Metagenomics Analysis of Oral Microbiota associated with Periodontal Disease by Machine Learning Methods

Wei-Ren Lin ； Yaw-Ling Lin ； Ming-Li Liou ； Shih-Hao Chang

《NCS 2017 全國計算機會議》 2017 (2018/01) Pp. 772-777

https://doi.org/10.29428/9789860544169.201801.0145

摘要

Analysis of shotgun metagenomic data provides opportunity to understand the metabolic potentials, ecological roles, and evolutionary history of rare and uncultured microbes in natural communities by analyzing environmental DNA directly without prior cultivation. In this paper, we propose methods and implement tools to facilitate the bioinformatics analysis of metagenomic data. Several bioinformatics sequences analysis open-source softwares are integrated to construct accessible platforms for metagenomics analysis. By applying machine-learning- based approaches, we analyze the oral microbiota compositions to further understand the effects of periodontal treatments on patients with chronic periodontitis. These machine-learning approaches include the (unsupervised) Dirichlet multinomial mixture (DMM) regression models, t- SNE visualization of high-dimensional metagenomic data, as well as the supervised convolutional neural networks and support vector machines models.

關鍵字

metagenomics ； microbiome community ； machine learning ； support vector machine ； convolutional neural networks