Two Novel Methods for Extracting Synchronously Fluctuated Genes

• Oku Makito

  Institute of Natural Medicine, University of Toyama

抄録

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.

収録刊行物

• IPSJ Transactions on Bioinformatics

  IPSJ Transactions on Bioinformatics 12 (0), 9-16, 2019

  一般社団法人 情報処理学会

キーワード

• transcriptome
• synchronously fluctuated gene
• clustering
• principal component analysis

詳細情報

• CRID: 1390282763116327168
• NII論文ID: 130007618904
• DOI: 10.2197/ipsjtbio.12.9
• ISSN: 18826679
• Web Site: https://www.jstage.jst.go.jp/article/ipsjtbio/12/0/12_9/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可