Poster "drug discovery" Papers
27 papers found
Conference
AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation
Wenyu Zhu, Jianhui Wang, Bowen Gao et al.
Automatic Auxiliary Task Selection and Adaptive Weighting Boost Molecular Property Prediction
Zhiqiang Zhong, Davide Mottin
ChemAgent: Self-updating Memories in Large Language Models Improves Chemical Reasoning
Xiangru Tang, Tianyu Hu, Muyang Ye et al.
Concept Bottleneck Language Models For Protein Design
Aya Ismail, Tuomas Oikarinen, Amy Wang et al.
DecoyDB: A Dataset for Graph Contrastive Learning in Protein-Ligand Binding Affinity Prediction
Yupu Zhang, Zelin Xu, Tingsong Xiao et al.
Drug-TTA: Test-Time Adaptation for Drug Virtual Screening via Multi-task Meta-Auxiliary Learning
Ao Shen, Ming'zhi Yuan, Yingfan MA et al.
Efficient Biological Data Acquisition through Inference Set Design
Ihor Neporozhnii, Julien Roy, Emmanuel Bengio et al.
Fast and Accurate Blind Flexible Docking
Zizhuo Zhang, Lijun Wu, Kaiyuan Gao et al.
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
Xiangxin Zhou, Yi Xiao, Haowei Lin et al.
Iterative Substructure Extraction for Molecular Relational Learning with Interactive Graph Information Bottleneck
Shuai Zhang, Junfeng Fang, Xuqiang Li et al.
MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds
Leon Hetzel, Johanna Sommer, Bastian Rieck et al.
Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model
Dongki Kim, Wonbin Lee, Sung Ju Hwang
MorphoDiff: Cellular Morphology Painting with Diffusion Models
Zeinab Navidi, Jun Ma, Esteban Miglietta et al.
OligoGym: Curated Datasets and Benchmarks for Oligonucleotide Drug Discovery
Rachapun Rotrattanadumrong, Carlo De Donno
PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching
Daniel Rose, Oliver Wieder, Thomas Seidel et al.
Reinforced Active Learning for Large-Scale Virtual Screening with Learnable Policy Model
Yicong Chen, Jiahua Rao, Jiancong Xie et al.
Rethinking Graph Prompts: Unraveling the Power of Data Manipulation in Graph Neural Networks
Chenyi Zi, Bowen LIU, Xiangguo SUN et al.
Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation
Chenbin Zhang, Zhiqiang Hu, Jiang Chuchu et al.
Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design
Lianghong Chen, Dongkyu Kim, Mike Domaratzki et al.
UniGEM: A Unified Approach to Generation and Property Prediction for Molecules
Shikun Feng, Yuyan Ni, Lu yan et al.
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design
Leo Klarner, Tim G. J. Rudner, Garrett Morris et al.
Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Seojin Kim, Jaehyun Nam, Sihyun Yu et al.
Entropy-Reinforced Planning with Large Language Models for Drug Discovery
Xuefeng Liu, Chih-chan Tien, Peng Ding et al.
Predicting Dose-Response Curves with Deep Neural Networks
Pedro A. Campana, Paul Prasse, Tobias Scheffer
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Songtao Liu, Hanjun Dai, Yue Zhao et al.
Projecting Molecules into Synthesizable Chemical Spaces
Shitong Luo, Wenhao Gao, Zuofan Wu et al.
Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design
Quan Nguyen, Adji Bousso Dieng