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Property Prediction

Property prediction involves forecasting or estimating a molecule's inherent physical and chemical properties based on information derived from its structural characteristics. It facilitates high-throughput evaluation of an extensive array of molecular properties, enabling the virtual screening of compounds. Additionally, it provides the means to predict the unknown attributes of new molecules, thereby bolstering research efficiency and reducing development times.

Papers

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Showing 301–325 of 691 papers

TitleStatusHype
Multi-modal Contrastive Learning with Negative Sampling Calibration for Phenotypic Drug Discovery—0
Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements—0
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs—0
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph LearningCode0
Data-Driven Self-Supervised Graph Representation LearningCode0
EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations—0
Category-Specific Topological Learning of Metal-Organic Frameworks—0
RingFormer: A Ring-Enhanced Graph Transformer for Organic Solar Cell Property PredictionCode0
Language model driven: a PROTAC generation pipeline with dual constraints of structure and property—0
Tokenizing 3D Molecule Structure with Quantized Spherical Coordinates—0
MolMetaLM: a Physicochemical Knowledge-Guided Molecular Meta Language ModelCode0
Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials—0
Investigating Graph Neural Networks and Classical Feature-Extraction Techniques in Activity-Cliff and Molecular Property Prediction—0
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and ChemistryCode0
Cuvis.Ai: An Open-Source, Low-Code Software Ecosystem for Hyperspectral Processing and ClassificationCode0
SeqProFT: Applying LoRA Finetuning for Sequence-only Protein Property Predictions—0
GeomCLIP: Contrastive Geometry-Text Pre-training for MoleculesCode0
Material Property Prediction with Element Attribute Knowledge Graphs and Multimodal Representation Learning—0
Two-Stage Pretraining for Molecular Property Prediction in the Wild—0
Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property PredictionCode0
MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property PredictionCode0
Subgraph Aggregation for Out-of-Distribution Generalization on GraphsCode0
Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery—0
PepDoRA: A Unified Peptide Language Model via Weight-Decomposed Low-Rank Adaptation—0
Homomorphism Counts as Structural Encodings for Graph LearningCode0
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