Artificial intelligence to shed light on the algal dark proteomes
Nelson et al. developed LA⁴SR, a large-scale language-model framework to classify translated open reading frames (ORFeomes) across ten algal phyla. LA⁴SR achieves near-complete protein classification coverage even for algal dark proteomes, where alignment tools often return "no hit." The framework provides a leap forward for high-throughput protein classification in algae and could be a promising tool for better classifying proteins from many organisms.
Authors
- Éric Dubreucq (ORCID: https://orcid.org/0000-0002-8904-504X)
- Maxence Plouviez (ORCID: https://orcid.org/0000-0001-6824-697X)
Institutions
- Université de Montpellier (FR)
- Ingénierie des Agropolymères et Technologies Emergentes (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Institut Agro Montpelier (FR)
- Massey University (NZ)
- Cawthron Institute (NZ)
Publication Details
- Journal
- Patterns
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1016/j.patter.2025.101421
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00