mlsanityData to 7 Oct 2026

SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules

arXiv 1703.07076 ↗First posted 21 Mar 2017cs.LGcited by 58

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Abstract (arXiv)

Simplified Molecular Input Line Entry System (SMILES) is a single line text representation of a unique molecule. One molecule can however have multiple SMILES strings, which is a reason that canonical SMILES have been defined, which ensures a one to one correspondence between SMILES string and molecule. Here the fact that multiple SMILES represent the same molecule is explored as a technique for data augmentation of a molecular QSAR dataset modeled by a long short term memory (LSTM) cell based neural network. The augmented dataset was 130 times bigger than the original. The network trained with the augmented dataset shows better performance on a test set when compared to a model built with only one canonical SMILES string per molecule. The correlation coefficient R2 on the test set was improved from 0.56 to 0.66 when using SMILES enumeration, and the root mean square error (RMS) likewise fell from 0.62 to 0.55. The technique also works in the prediction phase. By taking the average per molecule of the predictions for the enumerated SMILES a further improvement to a correlation coefficient of 0.68 and a RMS of 0.52 was found.

Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Mar 2017.

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Citing papers per year: 2021: 9; 2022: 10; 2023: 5; 2024: 10; 2025: 11; 2026: 13.

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  1. 2021Large-Scale Chemical Language Representations Capture Molecular Structure and Propertiescited by 203
  2. 2023Large Language Models on Graphs: A Comprehensive Surveycited by 190
  3. 2021Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction predictioncited by 66
  4. 2022MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Designcited by 66
  5. 2022Regression Transformer: Concurrent sequence regression and generation for molecular language modelingcited by 49
  6. 2025KL-Regularized Reinforcement Learning is Designed to Mode Collapsecited by 29
  7. 2022Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Modelcited by 25
  8. 2021MolGrow: A Graph Normalizing Flow for Hierarchical Molecular Generationcited by 22
  9. 2022A smile is all you need: Predicting limiting activity coefficients from SMILES with natural language processingcited by 19
  10. 2021TITAN: T Cell Receptor Specificity Prediction with Bimodal Attention Networkscited by 15
  11. 2024Saturn: Sample-efficient Generative Molecular Design using Memory Manipulationcited by 14
  12. 2024BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learningcited by 12
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  1. 2024LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR Modelscited by 11
  2. 2021AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learningcited by 10
  3. 2025MolLangBench: A Comprehensive Benchmark for Language-Prompted Molecular Structure Recognition, Editing, and Generationcited by 8
  4. 2022Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representationcited by 6
  5. 2022Deep learning methods for drug response prediction in cancer: predominant and emerging trendscited by 6
  6. 2023Language models in molecular discoverycited by 6
  7. 2022Pre-training Transformers for Molecular Property Prediction Using Reaction Predictioncited by 5
  8. 2022Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILEScited by 5
  9. 2023Recent advances in artificial intelligence for retrosynthesiscited by 5
  10. 2025Synergistic Benefits of Joint Molecule Generation and Property Predictioncited by 5
  11. 2022Investigation of a Data Split Strategy Involving the Time Axis in Adverse Event Prediction Using Machine Learningcited by 3
  12. 2021Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspectivecited by 2
  13. 2024SAFE setup for generative molecular designcited by 2
  14. 2024NPGPT: Natural Product-Like Compound Generation with GPT-based Chemical Language Modelscited by 2
  15. 2025MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Designcited by 2
  16. 2025Circuits, Features, and Heuristics in Molecular Transformerscited by 2
  17. 2021Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19cited by 1
  18. 2021Analysis of training and seed bias in small molecules generated with a conditional graph-based variational autoencoder -- Insights for practical AI-driven molecule generationcited by 1
  19. 2023Transfer Learning across Different Chemical Domains: Virtual Screening of Organic Materials with Deep Learning Models Pretrained on Small Molecule and Chemical Reaction Datacited by 1
  20. 2024Synthetic data enables faster annotation and robust segmentation for multi-object grasping in cluttercited by 1
  21. 2026Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimizationcited by 1
  22. 2026Augmenting Molecular Language Models with Local n-gram Memorycited by 1
  23. 2021Evening the Score: Targeting SARS-CoV-2 Protease Inhibition in Graph Generative Models for Therapeutic Candidatescited by 0
  24. 2022Investigation of chemical structure recognition by encoder-decoder models in learning progresscited by 0
  25. 2023Data augmentation for machine learning of chemical process flowsheetscited by 0
  26. 2024Empirical Evidence for the Fragment level Understanding on Drug Molecular Structure of LLMscited by 0
  27. 2024A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Predictioncited by 0
  28. 2024GUISE: Graph GaUssIan Shading watErmarkcited by 0
  29. 2024It Takes Two to Tango: Directly Optimizing for Constrained Synthesizability in Generative Molecular Designcited by 0
  30. 2025A Transformer Model for Predicting Chemical Products from Generic SMARTS Templates with Data Augmentationcited by 0
  31. 2025Evaluating Effects of Augmented SELFIES for Molecular Understanding Using QK-LSTMcited by 0
  32. 2025Look the Other Way: Designing 'Positive' Molecules with Negative Data via Task Arithmeticcited by 0
  33. 2025SHA-256 Infused Embedding-Driven Generative Modeling of High-Energy Molecules in Low-Data Regimescited by 0
  34. 2025Reaction Prediction via Interaction Modeling of Symmetric Difference Shingle Setscited by 0
  35. 2025ChemFixer: Correcting Invalid Molecules to Unlock Previously Unseen Chemical Spacecited by 0
  36. 2026SIGMA: Semantic Identifier Grouping for Molecular Autoregressioncited by 0
  37. 2026Reinforced Reasoning for End-to-End Retrosynthetic Planningcited by 0
  38. 2026Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spacescited by 0

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