CELLM:自然言語処理と人工知能による合成遺伝子回路設計の橋渡し
Lucas Abello Castillo1, Martín Gutiérrez Pescarmona1
1Facultad de Ingeniería y Ciencias, Universidad Diego Portales, Av. Ejército Libertador 441, 8370191 Santiago, RM, Chile.
ACS synthetic biology
|September 4, 2025
まとめ
この研究はCELLMを紹介しています CELLMはCelloのような合成生物学ツールと 大規模な言語モデルを統合する新しいシステムです 自然言語による 遺伝子回路の設計を可能にし 合成生物学をより容易に入手できます
科学分野:
- 合成生物学
- コンピュータ生物学
- バイオ情報学
背景:
- 遺伝子回路の設計は複雑で 合成生物学のアクセシビリティと効率を妨げています
- 現在の設計ツールには 生物工学の専門知識が必要です
研究 の 目的:
- 自然言語の指示を用いた遺伝回路の作成,分析,最適化のための統合システム (CELLM) を開発する.
- 自然言語処理と 機能的な生物学的デザインの間のギャップを 埋めるためです
主な方法:
- Python の LangChain フレームワークを介して,Cello ソフトウェア (v2.1) を大規模な言語モデル (DeepSeek-R1, Phi-4) と統合する.
- テキスト記述を遺伝子回路設計に自動翻訳する.
- 生物学的要件を解釈し,論理的な最適化を行うためにLLMを使用します.
主要な成果:
- セルロのような合成生物学設計ツールとLLMを統合した最初のシステムを実証しました.
- 機能的な遺伝子回路の設計に促すのです 遺伝子回路の設計に促すのです
- CELLMは回路合成と最適化プロセスを自動化する.
結論:
- CELLMは合成生物学の設計でLLMを使用するための先例を確立しています.
- このシステムは 遺伝子回路のプロトタイプ化への 入り口を大幅に低減します
- このアプローチにより,合成生物学の研究の効率とアクセシビリティが向上します.
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