ArticleACS omega2021
Siamese Recurrent Neural Network with a Self-Attention Mechanism for Bioactivity Prediction.
Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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Who cites it
14 citing papers in PubMed.
- Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms.Chemical reviews · 2026Review
- NCIVISION: A Siamese Neural Network for Molecular Similarity Prediction MEP and RDG Images.Molecules (Basel, Switzerland) · 2025Article
- Going beyond SMILES enumeration for data augmentation in generative drug discovery.Digital discovery · 2025Article
- Beyond Tanimoto: a learned bioactivity similarity index enhances ligand discovery.Frontiers in bioinformatics · 2025Article
- Advancing Ionic Liquid Research with pSCNN: A Novel Approach for Accurate Normal Melting Temperature Predictions.ACS omega · 2024Article
- Leveraging bounded datapoints to classify molecular potency improvements.RSC medicinal chemistry · 2024Article
- PECAN Predicts Patterns of Cancer Cell Cytostatic Activity of Natural Products Using Deep Learning.Journal of natural products · 2024Article
- Finding the most potent compounds using active learning on molecular pairs.Beilstein journal of organic chemistry · 2024Article
- BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity Representation.ACS omega · 2023Article
- DeepDelta: predicting ADMET improvements of molecular derivatives with deep learning.Journal of cheminformatics · 2023Article
- The rise of automated curiosity-driven discoveries in chemistry.Chemical science · 2023Review
- Cheminformatics and artificial intelligence for accelerating agrochemical discovery.Frontiers in chemistry · 2023Review
- Dense Residual LSTM-Attention Network for Boiler Steam Temperature Prediction with Uncertainty Analysis.ACS omega · 2022Article
- Application of random forest based on semi-automatic parameter adjustment for optimization of anti-breast cancer drugs.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Activity prediction plays an essential role in drug discovery by directing search of drug candidates in the relevant chemical space. Despite being applied successfully to image recognition and semantic similarity, the Siamese neural network has rarely been explored in drug discovery where modelling faces challenges such as insufficient data and class imbalance. Here, we present a Siamese recurrent neural network model (SiameseCHEM) based on bidirectional long short-term memory architecture with a self-attention mechanism, which can automatically learn discriminative features from the SMILES representations of small molecules. Subsequently, it is used to categorize bioactivity of small molecules via
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.