ArticleDigital discovery2025
BitBIRCH: efficient clustering of large molecular libraries.
Article in Digital discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Efficient visualization of chemical space.Chemical science · 2026Article
- Diversity Beats Size Scaling for Chemical Language Models.npj drug discovery · 2026Article
- Transformers for molecular property prediction: domain adaptation efficiently improves performance.Journal of cheminformatics · 2026Article
- PyRMD Studio: A Unified Suite for Next-Generation, AI-Powered Virtual Screening.Journal of chemical information and modeling · 2026Article
- Chemical space visualization at scale: a survey of end-to-end pipelines and dataset-size archetypes.Journal of cheminformatics · 2026Review
- Nested TMAPs to Visualize Billions of Molecules.Journal of chemical information and modeling · 2026Article
- mdBIRCH for Fast, Scalable, Online Clustering of Molecular Dynamics Trajectories.Journal of chemical theory and computation · 2026Article
- Divide and Cluster: The DIVINE Framework for Deterministic Top-Down Analysis of Molecular Dynamics Trajectories.Journal of chemical information and modeling · 2026Article
- Best practices to cluster large molecular libraries.bioRxiv : the preprint server for biology · 2026Article
- Interpretable and Scalable Similarity Metrics for DNA-Encoded Library Design Using Generative Topographic Mapping.Molecular informatics · 2026Article
- mdBIRCH for Fast, Scalable, Online Clustering of Molecular Dynamics Trajectories.bioRxiv : the preprint server for biology · 2025Article
- BitBIRCH-Lean: chemical space in the palm of your workstation.bioRxiv : the preprint server for biology · 2025Article
- Undersampling techniques for large datasets.bioRxiv : the preprint server for biology · 2025Article
- Efficiently finding activity cliffs.bioRxiv : the preprint server for biology · 2025Article
- Growth vs Diversity: A Time-Evolution Analysis of the Chemical Space.Journal of chemical information and modeling · 2025Article
- CADENCE: Clustering Algorithm─Density-Based Exploration and Novelty Clustering with Efficiency.Journal of chemical information and modeling · 2025Article
- iSIM-Sigma: Efficient Standard Deviation Calculation for Molecular Similarity.Journal of chemical information and modeling · 2025Article
- Hierarchical Extended Linkage Method (HELM)'s Deep Dive into Hybrid Clustering Strategies.Journal of chemical information and modeling · 2025Article
- BitBIRCH Clustering Refinement Strategies.Journal of chemical information and modeling · 2025Article
- Extended Quality (eQual): Radial Threshold Clustering Based onJournal of chemical information and modeling · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
The widespread use of Machine Learning (ML) techniques in chemical applications has come with the pressing need to analyze extremely large molecular libraries. In particular, clustering remains one of the most common tools to dissect the chemical space. Unfortunately, most current approaches present unfavorable time and memory scaling, which makes them unsuitable to handle million- and billion-sized sets. Here, we propose to bypass these problems with a time- and memory-efficient clustering algorithm, BitBIRCH. This method uses a tree structure similar to the one found in the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm to ensure
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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.