Results 131 to 140 of about 1,651,457 (304)

Agent‐Based Simulations of Lung Tumor Evolution Suggest That Ongoing Cell Competition Drives Realistic Clonal Expansions

Advanced Science, EarlyView.
Computational simulations of tumor evolution are increasingly used to infer the rules underlying cancer growth, with the goal of one day recommending tailored treatments. Here we show that the properties of lung cancer sequencing data are best replicated by a model which assumes that cells compete both to proliferate and survive. ABSTRACT Computational
Helena Coggan, James R. M. Black, Carlos Martínez‐Ruiz, Kristiana Grigoriadis, Jasmin Fisher, Nicholas McGranahan   +5 more
wiley   +1 more source

Bayesian network classifiers in Weka [PDF]

, 2004
Various Bayesian network classifier learning algorithms are implemented in Weka [10].This note provides some user documentation and implementation details.
Remco R. Bouckaert, Bouckaert, Remco R.
core  

Deep‐Learning‐Driven High‐Fidelity In Vivo Hyperspectral Fluorescence Imaging Under Extreme Photon‐Limited Conditions

Advanced Science, EarlyView.
Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Renjian Li, Shutao Wu, Kaixiang Li, Zhenyu An, Yuwen Ben, Guiye LI, Sunil Kumar, James Mcginty, Tawfique Hasan, Songnian Fu, Meng Zhang, LingLing Chen   +11 more
wiley   +1 more source

Predicting the Incident Cases of Emerging Infectious Disease Using a Bayesian Probability Model - China, February 2020. [PDF]

China CDC Wkly, 2020
Zhang Y, Wang X, Li Y, Wu S, Wan M, Su X, Yang S, Lai H, Jia Z, Ma J.   +9 more
europepmc   +1 more source

Time-series Modelling, Stationarity and Bayesian Nonparametric Methods [PDF]

In this paper we introduce two general non-parametric first-order stationary time-series models for which marginal (invariant) and transition distributions are expressed as infinite-dimensional mixtures.
Stephen G. Walker, Juan Carlos Martínez-Ovando   +1 more
core  

Large incomplete sample robustness in Bayesian networks [PDF]

, 2008
Under local DeRobertis (LDR) separation measures, the posterior distances between two densities is the same as between the prior densities. Like Kullback - Leibler separation they also are additive under factorization. These two properties allow us the
Smith, J. Q., Daneshkhah, Alireza
core  

CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model

Advanced Science, EarlyView.
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang, Yuqi Zhang, Xuzhe Zhao, Yansong Tang, Kaichen Dong   +4 more
wiley   +1 more source

What do Bayesian methods offer population forecasters?

, 2010
The Bayesian approach has a number of attractive properties for probabilistic forecasting. In this paper, we apply Bayesian time series models to obtain future population estimates with uncertainty for England and Wales.
Smith, Peter W.F., Raymer, James, Bijak, Jakub, Abel, Guy J., Forster, Jonathan J.   +4 more
core   +1 more source

Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization

IEEE Access
Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties.
Shuangqing Chen, Shun Zhou, Zhe Xu, Yongbin Liu, Bing Guan, Xiaoyu Jiang, Wencheng Li   +6 more
doaj   +1 more source

Systematic Multi‐Level Analyses Decode the Arthritis‐Neurodegeneration Axis With In Vivo Validation

Advanced Science, EarlyView.
Arthritis and neurodegeneration are usually studied as separate disorders, but this study connects them through population evidence, genetic inference, transcriptomic mapping, and mouse models. It highlights RNF40 as a context‐dependent joint‐brain candidate, induced in inflammatory joints yet functionally linked to dopamine‐neuron vulnerability ...
Jinwen Wang, Wenhui Xie, Lei Yang, Zhengrong Wang, Yi Huang, Peng Huang, Yuan Liu, Jun Hu   +7 more
wiley   +1 more source