S
Sara Green
Researcher at University of Copenhagen
Publications - 44
Citations - 755
Sara Green is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Systems biology & Philosophy of biology. The author has an hindex of 15, co-authored 43 publications receiving 560 citations. Previous affiliations of Sara Green include University of Pittsburgh & Aarhus University.
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The search for organizing principles as a cure against reductionism in systems medicine.
TL;DR: The prospects for use of an old regulative ideal from systems theory to describe the organization of cellular systems ‘in general’ are investigated by identifying key concepts, challenges and strategies to pursue the search for organizing principles.
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Biology meets physics: Reductionism and multi-scale modeling of morphogenesis
Sara Green,Robert W. Batterman +1 more
TL;DR: Controlling the scale-dependency of physical and biological behaviors that forces researchers to combine different models relying on different scale-specific mathematical strategies and boundary conditions presents a challenge to reductive explanations in both physics and biology.
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Network analyses in systems biology: new strategies for dealing with biological complexity
TL;DR: It is shown how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological complexity.
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Is defining life pointless? Operational definitions at the frontiers of biology
Leonardo Bich,Sara Green +1 more
TL;DR: It is argued that critically rethinking the nature and uses of definitions can provide new insights into the epistemic roles of definitions of life for different research practices, and the pragmatic utility of what are called operational definitions that serve as theoretical and epistemic tools in scientific practice.
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Revisiting generality in biology: systems biology and the quest for design principles
TL;DR: In this paper, the authors argue that design principles increase our understanding of living systems by relating specific models to general types, and characterize the basis for general principles through generic abstraction and reasoning about possibility spaces.