https://github.com/khodabandeh-ali/bokdiff
공식 코드BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation
Papers with Code 아카이브
Drug Design
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/koziarskilab/scent
공식 코드Scalable and Cost-Efficient de Novo Template-Based Molecular Generation
https://github.com/lee-jwon/bind
공식 코드https://github.com/linhaowei1/tfg-flow
공식 코드TFG-Flow: Training-free Guidance in Multimodal Generative Flow
https://github.com/liugangcode/Llamole
공식 코드Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
https://github.com/lucagl/moad_ligandfinder
공식 코드https://github.com/luost26/3d-generative-sbdd
공식 코드https://github.com/mahsasheikh/DrugGen
공식 코드DrugGen: Advancing Drug Discovery with Large Language Models and Reinforcement Learning Feedback
https://github.com/marcelkh13/clapim
공식 코드ClaPIM: Scalable Sequence CLAssification using Processing-In-Memory
https://github.com/marcopodda/fragment-based-dgm
공식 코드A Deep Generative Model for Fragment-Based Molecule Generation
https://github.com/minkaixu/alidiff
공식 코드Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
https://github.com/minys233/dynafomer
공식 코드https://github.com/mirunacrt/synflownet
공식 코드SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
https://github.com/ml-jku/hopfield-layers
공식 코드https://github.com/morgancthomas/molscore
공식 코드ACEGEN: Reinforcement learning of generative chemical agents for drug discovery
https://github.com/nguyenlabuky/ggl-eta-score
공식 코드https://github.com/nguyenlabuky/ggl-mutation
공식 코드GGL-PPI: Geometric Graph Learning to Predict Mutation-Induced Binding Free Energy Changes
https://github.com/ninglab/gellmo-c
공식 코드Large Language Models for Controllable Multi-property Multi-objective Molecule Optimization
https://github.com/octavian-ganea/equidock_public
공식 코드Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
https://github.com/orgw/TurboHopp
공식 코드TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Models
https://github.com/pengxingang/pocket2mol
공식 코드Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
https://github.com/polowitty/covdocker
공식 코드CovDocker: Benchmarking Covalent Drug Design with Tasks, Datasets, and Solutions
https://github.com/prescient-design/StrainRelief
공식 코드https://github.com/qiangbo1222/uni-rxn-official
공식 코드https://github.com/quanlin-wu/unisite
공식 코드https://github.com/rafalkarczewski/simplesbdd
공식 코드What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?
https://github.com/rahuln/lm-bio-kgc
공식 코드Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical Study
https://github.com/rea1991/geo-nav
공식 코드GEO-Nav: a geometric dataset of voltage-gated sodium channels
https://github.com/ribesstefano/PROTAC-Degradation-Predictor
공식 코드https://github.com/rifqat/Comparative-Analysis
공식 코드A Comparative Analysis of the Ensemble Methods for Drug Design
https://github.com/ruqizhang/dpfastmh
공식 코드DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference
https://github.com/ryanchen227/lemon
공식 코드https://github.com/sail-sg/gdpo
공식 코드https://github.com/samuelstanton/lambo
공식 코드Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders
https://github.com/sandbox-quantum/idolpro-scoring
공식 코드Guided Multi-objective Generative AI to Enhance Structure-based Drug Design
https://github.com/securefederatedai/openfl
공식 코드Federated Discrete Denoising Diffusion Model for Molecular Generation with OpenFL
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.