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Aug 2026
A. Marcum JamesCorresponding author
The complexity of living systems, ranging from cellular networks to organisms to ecosystems, poses a significant challenge to the progress of contemporary biology and biomedicine. Living organisms are complex adaptive systems that are characterized by nonlinear interactions, causal-dynamic feedback loops, and context-dependent behaviors that give rise to emergent properties that are not completely explainable or predictable from the properties of the individual components alone. Investigating and understanding systemic complexity is therefore essential for advancing biology and biomedicine. Recently, artificial intelligence (AI) has been developed for analyzing large-scale, high-dimensional datasets generated by experimental and clinical research. AI enables the identification of correlations, causal patterns, and predictive relationships, which are difficult to discern using traditional analytical approaches. However, without an overarching framework, it risks being applied in fragmented or purely data-driven ways. Systems thinking (ST) provides a framework by emphasizing holism, interconnections, and dynamic behaviors across multiple organizational scales. By integrating ST and AI, researchers can creatively and effectively investigate living systems, ensuring that computational insights are meaningful and contextually grounded. An integrated ST–AI approach is proposed as a guiding framework for twenty-first century biology and biomedicine.
Oct 2024
Frais TonyCorresponding author
Both the human body and the natural world are governed by multiple complex systems. These systems have feedback loops which is a process in which the outputs of a system are circled back and used as inputs. Where there are multiple systems, there is always the potential for a catastrophic system failure. If a system fails in the human body, this can lead to a number of life-threatening and debilitating diseases such as cancer. Diseases such as cancer is in effect, the result of a catastrophic system failure. There are cancer cases in which the root cause of the disease is unknown. System failure in the human reproductive system can lead to congenital birth defects. In cases of a system failure leading to congenital birth defects, some of the causal factors are known but in 65% of these cases, the reasons for this reproductive system failure are unexplained. There are neurological diseases such as Parkinson’s, multiple sclerosis and Alzheimer’s where again, the root causes are unknown. Then there are a number of infectious diseases where the root cause is unknown. The initial causative factors for most of these human diseases are well known. What has yet to be fully understood is the primary root cause that triggers and underpins these system failures in the first place. Nature also has devastating system failures such as in earthquakes and hurricanes. Humans and nature are a close partnership and nature can influence human health. Nature’s systems are deeply interconnected and often exhibit complex behaviours due to positive and negative feedback loops present in both nature and human body systems. Using systems methodology and systems thinking and philosophical insights, the objective is to try to ascertain the answer as to why there are these unknown root causes of diseases; questions that presently, science alone cannot explain. It will be argued that as man and nature are as one, the answers as to why human body systems fail leading to disease may lie not in science but in nature.
Aug 2018 DOI 10.14302/issn.2689-4602.jes-18-2229
Mikhailovsky GeorgeCorresponding author
Global Mind Share, Norfolk, VA, United States
A historical and conceptual review traces how evolutionary theory has expanded from classical selection to modern syntheses incorporating development, epigenetics, and systems thinking. Implications for research and science communication are discussed.