Gibbs Sampling Based Banoian Biclustering of Gene Expression Data
2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)(2020)
摘要
This paper proposes a rigorous Bayes model to infer biclusters of microarray data formed by gene sets and condition sets. The model employs few fine-tune threshold parameters and handles missing data by statistically inferring them in Gibbs sampling. The proposed model outperforms others on simulated data and discovered meaningful local patterns, 63% of which were corroborated by biological evidence.
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关键词
Biclustering,Bayesian inference,Gibbs sampling,Multivariate Gaussian distribution
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