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message: "If you use GenerRNA in your research, please cite the article below."
title: "GenerRNA: A generative pre-trained language model for de novo RNA design"
abstract: >-
GenerRNA is a generative pre-trained language model for de novo RNA design,
based on a Transformer decoder-only architecture. It generates novel RNA
sequences in a zero-shot manner or after fine-tuning, without requiring prior
structural information.
type: software
authors:
- family-names: Zhao
given-names: Yichong
affiliation: "The University of Tokyo"
- family-names: Oono
given-names: Kenta
affiliation: "Preferred Networks, Inc."
- family-names: Takizawa
given-names: Hiroki
affiliation: "Preferred Networks, Inc."
- family-names: Kotera
given-names: Masaaki
affiliation: "Preferred Networks, Inc."
email: kotera@preferred.jp
repository-code: "https://huggingface.co/pfnet/GenerRNA"
url: "https://huggingface.co/pfnet/GenerRNA"
license: MIT
keywords:
- RNA design
- de novo design
- generative model
- language model
- transformer
- RNA generation
- computational biology
- bioinformatics
- drug discovery
preferred-citation:
type: article
title: "GenerRNA: A generative pre-trained language model for de novo RNA design"
authors:
- family-names: Zhao
given-names: Yichong
- family-names: Oono
given-names: Kenta
- family-names: Takizawa
given-names: Hiroki
- family-names: Kotera
given-names: Masaaki
journal: "PLOS ONE"
year: 2024
month: 10
volume: 19
issue: 10
start: "e0310814"
doi: "10.1371/journal.pone.0310814"
publisher:
name: "Public Library of Science"
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