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SMILES-BERT

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cmdc.200800408openalex-snapshot

Improving the Search Performance of Extended Connectivity Fingerprints through Activity‐Oriented Feature Filtering and Application of a Bit‐Density‐Dependent Similarity Function

inferredcites →https://doi.org/10.1007/11530084_13openalex-snapshot

Assigning Unique Keys to Chemical Compounds for Data Integration: Some Interesting Counter Examples

inferredcites →https://doi.org/10.1007/978-3-030-20351-1_36openalex-snapshot

Graph Convolutional Nets for Tool Presence Detection in Surgical Videos

inferredcites →https://doi.org/10.1007/978-3-319-46723-8_74openalex-snapshot

Subtype Cell Detection with an Accelerated Deep Convolution Neural Network

inferredcites →https://doi.org/10.1007/s10822-016-9938-8openalex-snapshot

Molecular graph convolutions: moving beyond fingerprints

inferredcites →https://doi.org/10.1016/j.cell.2018.02.010openalex-snapshot

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning

inferredcites →https://doi.org/10.1021/acs.jcim.6b00290openalex-snapshot

Computational Modeling of β-Secretase 1 (BACE-1) Inhibitors Using Ligand Based Approaches

inferredcites →https://doi.org/10.1021/c160017a018openalex-snapshot

The Generation of a Unique Machine Description for Chemical Structures-A Technique Developed at Chemical Abstracts Service.

inferredcites →https://doi.org/10.1021/ci00057a005openalex-snapshot

SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

inferredcites →https://doi.org/10.1021/ci100050topenalex-snapshot

Extended-Connectivity Fingerprints

inferredcites →https://doi.org/10.1021/ci3001277openalex-snapshot

ZINC: A Free Tool to Discover Chemistry for Biology

inferredcites →https://doi.org/10.1021/ci500749qopenalex-snapshot

Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe

inferredcites →https://doi.org/10.1021/jp202765copenalex-snapshot

Computational Design and Selection of Optimal Organic Photovoltaic Materials

inferredcites →https://doi.org/10.1093/nar/gkr1132openalex-snapshot

PubChem's BioAssay Database

inferredcites →https://doi.org/10.1098/rsif.2017.0387openalex-snapshot

Opportunities and obstacles for deep learning in biology and medicine

inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot

Densely Connected Convolutional Networks

inferredcites →https://doi.org/10.1109/cvpr.2017.683openalex-snapshot

Residual Attention Network for Image Classification

inferredcites →https://doi.org/10.1109/cvpr.2017.725openalex-snapshot

WSISA: Making Survival Prediction from Whole Slide Histopathological Images

inferredcites →https://doi.org/10.1145/3107411.3107424openalex-snapshot

Seq2seq Fingerprint

inferredcites →https://doi.org/10.1145/3233547.3233548openalex-snapshot

Seq3seq Fingerprint

inferredcites →https://doi.org/10.18653/v1/d15-1166openalex-snapshot

Effective Approaches to Attention-based Neural Machine Translation

inferredcites →https://doi.org/10.18653/v1/n19-1423openalex-snapshot

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

inferredcites →https://doi.org/10.48550/arxiv.1409.0473openalex-snapshot

Neural Machine Translation by Jointly Learning to Align and Translate

inferredcites →https://doi.org/10.48550/arxiv.1409.3215openalex-snapshot

Sequence to Sequence Learning with Neural Networks

inferredcites →https://doi.org/10.48550/arxiv.1502.02072openalex-snapshot

Massively Multitask Networks for Drug Discovery

inferredcites →https://doi.org/10.48550/arxiv.1509.09292openalex-snapshot

Convolutional Networks on Graphs for Learning Molecular Fingerprints

inferredcites →https://doi.org/10.48550/arxiv.1510.02855openalex-snapshot

AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery

inferredcites →https://doi.org/10.48550/arxiv.1705.03122openalex-snapshot

Convolutional Sequence to Sequence Learning

inferredcites →https://doi.org/10.48550/arxiv.1904.01038openalex-snapshot

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

inferredcites →https://doi.org/10.65215/2q58a426openalex-snapshot

Attention Is All You Need

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Prediction of Pic50 Bioactive Values Based on Knowledge Priors and Attention Neural Networks

