Results 51 to 60 of about 7,371,142 (245)
Dynamic Railway Derailment Risk Analysis with Text-Data-Based Bayesian Network
Applied Sciences, 2021 In recent years, transportation system safety analysis has become increasingly challenging and highly demanding. Unstructured data contain sufficient information from which inherent interactions can be extracted.
Liu Yang +3 more
doaj +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
FEBS Open Bio, EarlyView.In this study, a novel esterase from the thermoacidophilic archaeon Thermoplasma acidophilum was biochemically and structurally characterized. Our results demonstrate that Ta0887 is a highly thermostable esterase that preferentially hydrolyzes p‐nitrophenyl hexanoate and possesses an α‐helical cap domain that likely contributes to its substrate ...
Alejandro Delgado‐Rey +4 more
wiley +1 more source
Bayesian dynamic modeling and monitoring of network flows [PDF]
Network Science, 2019 AbstractIn the context of a motivating study of dynamic network flow data on a large-scale e-commerce website, we develop Bayesian models for online/sequential analysis for monitoring and adapting to changes reflected in node–node traffic. For large-scale networks, we customize core Bayesian time series analysis methods using dynamic generalized linear
Xi Chen 0049, David Banks, Mike West
openaire +3 more sources
Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes [PDF]
, 2010 <b>Method:</b> Dynamic Bayesian networks (DBNs) have been applied widely to reconstruct the structure of regulatory processes from time series data, and they have established themselves as a standard modelling tool in computational systems ...
Husmeier, D. +5 more
core +1 more source
Probabilistic Prognosis with Dynamic Bayesian Networks
International Journal of Prognostics and Health Management, 2015 This paper proposes a methodology for probabilistic prognosis of a system using a dynamic Bayesian network (DBN). Dynamic Bayesian networks are suitable for probabilistic prognosis because of their ability to integrate information in a variety of formats
Gregory Bartram, Sankaran Mahadevan
doaj +1 more source
Global Rather Than Vertical‐Selective Saccadic Abnormalities in Progressive Supranuclear Palsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To test whether vertical saccades are preferentially affected in Progressive Supranuclear Palsy (PSP). Methods PSP patients (n = 24) were compared to age‐matched controls (n = 94) and two degenerative groups (Alzheimer's disease, n = 20; Lewy body disease, n = 50).
Duy Duan Nguyen +6 more
wiley +1 more source
Efficient utility-based clustering over high dimensional partition spaces [PDF]
, 2009 Because of the huge number of partitions of even a moderately sized dataset, even when Bayes factors have a closed form, in model-based clustering a comprehensive search for the highest scoring (MAP) partition is usually impossible.
Smith, JQ +9 more
core +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Dependency Parsing with Dynamic Bayesian Network
CoRR, 2007 6 ...
Virginia Savova, Leonid Peshkin
openaire +3 more sources