GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation

Authors

Shanfeng Zhu (ORCID: https://orcid.org/0000-0002-6067-5312)
Hiroshi Mamitsuka (ORCID: https://orcid.org/0000-0002-6607-5617)
Shaojun Wang (ORCID: https://orcid.org/0000-0003-0467-8911)
Huiying Yan
Hancheng Liu

Institutions

Kyoto University (JP)
Fudan University (CN)
Shanghai Innovative Research Center of Traditional Chinese Medicine (CN)
Institute of Art (PL)
Instituto de Investigaciones Químicas (ES)
Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
Institute of Science and Technology
Kyoto University Institute for Chemical Research
Aalto University (FI)

Publication Details

Journal: Bioinformatics
Published: 2024-09-01
DOI: https://doi.org/10.1093/bioinformatics/btae401
Citations: 9
Primary Topic: Machine Learning in Bioinformatics
Type: article
Field-Weighted Citation Impact: 2.10

Funders

Ministry of Education, Culture, Sports, Science and Technology
National Natural Science Foundation of China
Academy of Finland
Higher Education Discipline Innovation Project
Japan Society for the Promotion of Science

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article

GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation

Shanfeng Zhu, Hiroshi Mamitsuka, Shaojun Wang, Huiying Yan et al.

Sep 1, 2024

9 citations

Bioinformatics

Machine Learning in Bioinformatics

2.10

article

GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation

Shanfeng Zhu, Hiroshi Mamitsuka, Shaojun Wang, Huiying Yan, Hancheng Liu

September 1, 2024article en

9 citations

Abstract

No abstract available for this paper.

BioinformaticsVol. 40(Supplement_2)

Kyoto University (JP), Fudan University (CN), Shanghai Innovative Research Center of Traditional Chinese Medicine (CN), Institute of Art (PL), Instituto de Investigaciones Químicas (ES), Shanghai Center for Brain Science and Brain-Inspired Technology (CN), Institute of Science and Technology, Kyoto University Institute for Chemical Research, Aalto University (FI)

Ministry of Education, Culture, Sports, Science and Technology, National Natural Science Foundation of China, Academy of Finland, Higher Education Discipline Innovation Project, Japan Society for the Promotion of Science

Quality Education

Openalex Percentile: Top 13%

Machine Learning in Bioinformatics

2.10

DOI Open Access PDF OpenAlex

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