Results 61 to 70 of about 862,083 (298)

A Generalization of Bayesian Inference

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1968
Summary Procedures of statistical inference are described which generalize Bayesian inference in specific ways. Probability is used in such a way that in general only bounds may be placed on the probabilities of given events, and probability systems of this kind are suggested both for sample information and for prior information.
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

Granger causality vs. dynamic Bayesian network inference: a comparative study [PDF]

, 2009
Background In computational biology, one often faces the problem of deriving the causal relationship among different elements such as genes, proteins, metabolites, neurons and so on, based upon multi-dimensional temporal data.
Denby Katherine J, Denby, Katherine J., Cunlu CunluZou, Katherine J Denby, Feng, Jianfeng, Jianfeng Feng, Zou Cunlu, Zou, Cunlu, Feng Jianfeng   +8 more
core   +1 more source

Structural and biochemical insights into the thermostable esterase Ta0887 from Thermoplasma acidophilum

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, Miriam Livier Llamas‐García, Gabriela M. Montero‐Morán, Leticia Santos, Samuel Lara‐González   +4 more
wiley   +1 more source

Evaluation of a Bayesian inference network for ligand-based virtual screening

Journal of Cheminformatics, 2009
Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query.
Chen Beining, Mueller Christoph, Willett Peter   +2 more
doaj   +1 more source

A Continuation Method in Bayesian Inference

SIAM/ASA Journal on Uncertainty Quantification, 2023
We present a continuation method that entails generating a sequence of transition probability density functions from the prior to the posterior in the context of Bayesian inference for parameter estimation problems. The characterization of transition distributions, by tempering the likelihood function, results in a homogeneous nonlinear partial integro-
openaire   +2 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

A Bayesian Account of Psychopathy: A Model of Lacks Remorse and Self-Aggrandizing [PDF]

Computational Psychiatry, 2018
This article proposes a formal model that integrates cognitive and psychodynamic psychotherapeutic models of psychopathy to show how two major psychopathic traits called lacks remorse and self-aggrandizing can be understood as a form of abnormal Bayesian
Aaron Prosser, Karl J. Friston, Nathan Bakker, Thomas Parr   +3 more
doaj   +3 more sources

The Size-Weight Illusion is not anti-Bayesian after all: a unifying Bayesian account [PDF]

PeerJ, 2016
When we lift two differently-sized but equally-weighted objects, we expect the larger to be heavier, but the smaller feels heavier. However, traditional Bayesian approaches with “larger is heavier” priors predict the smaller object should feel lighter ...
Megan A.K. Peters, Wei Ji Ma, Ladan Shams   +2 more
doaj   +2 more sources

Advanced Approach for Distributions Parameters Learning in Bayesian Networks with Gaussian Mixture Models and Discriminative Models

Mathematics, 2023
Bayesian networks are a powerful tool for modelling multivariate random variables. However, when applied in practice, for example, for industrial projects, problems arise because the existing learning and inference algorithms are not adapted to real data.
Irina Deeva, Anna Bubnova, Anna V. Kalyuzhnaya   +2 more
doaj   +1 more source