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Bayesian Models of Cognition [PDF]

, 2001
For over 200 years, philosophers and mathematicians have be en using probability theory to describe human cognition. While the theory of prob abilities was first developed as a means of analyzing games of chance, it quickly took on a larger and deeper significance as a formal account of how rational agents should reason in situations of uncertainty ...
Griffiths, Thomas L., Kemp, Charles, Tenenbaum, Joshua B.   +2 more
openaire   +1 more source

Bayesian population receptive field modelling [PDF]

NeuroImage, 2018
We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping.
Zeidman, Peter, Silson, Edward Harry, Schwarzkopf, Dietrich Samuel, Baker, Chris Ian, Penny, Will D.   +4 more
openaire   +6 more sources

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Imprecise Bayesian Networks as Causal Models

Information, 2018
This article considers the extent to which Bayesian networks with imprecise probabilities, which are used in statistics and computer science for predictive purposes, can be used to represent causal structure. It is argued that the adequacy conditions for
David Kinney
doaj   +1 more source

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

Dynamic Bayesian Networks for Evaluation of Granger Causal Relationships in Climate Reanalyses

Journal of Advances in Modeling Earth Systems, 2021
We apply a Bayesian structure learning approach to study interactions between global climate modes, so illustrating its use as a framework for developing process‐based diagnostics with which to evaluate climate models.
Dylan Harries, Terence J. O'Kane
doaj   +1 more source

Lévy Walk in Swarm Models Based on Bayesian and Inverse Bayesian Inference

Computational and Structural Biotechnology Journal, 2021
While swarming behavior is regarded as a critical phenomenon in phase transition and frequently shows the properties of a critical state such as Lévy walk, a general mechanism to explain the critical property in swarming behavior has not yet been found ...
Yukio-Pegio Gunji, Takeshi Kawai, Hisashi Murakami, Takenori Tomaru, Mai Minoura, Shuji Shinohara   +5 more
doaj   +1 more source

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

Interpretable artificial neural networks incorporating Bayesian alphabet models for genome-wide prediction and association studies

G3: Genes, Genomes, Genetics, 2021
In conventional linear models for whole-genome prediction and genome-wide association studies (GWAS), it is usually assumed that the relationship between genotypes and phenotypes is linear.
Tianjing Zhao, Rohan Fernando, Hao Cheng
doaj   +1 more source

Bayesian unmasking in linear models [PDF]

Computational Statistics & Data Analysis, 2001
We propose a Bayesian procedure for multiple outlier detection in linear models avoiding the masking problem. Our proposal is illustrated with several examples in which our procedure outperforms other recent methods for multiple outlier detection. The posterior probabilities of each data point being an outlier are estimated by using a new adaptive ...
JUSTEL, Ana, PEÑA , Daniel
openaire   +3 more sources