Toward Integrative Bayesian Analysis in Molecular Biology

Katja Ickstadt; Martin Schafer; Manuela Zucknick

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Toward Integrative Bayesian Analysis in Molecular Biology

机译：对分子生物学综合贝叶斯分析

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摘要

In the postgenome era, multiple types of molecular data for the same set of samples are often available and should be analyzed jointly in an integrative analysis in order to maximize the information gain. Bayesian methods are particularly well suitedfor integrating different biological data sources. In this article, we cover crucial tasks and corresponding methods with a focus on integrative analyses. We emphasize gene prioritization, model-based cluster approaches for subgroup identification, regression modeling, and prediction, as well as structure learning using network models. Our review introduces prior concepts for sparsity and variable selection and concludes with some aspects on validation and computation.

机译：在晚期时代，通常可用的多种类型的样本的分子数据，并且应该在一体化分析中共同分析，以最大化信息增益。贝叶斯方法特别适用于整合不同的生物数据来源。在本文中，我们涵盖了关注的任务和相应的方法，重点是综合分析。我们强调基因优先级，基于模型的群体识别，回归建模和预测方法，以及使用网络模型的结构学习。我们的评论介绍了稀疏性和变量选择的现有概念，并在验证和计算方面进行了一些方面。

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来源
《Annual Review of Statistics and Its Application》 |2018年第2018期|共27页
作者
Katja Ickstadt; Martin Schafer; Manuela Zucknick;
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作者单位

Faculty of Statistics TU Dortmund University 44227 Dortmund Germany;

Epidemiology Unit German Rheumatism Research Centre 10117 Berlin Germany;

Oslo Centre for Biostatistics and Epidemiology Department of Biostatistics University of Oslo 0317 Oslo Norway;

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原文格式 PDF
正文语种 eng
中图分类统计学;
关键词
Bayesian analysis; prior formulation; gene prioritization; subgroup identification; regression; structure learning; variable selection; validation;

机译：贝叶斯分析;先前配方;基因优先级;亚组识别;回归;结构学习;变量选择;验证;

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专利

1. Toward Integrative Bayesian Analysis in Molecular Biology [J] . Katja Ickstadt, Martin Schafer, Manuela Zucknick Annual Review of Statistics and Its Application . 2018,第期

机译：对分子生物学综合贝叶斯分析
2. GenFlow: generic flow for integration, management and analysis of molecular biology data [J] . Alexandre Dermargos, Hugo Aguirre Armelin, Jo?o Eduardo Ferreira, Genetics and molecular biology: publication of the Sociedade Brasileira de Genetica . 2004,第4期

机译：GenFlow：用于分子生物学数据整合，管理和分析的通用流程
3. An efficient and accurate integration of mini-Mu transposons in vitro: a general methodology for functional genetic analysis and molecular biology applications. [J] . Haapa S, Taira S, Heikkinen E, Nucleic Acids Research . 1999,第13期

机译：mini-Mu转座子在体外的有效和准确整合：功能基因分析和分子生物学应用的一般方法。
4. Bayesian Inference on Hidden Knowledge in High-Throughput Molecular Biology Data [C] . Viet-Anh Nguyen, Zdcna Koukolikova-Nicola, Franco Bagnoli, PRICAI 2008: Trends in Artificial Intelligence . 2008

机译：关于高通量分子生物学数据中隐藏知识的贝叶斯推断
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7. Analysis of molecular expression patterns and integration with other knowledge bases using probabilistic Bayesian network models [O] . Moler, Edward J., Mian, I.S. 2000

机译：使用概率贝叶斯网络模型分析分子表达模式并与其他知识库整合
8. Analysis of molecular expression patterns and integration with other knowledgebases using probabilistic Bayesian network models [R] . Moler, E. J., Mian, I. S. 2000

机译：使用概率贝叶斯网络模型分析分子表达模式并与其他知识库集成

Toward Integrative Bayesian Analysis in Molecular Biology

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