기타 데이터
Allergenicity Prediction
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AccessionKGD10764698
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Submission date2026-06-17
Project Detail
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Accession
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KAP242380 |
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프로젝트의 영문 제목
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Animal-Derived Allergenic Protein Sequences
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프로젝트의 국문 제목
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프로젝트의 영문 설명
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A comprehensive animal protein dataset was constructed for allergenicity prediction by integrating animal-derived allergen sequences and non-allergen protein sequences from publicly available allergen databases and UniProt. The allergen dataset includes proteins from animal-related sources such as mites, insects, milk, egg, fish, shellfish, meat, venom-producing organisms, and other animal taxa. Non-allergen proteins were collected from UniProt and assigned to the animal category based on organism-level taxonomy information. Where possible, non-allergen proteins were selected from the same or related animal-source organisms as those represented in the allergen dataset to reduce organism-level bias. This design helps the model focus on allergen-associated sequence features rather than simply distinguishing proteins by biological source. In total, 36,054 animal-derived protein sequences were compiled, including 1,480 allergen sequences and 34,574 non-allergen sequences, providing a curated resource for protein language model-based allergenicity prediction and explainable deep learning analysis.
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프로젝트의 국문 설명
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BioSample
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AccessionKAS24201783
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생명체 명
Metazoa -
샘플 종류
Model organism or animal
Metadata
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범주
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기타(직접입력) - Protein Sequences |
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인체유래데이터여부
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NO |
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제목
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Allergenicity Prediction |
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키워드
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Allergenicity prediction, Protein language models, Explainable deep learning |
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파일 설명
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Header: ID, Label, Domain, Database Source; Seq: Protein sequence |
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공개 날짜
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2026-06-09 |
File