Recent developments in AI have reinvigorated pursuits to advance the (life) sciences using AI techniques, thereby creating a renewed opportunity to bridge different fields and find synergies. Headlines for AI and the life sciences have been dominated by data-driven techniques, for instance, to solve protein folding with next to no expert knowledge. In contrast to this, we argue for the necessity of a formal representation of expert knowledge - either to develop explicit scientific theories or to compensate for the lack of data. Specifically, we argue that the fields of knowledge representation (KR) and systems biology (SysBio) exhibit important overlaps that have been largely ignored so far. This, in turn, means that relevant scientific questions are ready to be answered using the right domain knowledge (SysBio), encoded in the right way (SysBio/KR), and by combining it with modern automated reasoning tools (KR). Hence, the formal representation of domain knowledge is a natural meeting place for SysBio and KR. On the one hand, we argue that such an interdisciplinary approach will advance the field SysBio by exposing it to industrial-grade reasoning tools and thereby allowing novel scientific questions to be tackled. On the other hand, we see ample opportunities to move the state-of-the-art in KR by tailoring KR methods to the field of SysBio, which comes with challenging problem characteristics, e.g. scale, partial knowledge, noise, or sub-symbolic data. We stipulate that this proposed interdisciplinary research is necessary to attain a prominent long-term goal in the health sciences: precision medicine.

翻译：人工智能的最新进展重新激发了利用AI技术推动（生命）科学发展的追求，从而创造了弥合不同领域并寻求协同效应的新机遇。AI与生命科学的头条新闻一直被数据驱动技术主导，例如在几乎无需专家知识的情况下解决蛋白质折叠问题。与此相反，我们主张必须对专家知识进行形式化表示——无论是为了发展明确的科学理论，还是为了弥补数据不足。具体而言，我们认为知识表示（KR）与系统生物学（SysBio）这两个领域存在重要但迄今被忽视的重叠。这意味着相关的科学问题已准备好通过正确的领域知识（SysBio）、以正确的编码方式（SysBio/KR）并结合现代自动推理工具（KR）来解答。因此，领域知识的形式化表示自然成为SysBio与KR的融合点。一方面，我们认为这种跨学科方法将使SysBio领域接触到工业级推理工具，从而推动该领域发展并解决新的科学问题。另一方面，我们看到通过将KR方法适配至具有挑战性问题特征（如规模、部分知识、噪声或亚符号数据）的SysBio领域，将为KR前沿研究带来大量发展机遇。我们主张，这种跨学科研究对于实现健康科学领域的重要长期目标——精准医学——具有不可或缺的意义。