Bayesian Hierarchical Modelling for Antimicrobial Resistance

被引:1
|
作者
Zhelyazkova, Maya [1 ]
Yordanova, Roumyana [2 ,3 ]
Mihaylov, Iliyan [1 ]
Kirov, Stefan [4 ]
Tsonev, Stefan [5 ]
Danko, David [6 ]
Vassilev, Dimitar [1 ]
机构
[1] Sofia Univ St Kliment Ohridski, Fac Math & Informat, 5 James Bourchier Blvd, Sofia 1164, Bulgaria
[2] Hokkaido Univ, Sapporo, Hokkaido, Japan
[3] Bulgarian Acad Sci, Inst Math & Informat, Acad Georgi Bonchev Str,Block 8, Sofia, Bulgaria
[4] Bristol Myers Squibb, 311 Pennington Rocky Hill Rd, Pennington, NJ USA
[5] AgroBioInst, 8 Dragan Tsankov Blvd, Sofia 1164, Bulgaria
[6] Weill Cornell Med Coll, New York, NY USA
关键词
Bayesian hierarchical spatial inference; Spatial correlations; Antimicrobial resistance; Metagenomics;
D O I
10.1007/978-3-030-96638-6_9
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Antimicrobial resistance poses a serious health problem. Computational and statistical approaches have been developed for bacterial antimicrobial resistance discovery and classification. Next generation sequencing technologies allows us to analyze complex metagenomes and the presence of resistomes in them. In this work we apply Bayesian hierarchical spatial model to estimate the relative risk of antimicrobial resistance related taxa by using the available spatial information of the samples.
引用
收藏
页码:79 / 87
页数:9
相关论文
共 50 条
  • [31] Posterior Predictive Simulation Checks for Hierarchical Bayesian Modelling
    Elobaid, Rafida M.
    Akma, Noor, I
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2010, 19 (D10): : 40 - 49
  • [32] Statistical comparison of classifiers through Bayesian hierarchical modelling
    Giorgio Corani
    Alessio Benavoli
    Janez Demšar
    Francesca Mangili
    Marco Zaffalon
    Machine Learning, 2017, 106 : 1817 - 1837
  • [33] A Bayesian approach to modeling antimicrobial multidrug resistance
    Zhang, Min
    Wang, Chong
    O'Connor, Annette
    PLOS ONE, 2021, 16 (12):
  • [34] Hierarchical viewpoint discovery from tweets using Bayesian modelling
    Zhu, Lixing
    He, Yulan
    Zhou, Deyu
    EXPERT SYSTEMS WITH APPLICATIONS, 2019, 116 : 430 - 438
  • [35] Hierarchical Bayesian Modelling of Geographic Dependence of Risk in Household Insurance
    Markus, Laszlo
    Arato, N. Miklos
    Prokaj, Vilmos
    ADVANCES IN DATA ANALYSIS: THEORY AND APPLICATIONS TO RELIABILITY AND INFERENCE, DATA MINING, BIOINFORMATICS, LIFETIME DATA, AND NEURAL NETWORKS, 2010, : 219 - 227
  • [36] Multi-population mortality modelling: a Bayesian hierarchical approach
    Shi, Jianjie
    Shi, Yanlin
    Wang, Pengjie
    Zhu, Dan
    ASTIN BULLETIN-THE JOURNAL OF THE INTERNATIONAL ACTUARIAL ASSOCIATION, 2024, 54 (01) : 46 - 74
  • [38] Leveraging single-case results to Bayesian hierarchical modelling
    Si, Shijing
    Gu, Jia-wen
    Tian, Maozai
    COMPUTATIONAL STATISTICS, 2024, : 795 - 819
  • [39] A Bayesian hierarchical approach to the joint modelling of Revealed and stated choices
    Li, Zili
    Washington, Simon P.
    Zheng, Zuduo
    Prato, Carlo G.
    JOURNAL OF CHOICE MODELLING, 2023, 47
  • [40] A comparison of the hierarchical likelihood and Bayesian approaches to spatial epidemiological modelling
    Jang, Myoung Jin
    Lee, Youngjo
    Lawson, Andrew B.
    Browne, William J.
    ENVIRONMETRICS, 2007, 18 (07) : 809 - 821