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Machine Learning for Rational Electrolyte Design in Lithium Batteries: Bridging Macroscopic Performance and Physically Interpretable Descriptors

inferred← citeshttps://doi.org/10.1002/asia.70837openalex-snapshot

Transforming Molecular Science With Large Language Models: From Molecule Understanding to Autonomous Scientific Discovery

inferred← citeshttps://doi.org/10.1002/cem.70003openalex-snapshot

Improving Vapor Pressure Prediction Through Integration of Multiple Molecular Representations: A Super Learner Approach

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Wide and Cross GNNs: Cross‐Interactions and Parallel Scaling for Robust Chemical Property Prediction

inferred← citeshttps://doi.org/10.1002/cjce.25525openalex-snapshot

Artificial intelligence and machine learning at various stages and scales of process systems engineering

inferred← citeshttps://doi.org/10.1002/jcc.27315openalex-snapshot

Advances in machine learning with chemical language models in molecular property and reaction outcome predictions

inferred← citeshttps://doi.org/10.1002/jcc.70011openalex-snapshot

Mfgnn: Multi‐Scale Feature‐Attentive Graph Neural Networks for Molecular Property Prediction

inferred← citeshttps://doi.org/10.1002/marc.202500388openalex-snapshot

Benchmarking Large Language Models for Polymer Property Predictions

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Accelerating the integration of ChatGPT and other large‐scale AI models into biomedical research and healthcare

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Leveraging transformers‐based language models in proteome bioinformatics

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Foundation models for bioinformatics

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The Role of Artificial Intelligence for Drug Repurposing in Alzheimer’s Disease

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Machine Learning Applications in Chemical Kinetics and Thermochemistry

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Balancing Imbalanced Toxicity Models: Using MolBERT with Focal Loss

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Growing the Network—Generative AI

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Deep Learning for Polymer Property Prediction

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The Changing Face of Drug and Materials Discovery

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CMIF: A Cross-Modal Information Fusion Approach for Molecular Property Prediction

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Large Language Models in Drug Discovery

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Methods of Literary Text Analysis with the Help of Artificial Intelligence

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MolEncoder: Improved Masked Language Modeling for Molecules

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Convolutional Spiking Neural Networks with Molecular Fingerprints for Drug Discovery

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Compound Property Prediction Based on Multiple Different Molecular Features and Ensemble Learning

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MM-MolP: A Multimodal Self-supervised Framework via Cross-Modal Alignment and Dynamic Edge Modeling for Molecular Property Prediction

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Dual-Modality Representation Learning for Molecular Property Prediction

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Cross-Media Intelligence

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CRAFT: Consistent Representational Fusion of Three Molecular Modalities

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Enhanced Molecular Property Prediction with SMILES and Graph Aligned Contrastive Learning

inferred← citeshttps://doi.org/10.1007/978-981-97-4828-0_1openalex-snapshot

The AI Trends in Chemical Space for Drug Discovery

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Transformers and Large Language Models for Chemistry and Drug Discovery

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Biomedical Knowledge Representation Learning

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Large language models in radiogenomics: a comprehensive survey of applications from imaging to genetics

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3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information

inferred← citeshttps://doi.org/10.1007/s10115-025-02514-2openalex-snapshot

Enhancing molecular property prediction by fusing graph and sequence encoder representations

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TranGRU: focusing on both the local and global information of molecules for molecular property prediction

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Comparison study of dominant molecular sequence representation based on diffusion model

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Which chemical features are captured by ChemBERTa’s attention?

