Zhao Weijie
Natl Sci Rev. 2025 Apr 11;12(6):nwaf142. doi: 10.1093/nsr/nwaf142. eCollection 2025 Jun.
In the 2021 paper [1] that introduced the groundbreaking protein structure prediction artificial intelligent (AI) tool AlphaFold2 to the world, Martin Steinegger was the only author who was not affiliated with DeepMind. At the forefront of the ongoing revolution in biological research methodology, Steinegger has pioneered the development of a series of powerful bioinformatics tools, including MMseqs2 [2] for protein and nucleotide sequence searching and clustering, Foldseek [3] for protein structure searches at the scale of the AlphaFold database and ColabFold [4] for rapid and accessible protein structure prediction. After earning his PhD in Computer Science with summa cum laude honors from the Technical University of Munich in 2018, based on his doctoral research that was conducted at the Max Planck Institute for Multidisciplinary Sciences, Steinegger completed a postdoctoral fellowship at Johns Hopkins University. He is now an associate professor in the Biology Department at Seoul National University in the Republic of Korea, with a joint appointment to the Interdisciplinary Program in Bioinformatics. His group develops user-friendly, open-source methods for protein sequence and structure analysis. In recognition of his scientific contributions, Steinegger received the prestigious 2024 Overton Award from the International Society for Computational Biology. In this interview with NSR, Steinegger shares his unconventional academic journey, his experiences in developing these transformative tools and his insights into the rapidly evolving field of computational biology.
在2021年向世界介绍开创性蛋白质结构预测人工智能(AI)工具AlphaFold2的论文[1]中,马丁·施泰内格是唯一一位与DeepMind没有关联的作者。处于生物研究方法学这场正在进行的革命前沿,施泰内格率先开发了一系列强大的生物信息学工具,包括用于蛋白质和核苷酸序列搜索与聚类的MMseqs2[2]、用于在AlphaFold数据库规模上进行蛋白质结构搜索的Foldseek[3]以及用于快速且便捷的蛋白质结构预测的ColabFold[4]。2018年,施泰内格以优异成绩从慕尼黑工业大学获得计算机科学博士学位,其博士研究是在马克斯·普朗克多学科科学研究所进行的,之后他在约翰·霍普金斯大学完成了博士后研究。他现在是大韩民国首尔国立大学生物系的副教授,并兼任生物信息学跨学科项目的职位。他的团队开发用于蛋白质序列和结构分析的用户友好型开源方法。鉴于他的科学贡献,施泰内格获得了国际计算生物学学会颁发的享有盛誉的2024年奥弗顿奖。在接受《国家科学评论》(NSR)的这次采访中,施泰内格分享了他非传统的学术历程、开发这些变革性工具的经历以及他对快速发展的计算生物学领域的见解。