Advancing plant biology through deep learning-powered natural language processing
Author:
Funder
China Sponsorship Council
Agence Nationale de la Recherche
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00299-024-03294-9.pdf
Reference116 articles.
1. Abramson J, Adler J, Dunger J et al (2024) Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630:493–500. https://doi.org/10.1038/s41586-024-07487-w
2. Almagro Armenteros JJ, Johansen AR, Winther O, Nielsen H (2020) Language modelling for biological sequences – curated datasets and baselines. BioRxiv. https://doi.org/10.1101/2020.03.09.983585
3. Almeida-Silva F, Van de Peer Y (2023) Whole-genome duplications and the long-term evolution of gene regulatory networks in angiosperms. Mol Biol Evol. https://doi.org/10.1093/molbev/msad141
4. Amani K, Shivnauth V, Castroverde CDM (2023) CBP60-DB: An AlphaFold-predicted plant kingdom-wide database of the CALMODULIN-BINDING PROTEIN 60 protein family with a novel structural clustering algorithm. Plant Direct 7:e509. https://doi.org/10.1002/pld3.509
5. Amaratunga T (2023) What makes LLMs large? In: Amaratunga T (ed) Understanding Large Language Models. Apress, Berkeley, pp 81–117
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