環境ゲノムと機械学習の融合による未知代謝機能の解明と環境工学イノベーションの創出

我们采用了一种基于机器学习的方法，该方法利用了芳香化合物降解的两个基本生物学特征：激活和组织。这位研究员和东道主成功地确定了涉及废水处理过程中复杂芳香族化合物的利用和转化的新的代谢途径和生物。进一步的进化分析表明，塑料工业废水流中有多少是同时进化的。预计研究结果将对微生物学和工程界产生重大影响，不久将提交发表。

We employed a machine learning-based approach that utilizes two foundational biological features of aromatic compound degradation: activation and organization. The fellow and host successfully identified novel metabolic pathways and organisms involved in utilization and conversion of complex aromatics compounds in wastewater treatment processes. Further evolutionary analyses showed how many contemporarily evolved in plastics industry wastewater streams. The results are expected to bring high impact to the microbiology and engineering communities and will be submitted for publication soon.