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AI図鑑

AlphaFold

アミノ酸配列からタンパク質の立体構造を予測する

Google DeepMind モデル オープンソース

本ページの本文は英語で提供されています。タイトルと導入は日本語化されています。

これは何か

AlphaFold is Google DeepMind’s protein-structure prediction system; the second version (AlphaFold2) was announced at the CASP14 assessment in November 2020 with accuracy close to experimental methods. It takes a protein’s amino-acid sequence and a multiple sequence alignment as input, uses an attention-based Evoformer module to model relationships between residues, and outputs three-dimensional coordinates. DeepMind later open-sourced the code and model weights and, with EMBL-EBI, built the AlphaFold Protein Structure Database, which holds hundreds of millions of predicted structures.

なぜ覚えておく価値があるか

It pushed protein-structure prediction to near-experimental accuracy, released the code and weights, and built a large structure database, becoming one of the most cited cases of AI applied to scientific research.

主な仕様

Open source
Yes (code and model weights released)
Database scale
AlphaFold DB holds hundreds of millions of predicted structures
Input
Amino-acid sequence and multiple sequence alignment
Released
2020-11 (CASP14)

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