Anter Jacob Marcel, Yakimovich Artur
Center for Advanced Systems Understanding (CASUS), Görlitz, Germany.
Helmholtz-Zentrum Dresden-Rossendorf e. V. (HZDR), Dresden, Germany.
Methods Mol Biol. 2025;2890:291-333. doi: 10.1007/978-1-0716-4326-6_15.
Despite unprecedented achievements, the domain-specific application of artificial intelligence (AI) in the realm of infection biology was still in its infancy just a couple of years ago. This is largely attributable to the proneness of the infection biology community to shirk quantitative techniques. The so-called "sorting machine" paradigm was prevailing at that time, meaning that AI applications were primarily confined to the automation of tedious laboratory tasks. However, fueled by the severe acute respiratory syndrome coronavirus 2 pandemic, AI-driven applications in infection biology made giant leaps beyond mere automation. Instead, increasingly sophisticated tasks were successfully tackled, thereby ushering in the transition to the "Swiss army knife" paradigm. Incentivized by the urgent need to subdue a raging pandemic, AI achieved maturity in infection biology and became a versatile tool. In this chapter, the maturation of AI in the field of infection biology from the "sorting machine" paradigm to the "Swiss army knife" paradigm is outlined. Successful applications are illustrated for the three data modalities in the domain, that is, images, molecular data, and language data, with a particular emphasis on disentangling host-pathogen interactions. Along the way, fundamental terminology mentioned in the same breath as AI is elaborated on, and relationships between the subfields these terms represent are established. Notably, in order to dispel the fears of infection biologists toward quantitative methodologies and lower the initial hurdle, this chapter features a hands-on guide on software installation, virtual environment setup, data preparation, and utilization of pretrained models at its very end.
尽管取得了前所未有的成就，但就在几年前，人工智能（AI）在感染生物学领域的特定应用仍处于起步阶段。这在很大程度上归因于感染生物学界倾向于回避定量技术。当时所谓的“分拣机”范式盛行，这意味着人工智能应用主要局限于繁琐实验室任务的自动化。然而，在严重急性呼吸综合征冠状病毒2大流行的推动下，感染生物学中由人工智能驱动的应用取得了巨大飞跃，不再仅仅是自动化。相反，越来越复杂的任务得到了成功解决，从而迎来了向“瑞士军刀”范式的转变。在制服肆虐大流行的迫切需求的激励下，人工智能在感染生物学中走向成熟，成为一种多功能工具。在本章中，概述了人工智能在感染生物学领域从“分拣机”范式到“瑞士军刀”范式的成熟过程。针对该领域的三种数据模式，即图像、分子数据和语言数据，展示了成功的应用案例，特别强调了解析宿主-病原体相互作用。在此过程中，详细阐述了与人工智能一同提及的基本术语，并建立了这些术语所代表的子领域之间的关系。值得注意的是，为了消除感染生物学家对定量方法的恐惧并降低入门门槛，本章在结尾提供了一份关于软件安装、虚拟环境设置、数据准备以及预训练模型使用的实践指南。
