著者

Makito Oku

出版者

Information Processing Society of Japan

雑誌

IPSJ Transactions on Bioinformatics (ISSN:18826679)

巻号頁・発行日

vol.12, pp.9-16, 2019 (Released:2019-03-25)

参考文献数

16

被引用文献数

2

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In this paper, I propose two novel methods for extracting synchronously fluctuated genes (SFGs) from a transcriptome data. Variability and synchrony in biological signals are generally considered to be associated with the system's stability in some sense. However, a standard method for extracting SFGs from a transcriptome data with high reproducibility has not been established. Here, I propose two novel methods for extracting SFGs. The first method has two steps: selection of remarkably fluctuated genes and extraction of synchronized gene clusters. The other method is based on principal component analysis. It has been confirmed that the two methods have high extraction performance for artificial data and a moderate level of reproducibility for real data. The proposed methods will help to extract candidate genes related to the stability and homeostasis in living organisms.