Funahashi Akira

フナハシアキラ | Funahashi Akira

Affiliation and department：
Job title： Professor
Homepage URL (1)： https://fun.bio.keio.ac.jp/

Research field (2)： Biological, health, and medical informatics , Systems genomics

Research keywords (3)： Computational Biology , Quantitative Biology , Systems Biology

Research theme for competitive and other funds (24)：

2022 - 2028 Advanced Bioimaging Support
2022 - 2026 Genome protection and repair mechanisms for the extreme desiccation tolerance, anhydrobiosis
2020 - 2026 構造的・動力学的制約を活用した多元混合化学情報の解読とその応用
2021 - 2026 機械学習を用いた精巣組織培養の自動最適化による精子形成の理解
2020 - 2023 Development of a cell tracking algorithm using deep learning

2019 - 2022 Efficient maturation of 3D tissues in vitro by intelligent mechanical stimuli

2019 - 2021 Development of the evaluation method for differentiation and maturity of human ES, iPS cell-derived cardiomyocytes with deep learning

2017 - 2021 Gene regulatory networks underlying 3-D conformational change in genome associated with anhydrobiosis

2018 - 2020 Development of Robust Segmentation Algorithm using Unsupervised Learning

2016 - 2020 Development of Deep Learning-based Nuclear Detection Algorithm for Mouse Embryo

2015 - 2020 Regenerative-medicine oriented controlling of neuronal cell differentiation with shear stress

2016 - 2019 Is Mg ion a novel second messenger for regulating energy metabolism?

2016 - 2019 Development of informatics techniques for analysis developmental lineages

2015 - 2019 Construction and Experimental Validation of Mechanical Models for Cell Division

2014 - 2016 Development of High-speed, High-resolution 3D Single-Molecule Measurement System

2013 - 2015 数理モデル構築を指向した生化学ネットワーク解析環境の実装

2012 - 2015 Design and Implementation of high-performance spatial model simulator

2009 - 2014 Informatics and mathematics for In siloco reconstruction of mammalian early embryogenesis

2011 - 2013 超高速生化学ネットワークシミュレーションの基盤構築

2009 - 2011 Systems biological analysis of signal transduction in growth cones

2009 - 2011 Design and Implementation of high-performance sequence analysis environment using GPGPU

2009 - 2011 Implementation of integrated biochemical network simulator

2001 - 2002 PCクラスタにおける適応型ルーティングアルゴリズムに関する研究

1998 - 1999 超並列計算機向き結合網RDT上でのアダプティブルーティング

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Papers (133)：

Taichi Kanazawa, Tatsuma Yao, Sora Takeshita, Tatsuki Hirai, Ryo Suenaga, Takahiro G Yamada, Yuta Tokuoka, Kazuo Yamagata, Akira Funahashi. Four-dimensional Label-free Live Cell Image Segmentation for Predicting Live Birth Potential of Mouse Embryos. 2024
Yuta Tokuoka, Tsutomu Endo, Takashi Morikura, Yuki Hiradate, Masahito Ikawa, Akira Funahashi. Deep Learning-based Automated Prediction of Mouse Seminiferous Tubule Stage by Using Bright-field Microscopy. 2024
Yusuke Hiki, Yuta Tokuoka, Takahiro G. Yamada, Akira Funahashi. Inference of Gene Regulatory Networks for Overcoming Low Performance in Real-world Data. 2024
Mengji Zhang, Yusuke Hiki, Akira Funahashi, Tetsuya J. Kobayashi. A Deep Position-encoding Model for Predicting Olfactory Perception from Molecular Structures and Electrostatics. npj Systems Biology and Applications. 2024
Shintaro Miyaki, Shori Nishimoto, Yuta Tokuoka, Takahiro G Yamada, Takashi Morikura, Akira Funahashi. Cell Segmentation Without Annotation by Unsupervised Domain Adaptation Based on Cooperative Self-learning. 2024