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Interpretable drug-target affinity prediction based on pre-trained models’ output as embeddings and based on structure-aware cross-attention for feature fusion

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Mol-SGGI: an attention-guided comprehensive molecular multi-representation learning and adaptive fusion framework for molecular property prediction

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A scalable multimodal graph neural network for drug combination response prediction

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FinBERT–MRC: Financial Named Entity Recognition Using BERT Under the Machine Reading Comprehension Paradigm

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Molecular pretraining models towards molecular property prediction

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Predicting residues involved in anti-DNA autoantibodies with limited neural networks

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Transformer-Based Mechanical Property Prediction for Polymer Matrix Composites

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Advancements in Molecular Property Prediction: A Survey of Single and Multimodal Approaches

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Large Language Models Meet Molecules: A Systematic Review of Advances and Challenges in AI-Driven Cheminformatics

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Prediction of human pharmacokinetic parameters incorporating SMILES information

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Molecular representations in bio-cheminformatics

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Next-generation pediatric care: nanotechnology-based and AI-driven solutions for cardiovascular, respiratory, and gastrointestinal disorders

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A Multi-view Molecular Pre-training with Generative Contrastive Learning

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RETRACTED ARTICLE: Deterministic functions for measuring human protein structural variations with merit based ensemble learning scheme for native classification

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A multimodal DTA prediction method based on triple-view contrastive learning

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Conf-GEM: A geometric information-assisted direct conformation generation model

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ChiralCat: Molecular chirality classification with enhanced spatial representation using learnable queries

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Directed message passing based on attention for prediction of molecular properties

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A quantum-transformer hybrid architecture for polymer property prediction: Addressing data sparsity issues

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Carbon-based molecular properties efficiently predicted by deep learning-based quantum chemical simulation with large language models

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eSFILES: Intelligent process flowsheet synthesis using process knowledge, symbolic AI, and machine learning

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AI-based language models powering drug discovery and development

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SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning

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Self-Supervised Contrastive Molecular Representation Learning with a Chemical Synthesis Knowledge Graph

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DrugSK: A Stacked Ensemble Learning Framework for Predicting Drug Combinations of Multiple Diseases

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Transformers for Molecular Property Prediction: Lessons Learned from the Past Five Years

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Quantum-Informed Molecular Representation Learning Enhancing ADMET Property Prediction

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From SMILES to Enhanced Molecular Property Prediction: A Unified Multimodal Framework with Predicted 3D Conformers and Contrastive Learning Techniques

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Natural Language Processing Methods for the Study of Protein–Ligand Interactions

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Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks

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Recent Advances in the Modeling of Ionic Liquids Using Artificial Neural Networks

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Machine Learning Classification of Chirality and Optical Rotation Using a Simple One-Hot Encoded Cartesian Coordinate Molecular Representation

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Application of Large Language Models in Drug-Induced Osteotoxicity Prediction

inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00950openalex-snapshot

Combining GCN Structural Learning with LLM Chemical Knowledge for Enhanced Virtual Screening

inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00986openalex-snapshot

SMILES Token Additivity Model with Interpretability and Generalizability for Fuel Property Predictions

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MolDecor: Leveraging Transformers to Decorate Bioactive Molecules for Property Optimization

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MycoPermeNet-v2: Improved Prediction of Mycomembrane Permeation Using Fusion Noisy Student Self-Distillation

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Dual Embedding: A Fine-Tuned Language Model Approach for Accurate Polymer Glass Transition Temperature Prediction

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Multi-Modal Fusion Frameworks of Subgraph-Optimized Graph Autoencoder for Molecular Property Prediction

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Polymer-Agent: Large Language Model Agent for Polymer Design

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HELM-BERT: Topology-Aware Representations for Chemically Modified Peptides

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Comprehensive Review of Contrastive and Generative Self-Supervised Learning for Small Molecular Representation

inferred← citeshttps://doi.org/10.1021/acs.jcim.6c00652openalex-snapshot

Scaling SMILES-Based Chemical Language Models for Therapeutic Peptide Engineering

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TextDTI: A Multimodal Context Representation Learning Framework for Drug–Target Interaction Prediction

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RetroMPA: A Molecular Property-Aware Auxiliary Framework for Enhancing Retrosynthesis Prediction

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PKP-Diffmol: A Physicochemical Knowledge-Prompt Encoding and Latent Diffusion Framework for Molecular Property Prediction

inferred← citeshttps://doi.org/10.1021/acs.jcim.6c01761openalex-snapshot

CUE: A Chemical Uncertainty-Aware Embedding Framework for Multimodal Drug Selectivity Prediction

