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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://bitbucket.org/grumpy_kat/corresponding-projections

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Corresponding Projections for Orphan Screening

https://gitee.com/xiaoyibang/clipdrug

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CLDR: Contrastive Learning Drug Response Models from Natural Language Supervision

https://github.com/99andBeyond/Apollo1060

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Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning

https://github.com/99andBeyond/max-bellman-toy

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Maximum Reward Formulation In Reinforcement Learning

https://github.com/AIRI-Institute/nablaDFT

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$\nabla^2$DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials

https://github.com/ATOMconsortium/AMPL

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AMPL: A Data-Driven Modeling Pipeline for Drug Discovery

https://github.com/AegisIK/DistMLIP

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DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials

https://github.com/Augus1999/bayesian-flow-network-for-chemistry

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A Bayesian Flow Network Framework for Chemistry Tasks

https://github.com/BC3D/BC3D_2021

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Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats

https://github.com/Barabasi-Lab/AI-Bind

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AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands

https://github.com/BenevolentAI/MolBERT

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Molecular representation learning with language models and domain-relevant auxiliary tasks

https://github.com/BioSysLab/deepSIBA

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DeepSIBA: Chemical Structure-based Inference of Biological Alterations

https://github.com/BioinfoMachineLearning/DIPS-Plus

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DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction

https://github.com/BioinfoMachineLearning/DProQ

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DProQ: A Gated-Graph Transformer for Protein Complex Structure Assessment

https://github.com/BioinfoMachineLearning/DeepRefine

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EGR: Equivariant Graph Refinement and Assessment of 3D Protein Complex Structures

https://github.com/BiomedSciAI/biomed-multi-view

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Multi-view biomedical foundation models for molecule-target and property prediction

https://github.com/Brian-hongyan/DEG-substance-addiction

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Multiscale Topology in Interactomic Network: From Transcriptome to Antiaddiction Drug Repurposing

https://github.com/BrightBlueCheese/transformers_and_chemistry

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The Role of Model Architecture and Scale in Predicting Molecular Properties: Insights from Fine-Tuning RoBERTa, BART, and LLaMA

https://github.com/CRIPAC-DIG/Pin-Tuning

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Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction

https://github.com/CS-SAIL/UQ-GNN-ROC

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Conditional Prediction ROC Bands for Graph Classification

https://github.com/CVC-Lab/SAC-for-H-Bond-Learning

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Reinforcement Learning for Molecular Dynamics Optimization: A Stochastic Pontryagin Maximum Principle Approach

https://github.com/Ced3-han/PepFlowww

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Full-Atom Peptide Design based on Multi-modal Flow Matching

https://github.com/CongSun-dlut/CPI_extraction

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Chemical-protein Interaction Extraction via Gaussian Probability Distribution and External Biomedical Knowledge

https://github.com/DSPsleeporg/smiles-transformer

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SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery

https://github.com/Data-reindeer/MOCO

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Improving Molecular Pretraining with Complementary Featurizations

https://github.com/DeepGraphLearning/GraphAF

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GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

https://github.com/DevSlem/Mol-AIR

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Mol-AIR: Molecular Reinforcement Learning with Adaptive Intrinsic Rewards for Goal-directed Molecular Generation

https://github.com/DiXue98/PDVN

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Retrosynthetic Planning with Dual Value Networks

https://github.com/DongqiFu/DPPIN

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DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data

https://github.com/DrugAI/ACNet

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Activity Cliff Prediction: Dataset and Benchmark

https://github.com/DrugLT/ImDrug

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ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery

https://github.com/GSK-AI/meta-learning-qsar

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Meta-Learning Initializations for Low-Resource Drug Discovery

https://github.com/Gaskell-1206/Ensemble_DRP

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Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms

https://github.com/HIPS/neural-fingerprint

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Convolutional Networks on Graphs for Learning Molecular Fingerprints

https://github.com/HannesStark/EquiBind

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EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction

https://github.com/HelikarLab/MADRID

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COMO: A Pipeline for Multi-Omics Data Integration in Metabolic Modeling and Drug Discovery

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