Results 71 to 80 of about 7,255,480 (346)
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source
Inversion of Bayesian networks
International Journal of Approximate ReasoningVariational autoencoders and Helmholtz machines use a recognition network (encoder) to approximate the posterior distribution of a generative model (decoder). In this paper we study the necessary and sufficient properties of a recognition network so that it can model the true posterior distribution exactly.
Jesse van Oostrum +2 more
openaire +3 more sources
FEBS Open Bio, EarlyView.Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young +7 more
wiley +1 more source
Bayesian networks to explain the effect of label information on product perception
, 2011 Interdisciplinary approaches in food research require new methods in data analysis that are able to deal with complexity and facilitate the communication among model users. Four parallel full factorial within-subject designs were performed to examine the
Kole, A.P.W. +4 more
core +1 more source
A Causal Bayesian Networks Viewpoint on Fairness [PDF]
Privacy and Identity Management, 2018 We offer a graphical interpretation of unfairness in a dataset as the presence of an unfair causal effect of the sensitive attribute in the causal Bayesian network representing the data-generation mechanism.
S. Chiappa, William S. Isaac
semanticscholar +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
Prognostic Modelling with Dynamic Bayesian Networks [PDF]
, 2009 In this paper, we review the application of dynamic Bayesian networks to prognostic modelling. An example is provided for illustration. With this example, we show how the equipment’s reliability decays over time in the situation where repair is not ...
McNaught, Ken R., Zagorecki, A.
core
Layer wise Scaled Gaussian Priors for Markov Chain Monte Carlo Sampled deep Bayesian neural networks
Frontiers in Artificial IntelligencePrevious work has demonstrated that initialization is very important for both fitting a neural network by gradient descent methods, as well as for Variational inference of Bayesian neural networks.
Devesh Jawla, John Kelleher
doaj +1 more source
Redai dili, 2023 Owing to the effects of rural tourism and urbanization, the frequent participation of external market activities in traditional villages has increased the sensitivity and fragility of villages.
Chu Jinlong +3 more
doaj +1 more source
Journal of Open Source SoftwareThe R package abn is a comprehensive tool for Bayesian Network (BN) analysis, a form of probabilistic graphical model. BNs are a type of statistical model that leverages the principles of Bayesian statistics and graph theory to provide a framework for representing complex multivariate data.
Delucchi, Matteo +3 more
openaire +2 more sources