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Pipeline to explore information on genome editing using large language models and genome editing meta-database
Open accessPublished version of a preprint
Abstract
Genome editing (GE) is widely recognized as an effective and valuable technology in life sciences research. However, certain genes are difficult to edit depending on some factors such as the type of species, sequences, and GE tools. Therefore, confirming the presence or absence of GE practices in previous publications is crucial for the effective designing and establishment of research using GE. Although the Genome Editing Meta-database (GEM: https://bonohu.hiroshima-u.ac.jp/gem/) aims to provide as comprehensive GE information as possible, it does not indicate how each registered gene is involved in GE. In this study, we developed a systematic method for extracting essential GE information using large language models from the information based on GEM and GE-related articles. This approach allows for a systematic and efficient investigation of GE information that cannot be achieved using the current GEM alone. In addition, by converting the extracted GE information into metrics, we propose a potential application of this method to prioritize genes for future research. The extracted GE information and novel GE-related scores are expected to facilitate the efficient selection of target genes for GE and support the design of research using GE. Database URLs: https://github.com/szktkyk/extract_geinfo, https://github.com/szktkyk/visualize_geinfo
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Metadata
- Authors
- Suzuki, T., & Bono, H.
- Affiliations
- Hiroshima University (JP)
- Corresponding author
- Bono, Hidemasa
- Venue
- Database
- Publisher
- Oxford University Press (OUP)
- Published
- 2025
- Volume
- 2025
- ISSN
- 1758-0463 (ISSN-L)
- PMC
- PMC11890094
- OpenAlex
- W4408266186
- Cited by
- 1
- References
- 36
- Citations by year
- 2026: 1
- FWCI
- 0.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Database (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- University Fellowship Creation Project for Creating Scientific and Technological Innovation (JPMJFS2129)
- Program on Open Innovation Platform with Enterprises, Research Institute and Academia (JPMJPF2010)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- genome editing, large language models, information extraction
- MeSH terms
- Gene Editing, Large Language Models, Animals, Humans, Programming Languages, Databases, Genetic
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