Saito, Rintaro

写真a

Affiliation

Graduate School of Media and Governance (Shonan Fujisawa)

Position

Project Professor (Non-tenured)

Related Websites

Career 【 Display / hide

  • 2000.04
    -
    2002.03

    理化学研究所, ゲノム科学総合研究センター, 研究員

  • 2002.04
    -
    2011.01

    慶應義塾大学, 環境情報学部, 専任講師(有期)

  • 2011.02
    -
    2014.01

    University of California, San Diego, Department of Medicine, Visiting Assistant Professor

  • 2014.03
    -
    2017.07

    University of California, San Diego, Department of Medicine, Associate Project Scientist

  • 2017.09
    -
    Present

    慶應義塾大学, 政策・メディア研究科, 特任教授

Academic Background 【 Display / hide

  • 2000.03

    Keio University, 政策・メディア研究科

    Graduate School, Completed, Doctoral course

Academic Degrees 【 Display / hide

  • 学術, Keio University, 2000.03

 

Research Areas 【 Display / hide

  • Informatics / Life, health and medical informatics

 

Books 【 Display / hide

  • 実験医学「Cytoscapeによる細胞内インタラクトームの解析」

    SAITO Rintaro, ONO, Keiichiro, 羊土社, 2013.08

    Scope: 2291-2297

  • 機能性non-coding RNA「バイオインフォマティクスを用いたnon-coding RNA予測の様々な試み」

    SAITO RINTARO, クバプロ, 2006.04

    Scope: 171-187

  • 人工知能学事典「モチーフ抽出」

    SAITO RINTARO, 共立出版, 2005.12

    Scope: 17-4

  • バイオインフォマティクスの基礎-ゲノム解析プログラミングを中心に

    TOMITA, Masaru, SAITO Rintaro, サイエンス社, 2005.07

  • ゲノムネットワーク「ゲノムワイドデータの精製」

    SAITO RINTARO, Suzuki Harukazu, Tomita Masaru, 共立出版, 2004.12

    Scope: III 8

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Papers 【 Display / hide

  • Study Profile of the Tsuruoka Metabolomics Cohort Study (TMCS)

    Harada S, Iida M, Miyagawa N, Hirata A, Kuwabara K, Matsumoto M, Okamura T, Edagawa S, Kawada Y, Miyake A, Toki R, Akiyama M, Kawai A, Sugiyama D, Sato Y, Takemura R, Fukai K, Ishibashi Y, Kato S, Kurihara A, Sata M, Shibuki T, Takeuchi A, Kohsaka S, Sawano M, Shoji S, Izawa Y, Katsumata, Oki K, Takahashi S, Takizawa T, Maruya H, Nishiwaki Y, Kawasaki R, Hirayama A, Ishikawa T, Saito R, Sato A, Soga T, Sugimoto M, Tomita M, Komaki M, Ohmomo H, Ono K, Otsuka-Yamasaki Y, Shimizu A, Sutoh Y, Hozawa A, Kinoshita K, Koshiba S, Kumada K, Ogishima S, Sakurai-Yageta M, Tamiya G, Takebayashi T

    J Epidemiol  2023

    Research paper (scientific journal), Joint Work, Accepted

  • Niacin restriction with NAMPT-inhibition is synthetic lethal 1 to neuroendocrine carcinoma

    Nomura M, Ohuchi M, Sakamoto Y, Kudo K, Yaku K, Soga T, Sugiura Y, Morita M, Hayashi K, Miyahara S, Sato T, Yamashita Y, Ito S, Kikuchi N, Sato I, Saito R, Yaegashi N, Fukuhara T, Yamada H, Shima H, Nakayama K, Hirao A, Kawasaki K, Arai Y, Akamatsu S, Tanuma S, Sato T, Nakagawa T, Tanuma N

    Nat Commun  2023

    Research paper (scientific journal), Joint Work, Accepted

  • Suppression of mitochondrial respiration is a feature of cellular glucose toxicity

    Sharma K, Zhang G, Saito R

    Trans Am Clin Climatol Assoc 133   24 - 33 2023

    Joint Work

  • iDMET: network-based approach for integrating differential analysis of cancer metabolomics

    Matsuta R., Yamamoto H., Tomita M., Saito R.

