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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 301–350 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
Category-Specific Topological Learning of Metal-Organic Frameworks—0
EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations—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
SeqProFT: Applying LoRA Finetuning for Sequence-only Protein Property Predictions—0
Cuvis.Ai: An Open-Source, Low-Code Software Ecosystem for Hyperspectral Processing and ClassificationCode0
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
PepDoRA: A Unified Peptide Language Model via Weight-Decomposed Low-Rank Adaptation—0
Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery—0
Homomorphism Counts as Structural Encodings for Graph LearningCode0
From Tokens to Materials: Leveraging Language Models for Scientific DiscoveryCode0
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property PredictionCode0
Text-Guided Multi-Property Molecular Optimization with a Diffusion Language Model—0
HELM: Hierarchical Encoding for mRNA Language Modeling—0
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction—0
Large-Scale Knowledge Integration for Enhanced Molecular Property PredictionCode0
KA-GNN: Kolmogorov-Arnold Graph Neural Networks for Molecular Property Prediction—0
UniGEM: A Unified Approach to Generation and Property Prediction for Molecules—0
WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction—0
TapWeight: Reweighting Pretraining Objectives for Task-Adaptive Pretraining—0
Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable TargetsCode0
Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property PredictionCode0
Molecular topological deep learning for polymer property prediction—0
Scalable Multi-Task Transfer Learning for Molecular Property Prediction—0
Task Addition in Multi-Task Learning by Geometrical Alignment—0
Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries—0
Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on Chemical Structure—0
Evaluating the Performance and Robustness of LLMs in Materials Science Q&A and Property Predictions—0
Smirk: An Atomically Complete Tokenizer for Molecular Foundation Models—0
Molecular Graph Representation Learning via Structural Similarity InformationCode0
Regression with Large Language Models for Materials and Molecular Property Prediction—0
Efficient Training of Transformers for Molecule Property Prediction on Small-scale Datasets—0
CrysAtom: Distributed Representation of Atoms for Crystal Property Prediction—0
Self-supervised learning for crystal property prediction via denoising—0
Do Graph Neural Networks Work for High Entropy Alloys?Code0
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