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   Sato, Brian (Ed.)

   As biological science rapidly generates new knowledge and novel approaches to address increasingly complex and integrative questions, biology educators face the challenge of teaching the next generation of biologists and citizens the skills and knowledge to enable them to keep pace with a dynamic field. Fundamentally, biology is the science of living systems. Not surprisingly, systems is a theme that pervades national reports on biology education reform. In this essay, we present systems as a unifying paradigm that provides a conceptual framework for all of biology and a way of thinking that connects and integrates concepts with practices. To translate the systems paradigm into concrete outcomes to support instruction and assessment in the classroom, we introduce the biology systems-thinking (BST) framework, which describes four levels of systems-thinking skills: 1) describing a system’s structure and organization, 2) reasoning about relationships within the system, 3) reasoning about the system as a whole, and 4) analyzing how a system interacts with other systems. We conclude with a series of questions aimed at furthering conversations among biologists, biology education researchers, and biology instructors in the hopes of building support for the systems paradigm. 

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2. Measuring the contributions of Chinese scholars to the research field of systems biology from 2005 to 2013

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   Zou, Yawen; Laubichler, Manfred D. (March 2017, Scientometrics)
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4. The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: putting systems biology to work

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5. Adapting modeling and simulation credibility standards to computational systems biology

   https://doi.org/10.1186/s12967-023-04290-5  

   Tatka, Lillian T.; Smith, Lucian P.; Hellerstein, Joseph L.; Sauro, Herbert M. (July 2023, Journal of Translational Medicine)

   Abstract Computational models are increasingly used in high-impact decision making in science, engineering, and medicine. The National Aeronautics and Space Administration (NASA) uses computational models to perform complex experiments that are otherwise prohibitively expensive or require a microgravity environment. Similarly, the Food and Drug Administration (FDA) and European Medicines Agency (EMA) have began accepting models and simulations as forms of evidence for pharmaceutical and medical device approval. It is crucial that computational models meet a standard of credibility when using them in high-stakes decision making. For this reason, institutes including NASA, the FDA, and the EMA have developed standards to promote and assess the credibility of computational models and simulations. However, due to the breadth of models these institutes assess, these credibility standards are mostly qualitative and avoid making specific recommendations. On the other hand, modeling and simulation in systems biology is a narrower domain and several standards are already in place. As systems biology models increase in complexity and influence, the development of a credibility assessment system is crucial. Here we review existing standards in systems biology, credibility standards in other science, engineering, and medical fields, and propose the development of a credibility standard for systems biology models. 

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