Results 51 to 60 of about 63,287 (274)

Molecular dynamics simulations of positively selected codons in FcγRI reveal novel biochemical binding properties

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, Omar Arias‐Gaguancela, Fiona Gibson, Morgan Grainger, Jodie Score, Amit Nathubhai, Mauricio Cafiero, Lee Richard Machado   +7 more
wiley   +1 more source

Variational Supertrees for Bayesian Phylogenetics

Bulletin of Mathematical Biology
AbstractBayesian phylogenetic inference is powerful but computationally intensive. Researchers may find themselves with two phylogenetic posteriors on overlapping data sets and may wish to approximate a combined result without having to re-run potentially expensive Markov chains on the combined data set.
Michael D. Karcher, Cheng Zhang, Frederic A. Matsen   +2 more
openaire   +3 more sources

A Bayesian Approach to Biological Variation Analysis [PDF]

Clinical Chemistry, 2019
Abstract BACKGROUND Biological variation (BV) data have many applications for diagnosing and monitoring disease. The standard statistical approaches for estimating BV are sensitive to “noisy data” and assume homogeneity of within-participant CV. Prior knowledge about BV is mostly ignored.
Thomas, Røraas, Sverre, Sandberg, Aasne K, Aarsand, Bård, Støve   +3 more
openaire   +2 more sources

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, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

A Bayesian Robust Tensor Ring Decomposition Model with Gaussian-Wishart Prior for Missing Traffic Data Completion

Promet (Zagreb)
The rapid development of Intelligent Transportation Systems (ITS) is often hindered by missing data due to technical or equipment failures, impacting data analysis and application.
Longsheng HUANG, Yu ZHU, Hanzeng SHAO, Yun ZHU, Gaohang YU, Jun WANG   +5 more
doaj   +1 more source

Direction of arrival estimation under Class A modelled noise in shallow water using variational Bayesian inference method

IET Radar, Sonar & Navigation, 2022
The shallow water noise shows obvious impulsive property, which greatly degrades the direction of arrival (DOA) performance due to the conventional design concept based on the Gaussian assumption.
Xiao Feng, Xuebo Zhang, Ruiping Song, Junfeng Wang, Haixin Sun, Hamada Esmaiel   +5 more
doaj   +1 more source

Functional Variational Bayesian Neural Networks

CoRR, 2019
ICLR ...
Shengyang Sun, Guodong Zhang 0006, Jiaxin Shi, Roger B. Grosse   +3 more
openaire   +3 more sources

Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer

Aging and Cancer, EarlyView.
Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss, Alexis C. Wardell, Allison M. Deal, Kirsten A. Nyrop, Allison Ross, Yara G. Abdou, Jeffrey D. Aldrich, Lisa A. Cary, E. Claire Dees, Katherine E. Reeder‐Hayes, Emily M. Ray, Natalia Mitin, Denis Tsygankov   +12 more
wiley   +1 more source

Gradient Regularization as Approximate Variational Inference

Entropy, 2021
We developed Variational Laplace for Bayesian neural networks (BNNs), which exploits a local approximation of the curvature of the likelihood to estimate the ELBO without the need for stochastic sampling of the neural-network weights.
Ali Unlu, Laurence Aitchison
doaj   +1 more source

Variational Bayesian Generative Topographic Mapping

Journal of Mathematical Modelling and Algorithms, 2008
General finite mixture models are powerful tools for the density-based grouping of multivariate i.i.d. data, but they lack data visualization capabilities, which reduces their practical applicability to real-world problems. Generative topographic mapping (GTM) was originally formulated as a constrained mixture of distributions in order to provide ...
Olier Caparroso, Iván, Vellido Alcacena, Alfredo   +1 more
openaire   +5 more sources