Results 91 to 100 of about 22,796,869 (307)
Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source
Inference in Nonlinear Differential Equations [PDF]
, 2015 Parameter inference in mechanistic models of coupled differential equations is a challenging problem. We propose a new method using kernel ridge regression in Reproducing Kernel Hilbert Spaces (RKHS). A three-step gradient matching algorithm is developed
Filippone, Maurizio +3 more
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Using mechanistic models for the clinical interpretation of complex genomic variation
Scientific Reports, 2019 The sustained generation of genomic data in the last decade has increased the knowledge on the causal mutations of a large number of diseases, especially for highly penetrant Mendelian diseases, typically caused by a unique or a few genes.
M. Peña-Chilet +6 more
semanticscholar +1 more source
FEBS Letters, EarlyView.Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi +5 more
wiley +1 more source
Universal differential equations as a unifying modeling language for neuroscience
Frontiers in Computational NeuroscienceThe rapid growth of large-scale neuroscience datasets has spurred diverse modeling strategies, ranging from mechanistic models grounded in biophysics, to phenomenological descriptions of neural dynamics, to data-driven deep neural networks (DNNs).
Ahmed El-Gazzar, Marcel van Gerven
doaj +1 more source
Impacts of reopening strategies for COVID-19 epidemic: a modeling study in Piedmont region
BMC Infectious Diseases, 2020 Background Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), the causative agent of the coronavirus disease 19 (COVID-19), is a highly transmittable virus.
Simone Pernice +8 more
doaj +1 more source
The Computable Universe Hypothesis
, 2013 When can a model of a physical system be regarded as computable? We provide the definition of a computable physical model to answer this question. The connection between our definition and Kreisel's notion of a mechanistic theory is discussed, and ...
Szudzik, Matthew P.
core +1 more source
Inferring and validating mechanistic models of neural microcircuits based on spike-train data
Nature Communications, 2018 The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic
J. Ladenbauer +4 more
semanticscholar +1 more source
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Parameter inference in mechanistic models of cellular regulation and signalling pathways using gradient matching [PDF]
, 2012 A challenging problem in systems biology is parameter inference in mechanistic models of signalling pathways. In the present article, we investigate an approach based on gradient matching and nonparametric Bayesian modelling with Gaussian processes.
Cretella, R. +7 more
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