Construction of cell evaluation system utilizing online distributed machine learning
Project/Area Number |
26670181
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Research Category |
Grant-in-Aid for Challenging Exploratory Research
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Allocation Type | Multi-year Fund |
Research Field |
Human pathology
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Research Institution | National Center for Child Health and Development |
Principal Investigator |
Umezawa Akihiro 国立研究開発法人国立成育医療研究センター, 再生医療センター, 副所長/再生医療センター長 (70213486)
|
Co-Investigator(Kenkyū-buntansha) |
神崎 誠一 国立研究開発法人国立成育医療研究センター, 細胞医療研究部, 研究員 (20589741)
|
Project Period (FY) |
2014-04-01 – 2017-03-31
|
Project Status |
Completed (Fiscal Year 2016)
|
Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2014: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
|
Keywords | 移植病理 / エピゲノム / 機械学習 / 再生医療 / 幹細胞 |
Outline of Final Research Achievements |
In this research, we established cell evaluation technology as applied to bio-big data of machine learning technology, information Retrieval technology, and examined issues for commercialization and service of evaluation technology by verification verification. We utilize genome wide data utilizing genome, transcriptome, epigenome data to classify and evaluate iPS cells, ES cells and somatic stem cells using a large-scale distributed online machine learning framework. Comprehensive DNA methylation analysis was performed using different tissue origin, different human stem cells, and human ES cells established by different methods.
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Report
(4 results)
Research Products
(2 results)
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[Journal Article] Ataxia telangiectasia derived iPS cells show preserved x-ray sensitivity and decreased chromosomal instability2014
Author(s)
Fukawatase Y, Toyoda M, Okamura K, Nakamura K, Nakabayashi K, Takada S, Yamazaki-Inoue M, Masuda A, Nasu M, Hata K, Hanaoka K, Higuchi A, Takubo K, Umezawa A
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Journal Title
Sci. Rep.
Volume: 4
Issue: 1
Pages: 5421-5421
DOI
Related Report
Peer Reviewed / Open Access