Results 91 to 100 of about 29,659,346 (383)
Pygpc: A sensitivity and uncertainty analysis toolbox for Python
SoftwareX, 2020 We present a novel Python package for the uncertainty and sensitivity analysis of computational models. The mathematical background is based on the non-intrusive generalized polynomial chaos method allowing one to treat the investigated models as black ...
Konstantin Weise +4 more
doaj +1 more source
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
FEBS Letters, EarlyView.Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan +2 more
wiley +1 more source
Probabilistic Sensitivity Analysis: Be a Bayesian [PDF]
Value in Health, 2009 To give guidance in defining probability distributions for model inputs in probabilistic sensitivity analysis (PSA) from a full Bayesian perspective.A common approach to defining probability distributions for model inputs in PSA on the basis of input-related data is to use the likelihood of the data on an appropriate scale as the foundation for the ...
Hendriek C. Boshuizen, Pieter van Baal
openaire +2 more sources
Aβ42 promotes the aggregation of α‐synuclein splice isoforms via heterogeneous nucleation
FEBS Letters, EarlyView.The aggregation of amyloid‐β (Aβ) and α‐synuclein (αSyn) is associated with Alzheimer's and Parkinson's diseases. This study reveals that Aβ aggregates serve as potent nucleation sites for the aggregation of αSyn and its splice isoforms, shedding light on the intricate interplay between these two pathogenic proteins.
Alexander Röntgen +2 more
wiley +1 more source
ICAN sensitivity analysis [PDF]
A computer program called Integrated Composite Analyzer (ICAN) was used to predict the properties of high-temperature polymer matrix composites. ICAN is a collection of NASA Lewis Research Center-developed computer codes designed to carry out analysis of
Bowles, Kenneth J. +2 more
core +1 more source
ERBIN limits epithelial cell plasticity via suppression of TGF‐β signaling
FEBS Letters, EarlyView.In breast and lung cancer patients, low ERBIN expression correlates with poor clinical outcomes. Here, we show that ERBIN inhibits TGF‐β‐induced epithelial‐to‐mesenchymal transition in NMuMG breast and A549 lung adenocarcinoma cell lines. ERBIN suppresses TGF‐β/SMAD signaling and reduces TGF‐β‐induced ERK phosphorylation.
Chao Li +3 more
wiley +1 more source
FEBS Letters, EarlyView.In this work, we reveal how different enzyme binding configurations influence the fluorescence decay of NAD(P)H in live cells using time‐resolved anisotropy imaging and fluorescence lifetime imaging microscopy (FLIM). Mathematical modelling shows that the redox states of the NAD and NADP pools govern these configurations, shaping their fluorescence ...
Thomas S. Blacker +8 more
wiley +1 more source
Clinical Epidemiology, 2013 Chenglin Ye,1,2 Gina Browne,1,3 Joseph Beyene,1 Lehana Thabane1,2 1Department of Clinical Epidemiology and Biostatistics, McMaster University, 2Biostatistcs Unit, St Joseph's Healthcare Hamilton, 3School of Nursing, McMaster University, Hamilton, ON,
Ye C, Browne G, Beyene J, Thabane L
doaj
Sensitivity Analysis of RFML Applications
IEEE AccessPerformance of radio frequency machine learning (RFML) models for classification tasks such as specific emitter identification (SEI) and automatic modulation classification (AMC) have improved greatly since their introduction, especially when measured ...
Braeden P. Muller +2 more
doaj +1 more source