Results 41 to 50 of about 112,632 (333)

Multi‐Tissue Genetic Regulation of RNA Editing in Pigs

Advanced Science, EarlyView.
This study presents the first multi‐tissue map of RNA editing and its genetic regulation in pigs. By integrating RNA editing profiles, edQTL mapping, GWAS, and cross‐species comparisons, this work establishes RNA editing as a distinct regulatory layer linking genetic variation to complex traits, highlighting its functional and evolutionary significance.
Xiangchun Pan, Wentao Gong, Xiaodian Cai, Jinyan Teng, Jiali Cai, Haonan Zeng, Wondossen Ayalew, Qingpeng Shen, Zhanming Zhong, Yifei Wang, Wenjing Zhang, Yuhan Tian, Dantong Xu, Yahui Gao, Hongwei Yin, Yuebo Zhang, Jiahui Hou, Tianru Zhou, Jiaqi Li, Lingzhao Fang, Xiaolong Yuan, Zhe Zhang   +21 more
wiley   +1 more source

Markov Chain Monte Carlo Solution of Poisson’s Equation in Axisymmetric Regions

Advanced Electromagnetics, 2019
The advent of the Monte Carlo methods to the field of EM have seen floating random walk, fixed random walk and Exodus methods deployed to solve Poisson’s equation in rectangular coordinate and axisymmetric solution regions.
A. E. Shadare, M. N. O. Sadiku, S. M. Musa   +2 more
doaj   +1 more source

Data Analysis Recipes: Using Markov Chain Monte Carlo [PDF]

, 2017
Markov Chain Monte Carlo (MCMC) methods for sampling probability density functions (combined with abundant computational resources) have transformed the sciences, especially in performing probabilistic inferences, or fitting models to data.
D. Hogg, D. Foreman-Mackey
semanticscholar   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Monte Carlo methods

EPJ Web of Conferences, 2013
Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable.
Bardenet Rémi
doaj   +1 more source

Automated Redistricting Simulation Using Markov Chain Monte Carlo

Journal of Computational And Graphical Statistics, 2020
Legislative redistricting is a critical element of representative democracy. A number of political scientists have used simulation methods to sample redistricting plans under various constraints to assess their impact on partisanship and other aspects of
Benjamin Fifield, Michael J. Higgins, K. Imai, Alexander Tarr   +3 more
semanticscholar   +1 more source

Markov chain Monte Carlo with the Integrated Nested Laplace Approximation [PDF]

Statistics and computing, 2017
The Integrated Nested Laplace Approximation (INLA) has established itself as a widely used method for approximate inference on Bayesian hierarchical models which can be represented as a latent Gaussian model (LGM).
V. Gómez‐Rubio, H. Rue
semanticscholar   +1 more source

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez, Estefania Ascencio, Jose M. Ageitos, Lucia Feijoo, Shan He, Amirreza Daghighi, Gerardo M. Casanola‐Martin, Cristian R. Munteanu, Santiago Rodriguez Yañez, Alejandro Pazos, Harbil Bediaga, Brenda Durand Ordiales, Raquel Esteban, Ana‐Maria Heres, Jorge Curiel Yuste, Lur Epelde, Bakhtiyor Rasulev, Tomas Gonzalez, Sonia Arrasate, Humberto González‐Diaz   +19 more
wiley   +1 more source

Phase space sampling with Markov Chain Monte Carlo methods [PDF]

EPJ Web of Conferences
The efficient exploration of the high-dimensional and multi-modal phase space of scattering events at high-energy particle colliders presents a severe computational challenge. We here discuss the application of Markov Chain Monte Carlo (MCMC) techniques,
La Cagnina Salvatore, Grunwald Cornelius, Janßen Timo, Kröninger Kevin, Schumann Steffen   +4 more
doaj   +1 more source

Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo

bioRxiv, 2016
Motivation In recent years, molecular species delimitation has become a routine approach for quantifying and classifying biodiversity. Barcoding methods are of particular importance in large-scale surveys as they promote fast species discovery and ...
P. Kapli, S. Lutteropp, Jiajie Zhang, Kassian Kobert, P. Pavlidis, A. Stamatakis, T. Flouri   +6 more
semanticscholar   +1 more source