgnn

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Forward Learning of Graph Neural Networks

https://github.com/fengshikun/frad

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Fractional Denoising for 3D Molecular Pre-training

https://github.com/fengyuewuya/equipocket

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EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction

https://github.com/fiezt/Transductive-Linear-Bandit-Code

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Sequential Experimental Design for Transductive Linear Bandits

https://github.com/franco-solis/graphvf-code

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GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow

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