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MISC (60)：

徳岡雄大, 山田貴大, 舟橋啓. 機械学習によるバイオイメージセグメンテーション. 機械学習を生命科学に使う! シークエンスや画像データをどう解析し、新たな生物学的発見につなげるか?. 2020. 38. 134-141
山田貴大, 徳岡雄大, 尾関光徳, 井伊海人, 広井賀子, 舟橋啓. クラシフィケーションの原理と生物・医療への応用. 機械学習を生命科学に使う! シークエンスや画像データをどう解析し、新たな生物学的発見につなげるか?. 2020. 38. 109-117
舟橋啓, 徳岡雄大, 山田貴大. Google Colaboratory入門-機械学習を体験しよう. 機械学習を生命科学に使う! シークエンスや画像データをどう解析し、新たな生物学的発見につなげるか?. 2020. 38. 16-35
舟橋啓, 仲井祐一郎, 広井賀子. いま知りたい!! DIYで顕微鏡を拡張しよう! 電気式焦点可変レンズによる三次元計測システムの構築. 実験医学. 2019. 37. 18. 3116-3120
山田貴大, 舟橋啓, 黄川田隆洋. ネムリユスリカの培養細胞の乾燥耐性に迫る. バイオサイエンスとインダストリー(B&I). 2019. 77. 4

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Books (8)：

機械学習を生命科学に使う! : シークエンスや画像データをどう解析し、新たな生物学的発見につなげるか?
羊土社 2020 ISBN:9784758103916
数でとらえる細胞生物学
羊土社 2020 ISBN:9784758121064
組織としての生命
慶應義塾大学出版会 2019
バイオインフォマティクス入門
慶應義塾大学出版会 2015
Modeling and Simulation Using CellDesigner
Springer 2014 ISBN:9781493908042

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Lectures and oral presentations (69)：

深層学習が駆動する定量生物学の新展開
(データ駆動生物学ワークショップ 2021)
CellDesigner: A modeling tool for biochemical networks
(Computational Modeling in Biology Network 2020 (COMBINE 2020) 2020)
一細胞系譜解析による低グルコース培養下大腸菌集団のATP濃度多様性の解明
(日本数理生物学会 2020年度年会 2020)
ライブセルイメージングと深層学習を用いた胚発生過程定量システムの構築
(第81回応用物理学会秋季学術講演会 2020)
深層学習を用いたマウス発生過程における定量的指標の獲得
(第30回日本サイトメトリー学会学術集会 2020)

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Education (3)：

2000 - 2000 Keio University Graduate School, Division of Science and Engineering Dept. of Computer Science
1997 - 1997 Keio University Graduate School, Division of Science and Engineering Dept. of Computer Science
1995 - 1995 Keio University Faculty of Science and Engineering Department of Electrical Engineering

Professional career (1)：

Ph.D. (Keio University)

Work history (13)：

2022/04 - 現在 Dept. of Biosciences and Informatics, Keio University Professor
2017/04 - 現在 Yamaguchi University Graduate School of Medicine 医学系研究科 Part-time teacher
2007/04 - 現在 The Systems Biology Institute(SBI) Visiting Scientist
2020/08 - 2023/03 Gunma University Center for Mathematics and Data Science Visiting Professor
2009/04 - 2022/03 Associate Professor, Dept. of Biosciences and Informatics, Keio University

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Committee career (19)：

2023/04 - 現在 Japan Society for the Promotion of Science Grant-in-Aid for Transformative Research Areas Advisor
2020/05 - 現在 Google Summer of Code 2020 Google Summer of Code Mentors
2019/04 - 現在 Japan Science and Technology Agency JST未来事業「共通基盤」領域専門アドバイザー
2011/02 - 現在 Frontiers Frontiers in Systems Biology Associate Editor
2008 - 現在 Japanese Society for Quantitative Biology Core member of Japanese Society for Quantitative Biology

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Awards (1)：

2015/10 - Japan Society for the Promotion of Science 平成27年度科学研究費審査委員表彰

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