Papers with Code 아카이브
Protein-Ligand Affinity Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 2
- 보존된 평가 기록
- 10
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems
Protein-ligand binding representation learning from fine-grained interactions
Towards antigenic peptide discovery with better MHC-I binding prediction and improved benchmark methodology
Efficient and Accurate Physics-aware Multiplex Graph Neural Networks for 3D Small Molecules and Macromolecule Complexes
High Performance of Gradient Boosting in Binding Affinity Prediction
Interpreting BERT architecture predictions for peptide presentation by MHC class I proteins
Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity
A Point Cloud-Based Deep Learning Strategy for Protein-Ligand Binding Affinity Prediction
ResAtom System: Protein and Ligand Affinity Prediction Model Based on Deep Learning
Ranking-based Convolutional Neural Network Models for Peptide-MHC Binding Prediction
HLA class I binding prediction via convolutional neural networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.