Development of novel algorithm for quality control of metabolomics data
| Project/Area Number |
17K00416
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Life / Health / Medical informatics
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| Research Institution | Tokyo Medical University |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | メタボローム / ソフトウェア / 人工知能 / メタボーローム / ソフトウエア学 |
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| Outline of Final Research Achievements |
This study aimed to develop a novel tool to analyze metabolomic data produced by a mass spectrometry. First, a complementary tool to analyze the feature or raw data, accommodating various types of mass spectrometry, which can optimize the options of subsequent automatic data processing. The developed program further optimizes the options of each step of the analyses based on the overlaid datasets. Therefore, a user is require to prepare a manually curated data (a training data). The program processes the other samples according to the training data. This algorithm functions for any types of data and enable high throughput non-targeted metabolomic analyses.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究は代謝物を網羅的に測定するメタボローム解析のデータ解析を自動化させることが目的である。測定データに含まれる全てのシグナルを正確に処理して、疾患マーカーの探索や生体の代謝の理解ができることが望ましいが、実際に完全な自動化ができているソフトウェアがなく、熟練技術者の品質制御・評価が必要となり、データ解析がボトルネックになっている。そこで熟練技術者の作業と評価基準を再現して自動的にデータ解析することができるアルゴリズムや関連するソフトを開発した。本手法は特定の機器やメーカー等に依存せず広く使用でき、本研究成果によりメタボロームを用いた臨床研究や創薬などの様々な応用研究が加速できると考えられる。
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Report
(4 results)
Research Products
(51 results)
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[Journal Article] High-resolution imaging mass spectrometry combined with transcriptomic analysis identified a link between fatty acid composition of phosphatidylinositols and the immune checkpoint pathway at the primary tumour site of breast cancer2020
Author(s)
Kawashima M, Tokiwa M, Nishimura T, Kawata Y, Sugimoto M, Kataoka TR, Sakurai T, Iwaisako K, Suzuki E, Hagiwara M, Harris AL, Toi M.
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Journal Title
Br J Cancer
Volume: 122
Pages: 245-257
DOI
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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[Journal Article] Association between dyslipidemia and plasma levels of branched-chain amino acids in the Japanese population without diabetes mellitus2019
Author(s)
Keiko Fukushima, Sei Harada, Ayano Takeuchi, Ayako Kurihara, Miho Iida, Kota Fukai, Kazuyo Kuwabara, Suzuka Kato, Minako Matsumoto, Aya Hirata, Miki Akiyama, Masaru Tomita, Akiyoshi Hirayama, Asako Sato, Chizuru Suzuki, Masahiro Sugimoto, Tomoyoshi Soga, Daisuke Sugiyama, Tomonori Okamura, Toru Takebayashi
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Journal Title
Journal of Clinical Lipidology
Volume: 13
DOI
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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