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Updated: Feb 13, 2026

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生物情報学の大型言語モデル

Wei Ruan¹, Yanjun Lyu², Jing Zhang²

¹School of Computing University of Georgia Athens Georgia USA.

Quantitative biology (Beijing, China)

|February 12, 2026

まとめ

バイオインフォマティクス特有の言語モデル (BioLMs) は急速に進歩し,疾患診断と薬剤発見のための新しいツールを提供しています. このレビューでは,BioLMの進化,応用,課題,およびバイオインフォマティックの将来の方向性を分析しています.

科学分野:

バイオインフォマティックス
コンピュータ生物学コンピュータ生物学
医療における人工知能

背景:

大型言語モデル (LLM) は急速に進化しています.
バイオインフォマティクス特有の言語モデル (BioLMs) は,強力なツールとして浮上しています.
BioLMsの包括的な分析が必要である.

研究の目的:

BioLMs.の徹底的なレビューを提供するために.
その進化,分類,特徴を分析する.
訓練方法論,データセット,評価フレームワークを検証する.

主な方法:

既存のBioLMsの文献レビューと分析.
アーキテクチャとアプリケーションに基づいてBioLMの分類.
訓練データ,計算方法,評価メトリックの検討.

主要な成果:

バイオLMは,疾患診断,薬剤発見,ワクチン開発において多様な応用がある.
主な課題には,データプライバシー,解釈可能性,バイアス,ドメインの適応などがあります.
新興のトレンドは,より洗練された生物学的および臨床的応用に向けています.

結論:

BioLMは,バイオインフォマティクスと臨床実務において,変革の可能性を秘めています.
課題に取り組むことは,責任ある開発と展開に不可欠です.
将来の研究は,複雑な生物学的問題に対するバイオLMの進歩に重点を置くべきである.

キーワード:

バイオインフォマティクス特有の言語モデル生物学的システム生物学的システムバイオメディカルAI 大規模な言語モデルがあります.ライフアクティブファクター

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