AIなら年間100万回の微生物実験が可能(AI could run a million microbial experiments per year)


2023-05-04 ミシガン大学



BacterAIは予備知識なしで微生物の代謝をマッピング BacterAI maps microbial metabolism without prior knowledge

Adam C. Dama,Kevin S. Kim,Danielle M. Leyva,Annamarie P. Lunkes,Noah S. Schmid,Kenan Jijakli & Paul A. Jensen
Nature Microbiology  Published:04 May 2023

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Training artificial intelligence (AI) systems to perform autonomous experiments would vastly increase the throughput of microbiology; however, few microbes have large enough datasets for training such a system. In the present study, we introduce BacterAI, an automated science platform that maps microbial metabolism but requires no prior knowledge. BacterAI learns by converting scientific questions into simple games that it plays with laboratory robots. The agent then distils its findings into logical rules that can be interpreted by human scientists. We use BacterAI to learn the amino acid requirements for two oral streptococci: Streptococcus gordonii and Streptococcus sanguinis. We then show how transfer learning can accelerate BacterAI when investigating new environments or larger media with up to 39 ingredients. Scientific gameplay and BacterAI enable the unbiased, autonomous study of organisms for which no training data exist.