    BMC Bioinformatics (BMC Bioinformatics)  23 ( 1 )  2022.12

     View Summary

    Background: Comprehensive metabolomic analyses have been conducted in various institutes and a large amount of metabolomic data are now publicly available. To help fully exploit such data and facilitate their interpretation, metabolomic data obtained from different facilities and different samples should be integrated and compared. However, large-scale integration of such data for biological discovery is challenging given that they are obtained from various types of sample at different facilities and by different measurement techniques, and the target metabolites and sensitivities to detect them also differ from study to study. Results: We developed iDMET, a network-based approach to integrate metabolomic data from different studies based on the differential metabolomic profiles between two groups, instead of the metabolite profiles themselves. As an application, we collected cancer metabolomic data from 27 previously published studies and integrated them using iDMET. A pair of metabolomic changes observed in the same disease from two studies were successfully connected in the network, and a new association between two drugs that may have similar effects on the metabolic reactions was discovered. Conclusions: We believe that iDMET is an efficient tool for integrating heterogeneous metabolomic data and discovering novel relationships between biological phenomena.

  • Urinary metabolome analyses of patients with acute kidney injury using capillary electrophoresis-mass spectrometry

    Saito R., Hirayama A., Akiba A., Kamei Y., Kato Y., Ikeda S., Kwan B., Pu M., Natarajan L., Shinjo H., Akiyama S., Tomita M., Soga T., Maruyama S.

    Metabolites (Metabolites)  11 ( 10 )  2021.10

     View Summary

    Acute kidney injury (AKI) is defined as a rapid decline in kidney function. The associated syndromes may lead to increased morbidity and mortality, but its early detection remains difficult. Using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), we analyzed the urinary metabolomic profile of patients admitted to the intensive care unit (ICU) after invasive surgery. Urine samples were collected at six time points: before surgery, at ICU admission and 6, 12, 24 and 48 h after. First, urine samples from 61 initial patients (non-AKI: 23, mild AKI: 24, severe AKI: 14) were measured, followed by the measurement of urine samples from 60 additional patients (non-AKI: 40, mild AKI: 20). Glycine and ethanolamine were decreased in patients with AKI compared with non-AKI patients at 6–24 h in the two groups. The linear statistical model constructed at each time point by machine learning achieved the best performance at 24 h (median AUC: 89%, cross-validated) for the 1st group. When cross-validated between the two groups, the AUC showed the best value of 70% at 12 h. These results identified metabolites and time points that show patterns specific to subjects who develop AKI, paving the way for the development of better biomarkers.

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Papers, etc., Registered in KOARA 【 Display / hide

Presentations 【 Display / hide

  • Multi-omics and Systems Analysis Reveal a Novel Role of MDM2 in Diabetic Nephropathy

    Saito R, Rocanin-Arjo A, You Y-H, Darshi M, Van Espen B, Miyamoto S, Pham J, Pu M, Romoli S, Natarajan L, Ju W, Kretzler M, Nelson R, Ono K, Thomasova D, Mulay SR, Ideker T, D'Agati, Beyret E, Izpisua Belmonte JC, Anders HJ, Sharma K

    ISN's Forefronts Symposium on the Metabolome and Microbiome in Kidney Disease, 

    2016

    Oral presentation (general)

  • Computational Prediction and Experimental Analyses of Proteins That Bridge Metabolite Markers of Human Diabetic Nephropathy

    Saito R, Rocanin-Arjo A, You Y-H, Darshi M, Van Espen B, Pu M, Romoli S, Natarajan L, Ju W, Kretzler M, Nelson R, Ono K, Thomasova D, Mulay S, Belmonte JC, Anders HJ, Sharma K

    ASN Kidney Week 2015 Annual Meeting, 

    2015

    Oral presentation (general)

  • A travel guide to Cytoscape plugins

    Saito R, Smoot ME, Ono K, Ruscheinski J, Wang P-L, Lotia S, Pico AR, Bader GD, Ideker T.

