关键词: 遗传学, 生物化学, 多学科交叉, 复杂生命系统, 高通量分析, 系统生物学, 调控网络, 稳健性, 可塑性, 建模

Abstract:

Given the inherent complexity, hierarchical organization, and dynamic nature of living systems, there is no single best strategy for investigation, and priorities shift with the evolution of the life sciences. In the 1990s, two classic stories, The Salvation of Doug and The Demise of Bill, used automobiles as analogies and satire to contrast two research strategies: dismantling components to uncover underlying mechanisms, or applying functional perturbations to identify critical elements. These heuristic parables stimulated broad discussion on the respective strengths and limitations of different research approaches and continue to be widely used in teaching today. The life sciences have since entered an era integrating high-throughput, high-resolution, and multidimensional approaches, where single-path strategies can no longer provide deep, systematic insights into complex biological processes. We view the intrinsic features of living systems, such as modular organization, regulatory networks, nonlinear responses, and adaptive compensation, as factors that make any single approach likely to capture only local, static aspects, thereby hindering the reconstruction of systems-level, dynamic properties. Against this backdrop, we present a modern continuation of the two parables, reimagined in a contemporary setting and featuring two protagonists with symbolic Chinese names, “Zhiwei” (meaning “decoding hidden mechanisms”) and “Sixu” (“reasoning through order”), who personify biochemical and genetic mindsets. In our narrative, the two protagonists transition from working independently to collaborating, integrating high-throughput experimentation, systems-level analysis, and computational modeling to uncover structural and operational principles underlying complex systems. We believe this retelling reflects the growing emphasis on systems-level and dynamic perspectives in biology, highlighting the value of methodological integration and innovation. We hope it will serve as a valuable resource for teaching in genetics and related disciplines, while fostering reflection on the enduring relevance of genetic reasoning in contemporary research.

Key words: genetics, biochemistry, interdisciplinary research, complex biological systems, high-throughput analysis, systems biology, regulatory networks, robustness, plasticity, modeling