16 papers · ranked by Valyu relevance
Jingmeng Cui, Dieta Wagenmakers, G. Sander van Doorn, Fred Hasselman + 1 more
Formal theories translate verbal theories into a mathematical representation, such as a coupled differential equation or other dynamical systems, intending to strengthen the deductive power of (clinical) theories and to formulate testable and novel hypotheses. Work in clinical formal theories mainly relies on…
Gemma Massonis, Alejandro F. Villaverde, Julio R. Banga, Marc R Birtwistle
'Marc R Birtwistle'] Mechanistic dynamical models allow us to study the behavior of complex biological systems. They can provide an objective and quantitative understanding that would be difficult to achieve through other means. However, the systematic development of these models is a non-trivial exercise and an open…
Gao Huang
This perspective article delves into the transformative realm of dynamic neural networks, which is reshaping AI with adaptable structures and improved efficiency, bridging the gap between artificial and human intelligence.
Ana Paredes-Vázquez, Eva Balsa-Canto, Julio R. Banga, Attila Csikász-Nagy
Microbial communities, complex ecological networks crucial for human and planetary health, remain poorly understood in terms of the quantitative principles governing their composition, assembly, and function. Dynamic modeling using ordinary differential equations (ODEs) is a powerful framework for understanding and…
Lukas Schumacher, Paul-Christian Bürkner, Andreas Voss, Ullrich Köthe + 1 more
Mathematical models of cognition are often memoryless and ignore potential fluctuations of their parameters. However, human cognition is inherently dynamic. Thus, we propose to augment mechanistic cognitive models with a temporal dimension and estimate the resulting dynamics from a superstatistics perspective. Such a…
Kamaryn T. Tanner, Ruth H. Keogh, Carol A. C. Coupland, Julia Hippisley-Cox + 1 more
'Julia Hippisley-Cox' 'Karla Diaz-Ordaz'] Background Over time, the performance of clinical prediction models may deteriorate due to changes in clinical management, data quality, disease risk and/or patient mix. Such prediction models must be updated in order to remain useful. In this study, we investigate dynamic…
Hetian Su, Nan Hao
Cellular aging is a multifaceted complex process. Many genes and factors have been identified that regulate cellular aging. However, how these genes and factors interact with one another and how these interactions drive the aging processes in single cells remain largely unclear. Recently, computational systems biology…
Jesse Wheeler, AnnaElaine Rosengart, Zhuoxun Jiang, Kevin Tan + 3 more
'Noah Treutle' 'Edward L. Ionides' 'Tom Britton'] Public health decisions must be made about when and how to implement interventions to control an infectious disease epidemic. These decisions should be informed by data on the epidemic as well as current understanding about the transmission dynamics. Such decisions can…
Mengman Wei, Qian Peng
Human behavioral and mental health outcomes arise from interactions among genetic, environmental, and neurobiological systems. Existing frameworks often model these components jointly, but many treat variables independently or use static representations. This limits their ability to capture system-level dynamics and…
Nithinan Mahawan, Thanapoom Rattananupong, Puchong Sri-Uam, Wiroj Jiamjarasrangsi + 1 more
'Wiroj Jiamjarasrangsi' 'Martial L. Ndeffo-Mbah'] This study examined the ability of the following five dynamic models for predicting pulmonary tuberculosis (PTB) incidence in a prison setting: the Wells-Riley equation, two Rudnick & Milton-proposed models based on air changes per hour and liters per second per person…
Karl J. Friston, Guillaume Flandin, Adeel Razi
This technical report describes the dynamic causal modelling of mitigated epidemiological outcomes during the COVID-9 coronavirus outbreak in 2020. Dynamic causal modelling is a form of complex system modelling, which uses ‘real world’ timeseries to estimate the parameters of an underlying state space model using…
Xiaojun Wu, MeiLu McDermott, Adam L MacLean, Mark Alber
Biological systems exhibit complex dynamics that differential equations can often adeptly represent. Ordinary differential equation models are widespread; until recently their construction has required extensive prior knowledge of the system. Machine learning methods offer alternative means of model construction…
Erik Blystad Solbu, Bert van der Veen, Ivar Herfindal, Knut Anders Hovstad
'Knut Anders Hovstad'] Title: Abstract Understanding the mechanisms of ecological community dynamics and how they could be affected by environmental changes is important. Population dynamic models have well known ecological parameters that describe key characteristics of species such as the effect of environmental…
Girdhari Rijal, In-Woo Park, Xin Zhao, Bruce P. Lee
Fabricating breast tumor models that mimic the natural breast tissue-like microenvironment (normal or cancerous) both physically and bio-metabolically, despite extended research, is still a challenge. A native-mimicking breast tumor model is the demand since complex biophysiological mechanisms in the native breast…
Malgorzata Kardynska, Daria Kogut, Marcin Pacholczyk, Jaroslaw Smieja
'Jaroslaw Smieja'] Regulatory networks structure and signaling pathways dynamics are uncovered in time- and resource consuming experimental work. However, it is increasingly supported by modeling, analytical and computational techniques as well as discrete mathematics and artificial intelligence applied to to extract…
Chen M Chen, Rosemary Yu
Plasticity is the potential for cells or cell populations to change their phenotypes and behaviors in response to internal or external cues. Plasticity is fundamental to many complex biological processes, yet to date there remains a lack of mathematical models that can elucidate and predict molecular behaviors in a…