Inference of cell differentiation factors in pluripotent cells by Structural Equation Modelling
Project/Area Number |
24510285
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
System genome science
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Research Institution | National Institute of Advanced Industrial Science and Technology |
Principal Investigator |
ABURATANI Sachiyo 独立行政法人産業技術総合研究所, ゲノム情報研究センター, 研究チーム長 (10361627)
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Project Period (FY) |
2012-04-01 – 2015-03-31
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Project Status |
Completed (Fiscal Year 2014)
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Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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Keywords | 構造方程式モデリング / 遺伝子ネットワーク / 多様性 / ES細胞 / 細胞分化 / 多能性 / ネットワーク推定 / 因子分析 / 発現制御 / 発生過程 / 形態形成 / 初期胚形成 / 発現プロファイル |
Outline of Final Research Achievements |
In embryonic stem cells, various transcription factors (TFs) maintain pluripotency. To gain insights into the regulatory system controlling pluripotency, I inferred the regulatory relationships between the TFs expressed in ES cells. In this study, I applied a method based on structural equation modeling (SEM), combined with factor analysis, to 649 expression profiles of 19 TF genes measured in mouse Embryonic Stem Cells (ESCs). The factor analysis identified 19 TF genes that were regulated by several unmeasured factors. Since the known cell reprogramming TF genes (Pou5f1, Sox2 and Nanog) are regulated by different factors, each estimated factor is considered to be an input for signal transduction to control pluripotency in mouse ESCs. In the inferred network model, TF proteins were also arranged as unmeasured factors that control other TFs. The interpretation of the inferred network model revealed the regulatory mechanism for controlling pluripotency in ES cells.
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Report
(4 results)
Research Products
(26 results)
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[Journal Article] Gene expression profiling of hepatitis B- and hepatitis C-related hepatocellular carcinoma using graphical Gaussian modeling.2013
Author(s)
Ueda T, Honda M, Horimoto K, Aburatani S, Saito S, Yamashita T, Sakai Y, Nakamura M, Takatori H, Sunagozaka H, Kaneko S.
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Journal Title
Genomics.
Volume: Apr;101(4)
Issue: 4
Pages: 238-48
DOI
Related Report
Peer Reviewed
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