    Cytoscape Retreat, 

    2012

    Oral presentation (general)

  • Comprehensive Analysis of Domain-Domain Interactions Using In Vitro Virus

    Saito R, Ozawa Y, Fujimori S, Matsui M, Ushiama S, Kashima H, Yanagawa H, Miyamoto-Sato E, Tomita M

    Genome Informatics Workshop 2007 (GIW2007) (Singapore) , 

    2007

    Oral presentation (general)

  • IVV データを用いたモチーフ間相互作用ネットワークの構築と創薬への応用

    斎藤輪太郎, 宮本悦子, 柳川弘志, 冨田勝

    分子生物学会2006フォーラム シンポジウム Sp2K「ゲノムネットワーク解析に基づく新しい創薬,診断,治療戦略」 (名古屋) , 

    2006

    Oral presentation (general)

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Research Projects of Competitive Funds, etc. 【 Display / hide

  • 統合シースレスキャピラリー電気泳動-質量分析システムの開発

    2022.09
    -
    2025.03

    経済産業省, 成長型中小企業等研究開発支援事業 (Go-Tech事業), Research grant, Coinvestigator(s)

  • Construction of Pipeline for Integrated Metabolome Analyses of Kidney Disease

    2022.04
    -
    2025.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, 基盤研究(C), Principal investigator

  • 仮想人体構築のための数理モデル化

    2020
    -
    2022

    文部科学省・日本学術振興会, 科学研究費助成事業, 学術変革領域研究(B), No Setting, Coinvestigator(s)

  • Development of AI for the discovery of novel kidney disease genes using metabolomics and network biology

    2019.04
    -
    2022.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), Principal investigator

  • 人々を軸にあらゆる情報をオープンに活用する基盤「PeOPLe」によるライフイノベーションの創出

    2018
    -
    2022

    国立研究開発法人科学技術振興機構, 産学共創プラットフォーム共同研究推進プログラム, Coinvestigator(s)

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Intellectual Property Rights, etc. 【 Display / hide

  • タンパク質間相互作用の評価方法

    Date applied: 2001-397762  2001 

    Patent, Joint

 

Courses Taught 【 Display / hide

  • GENOMIC MOLECULAR BIOLOGY 2

    2023

  • GENOMIC MOLECULAR BIOLOGY 1

    2023

  • GENOMIC MOLECULAR BIOLOGY 2

    2022

  • GENOMIC MOLECULAR BIOLOGY 1

    2022

  • GENOMIC MOLECULAR BIOLOGY 2

    2021

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Courses Previously Taught 【 Display / hide

  • ゲノム分子生物学1

    Keio University

    2018.04
    -
    2019.03

    Spring Semester

  • ゲノム分子生物学2

    Keio University

    2018.04
    -
    2019.03

    Autumn Semester, Lecture

  • 生命情報解析

    慶應義塾大学環境情報学部

    2010.04
    -
    2011.03

  • バイオインフォマティクスアルゴリズム

    慶應義塾大学政策・メディア研究科

    2010.04
    -
    2011.03

  • ゲノム解析プログラミング

    慶應義塾大学環境情報学部

    2010.04
    -
    2011.03

 

Memberships in Academic Societies 【 Display / hide

  • 日本分子生物学会

     
  • 日本バイオインフォマティクス学会

     

Committee Experiences 【 Display / hide

  • 2018

    生命医薬情報学連合大会プログラム委員, 日本バイオインフォマティクス学会

  • 2011
    -
    2014

    Collaboration consultant, Cytoscape instructor, National Resource for Network Biology / The San Diego Center for Systems Biology

  • 2010

    Programme committee member, The International Conference on Bioinformatics (InCoB2010)

  • 2008
    -
    2010

    Programme committee member, Genome Informatics Workshop (GIW)