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Toward Imbalanced Molecular Property Regression: A Benchmark Study and Interval-Aware Mixture of Experts

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AI-Driven Drug–Target Interaction Prediction: From Data Representation to Model Design

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GMSF: A Dual-Path Multimodal Framework for Enzyme Function Prediction via Difference Graph Encoding and Multiscale Semantic Fusion

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PointGAT: A Quantum Chemical Property Prediction Model Integrating Graph Attention and 3D Geometry

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A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era

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Relation-Aware Pretraining and Reaction Center Modeling for Chemical Reaction Graph Representation Learning

inferred← citeshttps://doi.org/10.1021/acs.jmedchem.4c00692openalex-snapshot

Enhancing Molecular Property Prediction through Task-Oriented Transfer Learning: Integrating Universal Structural Insights and Domain-Specific Knowledge

inferred← citeshttps://doi.org/10.1021/acs.jpca.3c04779openalex-snapshot

Recent Applications of Machine Learning in Molecular Property and Chemical Reaction Outcome Predictions

inferred← citeshttps://doi.org/10.1021/acs.jpca.5c00405openalex-snapshot

Rapid Discovery of Graphene Nanoflakes with Desired Absorption Spectra Using DFT and Bayesian Optimization with Neural Network Kernel

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Applications of Transformers in Computational Chemistry: Recent Progress and Prospects

inferred← citeshttps://doi.org/10.1021/acs.jpclett.5c02567openalex-snapshot

Extrapolating Foundation Generative Models with Physics: A Case Study of Exploring Peptide Conformations under Protein–Environment Interactions

inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.3c00129openalex-snapshot

Descriptor-Free Deep Learning QSAR Model for the Fraction Unbound in Human Plasma

inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.4c00311openalex-snapshot

Actionable Predictions of Human Pharmacokinetics at the Drug Design Stage

inferred← citeshttps://doi.org/10.1021/acsapm.5c00869openalex-snapshot

Decoding Structure–Optical Property Relationships in TiO2 Nanocomposites through Hybrid Features Integration

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Catalyst Energy Prediction with CatBERTa: Unveiling Feature Exploration Strategies through Large Language Models

inferred← citeshttps://doi.org/10.1021/acsearthspacechem.3c00009openalex-snapshot

Machine Learning for Ionization Potentials and Photoionization Cross Sections of Volatile Organic Compounds

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Accelerated Discovery of Macrocyclic CDK2 Inhibitor QR-6401 by Generative Models and Structure-Based Drug Design

inferred← citeshttps://doi.org/10.1021/acsomega.5c13460openalex-snapshot

MFDR-DTI: Multisource Feature Decoupling and Dual-Level Reorganization Fusion for Accurate Drug–Target Interaction Prediction

inferred← citeshttps://doi.org/10.1021/acssuschemeng.5c08057openalex-snapshot

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

inferred← citeshttps://doi.org/10.1021/jacsau.4c01160openalex-snapshot

A Perspective on Foundation Models in Chemistry

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Algebraic graph-assisted bidirectional transformers for molecular property prediction

inferred← citeshttps://doi.org/10.1038/s41467-022-28494-3openalex-snapshot

A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals

inferred← citeshttps://doi.org/10.1038/s41467-023-39868-6openalex-snapshot

polyBERT: a chemical language model to enable fully machine-driven ultrafast polymer informatics

inferred← citeshttps://doi.org/10.1038/s41467-024-49372-0openalex-snapshot

Topological regression as an interpretable and efficient tool for quantitative structure-activity relationship modeling

inferred← citeshttps://doi.org/10.1038/s41467-024-50469-9openalex-snapshot

Chemical language modeling with structured state space sequence models

inferred← citeshttps://doi.org/10.1038/s41467-024-51321-wopenalex-snapshot

Data-driven quantum chemical property prediction leveraging 3D conformations with Uni-Mol+

inferred← citeshttps://doi.org/10.1038/s41467-024-53751-yopenalex-snapshot

MolE: a foundation model for molecular graphs using disentangled attention

inferred← citeshttps://doi.org/10.1038/s41467-024-55374-9openalex-snapshot

A data-driven group retrosynthesis planning model inspired by neurosymbolic programming

