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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/HibaKob/MicroBundleCompute

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MicroBundleCompute: Automated segmentation, tracking, and analysis of subdomain deformation in cardiac microbundles

https://github.com/HongxinXiang/EDBench

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EDBench: Large-Scale Electron Density Data for Molecular Modeling

https://github.com/Hugh415/HimNet

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Learning Hierarchical Interaction for Accurate Molecular Property Prediction

https://github.com/IDEA-XL/SubgDiff

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SubGDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning

https://github.com/Jianing-Qiu/Awesome-Healthcare-Foundation-Models

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Large AI Models in Health Informatics: Applications, Challenges, and the Future

https://github.com/Jiaxin-Xu/PairwiseShapley

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From Abstract to Actionable: Pairwise Shapley Values for Explainable AI

https://github.com/JinA0218/drugood-densify

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Robust Molecular Property Prediction via Densifying Scarce Labeled Data

https://github.com/LLNL/FAST

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Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference

https://github.com/LabJunBMI/Latent-Space-Peptide-Analogues-Generation

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Exploring Latent Space for Generating Peptide Analogs Using Protein Language Models

https://github.com/Lirain21/UniMatch

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UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery

https://github.com/Lowpassfilter/tCNNS-Project

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Drug cell line interaction prediction

https://github.com/MIRALab-USTC/DD-RetroDCVAE

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Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables

https://github.com/MolecularAI/uq4dd

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Temporal Distribution Shift in Real-World Pharmaceutical Data: Implications for Uncertainty Quantification in QSAR Models

https://github.com/MoleculeAI/TAGMol

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TAGMol: Target-Aware Gradient-guided Molecule Generation

https://github.com/NVIDIA/DeepLearningExamples

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A Framework for Large Scale Synthetic Graph Dataset Generation

https://github.com/Namkyeong/3DMRL

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3D Interaction Geometric Pre-training for Molecular Relational Learning

https://github.com/Nanfeizhilu/DTI_WkNNIR

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Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery

https://github.com/PaccMann/paccmann_sarscov2

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PaccMann$^{RL}$ on SARS-CoV-2: Designing antiviral candidates with conditional generative models

https://github.com/PaddlePaddle/PaddleHelix

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Docking-based Virtual Screening with Multi-Task Learning

https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/drug_target_interaction/sman

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Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction

https://github.com/PattanaikL/GeoMol

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GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles

https://github.com/PattanaikL/chiral_gnn

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Message Passing Networks for Molecules with Tetrahedral Chirality

https://github.com/PerforatedAI/PerforatedAI-API

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Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks

https://github.com/PurdueMINDS/RelationalPooling

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Relational Pooling for Graph Representations

https://github.com/QHwan/PretrainDPI

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Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interaction

https://github.com/QizhiPei/BioT5

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BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations

https://github.com/Ryan-Rhys/Heteroscedastic-BO

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Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation

https://github.com/SBrandeis/k-core-embedding

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About Graph Degeneracy, Representation Learning and Scalability

https://github.com/SeonghwanSeo/RxnFlow

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Generative Flows on Synthetic Pathway for Drug Design

https://github.com/Shef-AIRE/FMM_TC

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Foundation-Model-Boosted Multimodal Learning for fMRI-based Neuropathic Pain Drug Response Prediction

https://github.com/Shen-Lab/DeepAffinity

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DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks

https://github.com/SobihanSurendran/LGS

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Latent Guided Sampling for Combinatorial Optimization

https://github.com/Steven51516/FlexMol

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FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning

https://github.com/SubsetSelection/EquiVSet

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Learning Neural Set Functions Under the Optimal Subset Oracle

https://github.com/THGLab/SynLlama

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SynLlama: Generating Synthesizable Molecules and Their Analogs with Large Language Models

https://github.com/THUDM/ProteinLM

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Modeling Protein Using Large-scale Pretrain Language Model

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