ArticleGenome biology2025
catGRANULE 2.0: accurate predictions of liquid-liquid phase separating proteins at single amino acid resolution.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed.
- Unlocking the bacterial condensome: from "dark matter" to design.Molecular biology of the cell · 2026Article
- Phase Separation of SF3B1 Serves as a Critical Post-Transcriptional Regulator During Early Mouse Embryogenesis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- A practical guide to investigating biomolecular condensates: a comment from the plant community.Science China. Life sciences · 2026Review
- A machine learning framework for predicting and modulating condition-dependent protein phase separation.Nature communications · 2026Article
- Taxonomy-aware, disorder-matched benchmarking of phase-separating protein predictors.Genome biology · 2026Article
- Article
- amyloid-predict and LLPS-predict: Predicting phase separation propensities in the intrinsically disordered proteome.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- RNA-binding protein family diversification correlates with neural complexity across metazoan evolution.iScience · 2026Article
- USP7 at PML Nuclear Bodies: A Protein Interaction Network Perspective.International journal of molecular sciences · 2026Article
- Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective.Briefings in bioinformatics · 2026Review
- Engineering Design of Artificial Phase-Separating Proteins.Biotechnology journal · 2026Review
- Shifts in protein aggregate stability define proteostasis decline in the aging human brain.bioRxiv : the preprint server for biology · 2026Article
- Dynamic yet well-defined organization of the FUS RGG3 dense phase.Communications chemistry · 2026Article
- Exploring Disordered Regions of Human Spliceosome Proteins.The journal of physical chemistry letters · 2026Article
- Article
- From biomolecular condensates to functional nanomaterials: LLPS-inspired frameworks for nanoscale hydrogels and adaptive materials.Journal of nanobiotechnology · 2026Review
- Transcriptional outputs and condensates - formation and function.The New phytologist · 2026Review
- Revisiting the Small Heat Shock Protein Family inmicroPublication biology · 2026Article
- Biomolecular condensates: molecular structure, biological functions, diseases, and therapeutic targets.Molecular biomedicine · 2025Review
- BAV-LLPS: a database of bacterial, archaea, and virus liquid-liquid phase separation proteins.Bioinformatics (Oxford, England) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Liquid-liquid phase separation (LLPS) enables the formation of membraneless organelles, essential for cellular organization and implicated in diseases. We introduce catGRANULE 2.0 ROBOT, an algorithm integrating physicochemical properties and AlphaFold-derived structural features to predict LLPS at single-amino-acid resolution. The method achieves high performance and reliably evaluates mutation effects on LLPS propensity, providing detailed predictions of how specific mutations enhance or inhibit phase separation. Supported by experimental validations, including microscopy data, it predicts LLPS across diverse organisms and cellular compartments, offering valuable insights into LLPS mechanisms and mutational impacts. The tool is freely available at https://tools.tartaglialab.com/catgranule2 and https://doi.org/10.5281/zenodo.14205831 .
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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 Socratic graph.