inferred← citeshttps://doi.org/10.1038/s41467-025-59628-yopenalex-snapshot

Token-Mol 1.0: tokenized drug design with large language models

inferred← citeshttps://doi.org/10.1038/s41467-025-66685-wopenalex-snapshot

Molecular Motif Learning as a pretraining objective for molecular property prediction

inferred← citeshttps://doi.org/10.1038/s41524-023-01016-5openalex-snapshot

TransPolymer: a Transformer-based language model for polymer property predictions

inferred← citeshttps://doi.org/10.1038/s41524-024-01372-wopenalex-snapshot

A Ring2Vec description method enables accurate predictions of molecular properties in organic solar cells

inferred← citeshttps://doi.org/10.1038/s41524-025-01652-zopenalex-snapshot

Unified multimodal multidomain polymer representation for property prediction

inferred← citeshttps://doi.org/10.1038/s41524-025-01774-4openalex-snapshot

Chemical foundation model-guided design of high ionic conductivity electrolyte formulations

inferred← citeshttps://doi.org/10.1038/s41564-025-02114-4openalex-snapshot

A generative artificial intelligence approach for the discovery of antimicrobial peptides against multidrug-resistant bacteria

inferred← citeshttps://doi.org/10.1038/s41598-021-90259-7openalex-snapshot

A merged molecular representation learning for molecular properties prediction with a web-based service

inferred← citeshttps://doi.org/10.1038/s41598-025-15265-5openalex-snapshot

Adjusted imbalance ratio leads to effective AI-based drug discovery against infectious disease

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Geometry-aware lightweight convolutional network for efficient molecular property prediction

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Molecular contrastive learning of representations via graph neural networks

inferred← citeshttps://doi.org/10.1038/s42256-023-00639-zopenalex-snapshot

Regression Transformer enables concurrent sequence regression and generation for molecular language modelling

inferred← citeshttps://doi.org/10.1038/s42256-023-00647-zopenalex-snapshot

Structure-inducing pre-training

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A bioactivity foundation model using pairwise meta-learning

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Reusability Report: Evaluating the performance of a meta-learning foundation model on predicting the antibacterial activity of natural products

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Recent advances in molecular representation methods and their applications in scaffold hopping

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Pre-trained molecular language models with random functional group masking

inferred← citeshttps://doi.org/10.1039/d1dd00052gopenalex-snapshot

A transfer learning protocol for chemical catalysis using a recurrent neural network adapted from natural language processing

inferred← citeshttps://doi.org/10.1039/d2dd00058jopenalex-snapshot

A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing

inferred← citeshttps://doi.org/10.1039/d2dd00087copenalex-snapshot

Assessment of chemistry knowledge in large language models that generate code

inferred← citeshttps://doi.org/10.1039/d3dd00040kopenalex-snapshot

Generalizing property prediction of ionic liquids from limited labeled data: a one-stop framework empowered by transfer learning

inferred← citeshttps://doi.org/10.1039/d3dd00088eopenalex-snapshot

Evaluating the roughness of structure–property relationships using pretrained molecular representations

inferred← citeshttps://doi.org/10.1039/d3dd00119aopenalex-snapshot

Using natural language processing (NLP)-inspired molecular embedding approach to predict Hansen solubility parameters

inferred← citeshttps://doi.org/10.1039/d4dd00077copenalex-snapshot

Understanding the language of molecules: predicting pure component parameters for the PC-SAFT equation of state from SMILES

inferred← citeshttps://doi.org/10.1039/d4dd00366gopenalex-snapshot

Developing large language models for quantum chemistry simulation input generation

inferred← citeshttps://doi.org/10.1039/d4sc03744hopenalex-snapshot

Unlocking comprehensive molecular design across all scenarios with large language model and unordered chemical language

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A review of large language models and autonomous agents in chemistry

inferred← citeshttps://doi.org/10.1039/d4sc90043jopenalex-snapshot

A focus on molecular representation learning for the prediction of chemical properties

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InChINet: a self-supervised molecular representation learning framework leveraging SMILES and InChI

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