ArticleNucleic acids research2026
PhaSepDB 3.0: a comprehensive knowledgebase of phase separation-related proteins from AI-assisted curation.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A practical guide to investigating biomolecular condensates: a comment from the plant community.Science China. Life sciences · 2026Review
- Multiaxial Biophysical Control of Oncogenic Phase Separation by Indoleamines: A Proof-of-Concept Synthesis of Landscape-Level Regulation.Journal of pineal research · 2026Review
- Taxonomy-aware, disorder-matched benchmarking of phase-separating protein predictors.Genome biology · 2026Article
- Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective.Briefings in bioinformatics · 2026Review
- Assessing the performance of multimodal large language models in experimental information extraction from liquid-liquid phase separation literature.Scientific reports · 2026Article
- Interpretable and generative deep learning models explicate phase separating intrinsically disordered motifs.Nature communications · 2026Article
- The 2026 Nucleic Acids Research database issue and the online molecular biology database collection.Nucleic acids research · 2026Article
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Authors and funding
11 authors.
Funding
Abstract
Phase separation (PS) is a fundamental principle driving the formation of membraneless organelles (MLOs), which are critical for various cellular functions and pathological conditions. We present PhaSepDB 3.0 (https://db.phasep.pro/), a significantly updated knowledgebase of proteins related to PS. To address the challenges of curating a vast body of literature, we have implemented a novel human-AI collaborative workflow that integrates a large language model (LLM)-based agentic system with expert verification, enabling a major expansion and enrichment of the database. PhaSepDB 3.0 now contains 3,484 expert-curated entries for 1849 PS-related proteins, more than doubling the content of the previous version. The annotation framework has been restructured to capture deeper insights, including functional relevance, experimental evidence, and the intrinsic and extrinsic regulations of PS. A key new feature is the protein-wise summary page, which synthesizes data from multiple publications to provide a comprehensive overview of each protein's PS behaviour and functional relevance. With redesigned, user-friendly web interfaces, PhaSepDB 3.0 serves as a critical resource for the community, supporting researchers to explore the intricate basis of PS and its biological implications in greater detail.
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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.