Rethinking the pragmatic systems biology and systems-theoretical biology divide: Toward a complexity-inspired epistemology of systems biomedicine

• Published in: Medical hypotheses 2019-10, Vol.131, p.109316-109316, Article 109316
• Main Author: Kesić, Srdjan
• Format: Article
• Language: English
• Subjects: Complex biological systems; Complexity; Computer Simulation; Cybernetics; Epistemology of complexity; Forecasting; Humans; Knowledge; Models, Theoretical; Philosophy; Second-order cybernetics; Systems Analysis; Systems biology; Systems Biology - classification; Systems Biology - methods
• ISSN: 0306-9877; 1532-2777
• DOI: 10.1016/j.mehy.2019.109316

This paper examines some methodological and epistemological issues underlying the ongoing “artificial” divide between pragmatic-systems biology and systems-theoretical biology. The pragmatic systems view of biology has encountered problems and constraints on its explanatory power because pragmatic systems biologists still tend to view systems as mere collections of parts, not as “emergent realities” produced by adaptive interactions between the constituting components. As such, they are incapable of characterizing the higher-level biological phenomena adequately. The attempts of systems-theoretical biologists to explain these “emergent realities” using mathematics also fail to produce satisfactory results. Given the increasing strategic importance of systems biology, both from theoretical and research perspectives, we suggest that additional epistemological and methodological insights into the possibility of further integration between traditional experimental studies and complex modeling are required. This integration will help to improve the currently underdeveloped pragmatic-systems biology and system-theoretical biology. The “epistemology of complexity,” I contend, acts as a glue that connects and integrates different and sometimes opposing viewpoints, perspectives, streams, and practices, thus maintaining intellectual and research coherence of systems research of life. It allows scientists to shift the focus from traditional experimental research to integrated, modeling-based holistic practices capable of providing a comprehensive knowledge of organizing principles of living systems. It also opens the possibility of the development of new practical and theoretical foundations of systems biology to build a better understanding of complex organismic functions.