Profile

松本 拡高 (Hirotaka MATSUMOTO)


Education

  • 2016.03: Doctor of Science, Department of Computational Biology and Medical Sciences, the University of Tokyo

  • 2013.03: Master of Science, Department of Computational Biology, the University of Tokyo

  • 2011.03: Bachelor of Science, Department of Bioinformatics and System Biology, the University of Tokyo


  • 2016.03: 東京大学大学院 新領域創成科学研究科 メディカル情報生命専攻 修了 博士（科学）

  • 2013.03: 東京大学大学院 新領域創成科学研究科 情報生命科学専攻 修了 修士（科学）

  • 2011.03: 東京大学 理学部 生物情報科学科 卒業 学士（理学）

Job experiences

  • 2020.04-present: Associate Professor at Nagasaki University, School of Information and Data Sciences

  • 2019.04-2020.03: Special Postdoctoral Researchers (SPDR) at RIKEN AIP Medical Image Analysis Team

  • 2016.04-2019.03: Research Fellow of the Japan Society for the Promotion of Science (PD) at RIKEN BDR Laboratory for Bioinformatics Research

  • 2013.04-2016.03: Research Fellow of the Japan Society for the Promotion of Science (DC1, Biology) at the University of Tokyo


  • 2020.04-present: 長崎大学 情報データ科学部 准教授

  • 2019.04-2020.03: 理研 革新知能統合研究センター 医用画像解析チーム 基礎科学特別研究員

  • 2016.04-2019.03: 理研 生命機能科学研究センター バイオインフォマティクス研究開発ユニット 日本学術振興会特別研究員（PD）

  • 2013.04-2016.03: 東京大学大学院 新領域創成科学研究科 メディカル情報生命専攻 木立研究室 日本学術振興会特別研究員（DC1）


Publications

Preprint


Journal Articles

  1. Miyamoto, K., Saiki, S., Matsumoto, H., Suzuki, A., Yamashita, Y., Iseki, T., ... & Hattori, N. (2022). Systemic Metabolic Alteration Dependent on the Thyroid‐Liver Axis in Early PD. Annals of Neurology.

  2. Uchimura, A., Matsumoto, H., Satoh, Y., Minakuchi, Y., Wakayama, S., Wakayama, T., ... & Yagi, T. (2022). Early embryonic mutations reveal dynamics of somatic and germ cell lineages in mice. Genome Research, 32(5), 945-955.

  3. Matsumoto, H., Mimori, T., & Fukunaga, T. (2021). Novel metric for hyperbolic phylogenetic tree embeddings. Biology Methods and Protocols, 6(1), bpab006.

  4. Ikeda, M., Matsumoto, H., & Izquierdo, E. J. (2021). Persistent thermal input controls steering behavior in Caenorhabditis elegans. PLOS Computational Biology, 17(1), e1007916.

  5. Kaminuma, E., Baba, Y., Mochizuki, M., Matsumoto, H., Ozaki, H., Okayama, T., Kato, T., Oki, S., Fujisawa, T., Arita, M., Oasawara, O., Kashima, H., and Takagi, T. (2020). DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences. Genes & Genetic Systems, 19-00034.[PubMed]

  6. Matsumoto, H., Hayashi, T., Ozaki, H., Tsuyuzaki, K., Umeda, M., Iida, T., ... & Nikaido, I. (2020). An NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data. NAR Genomics and Bioinformatics [nargab]

  7. Kojima, Y., Matsumoto, H., & Kiryu, H. (2019). Estimation of population genetic parameters using an EM algorithm and sequence data from experimental evolution populations. Bioinformatics.[PubMed]

  8. Matsumoto, H., Kiryu, H., Furusawa, C., Ko, M. S., Ko, S. B., Gouda, N., Hayashi, T. & Nikaido, I. (2017). SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation. Bioinformatics, 33(15), 2314-2321. [PubMed]

  9. Matsumoto, H., & Kiryu, H. (2016). SCOUP: a probabilistic model based on the Ornstein–Uhlenbeck process to analyze single-cell expression data during differentiation. BMC Bioinformatics, 17, 232.[PubMed]

  10. Matsumoto, H., & Kiryu, H. (2014). Integrating dilution-based sequencing and population genotypes for single individual haplotyping. BMC Genomics, 15(1), 733. [PubMed]

  11. Matsumoto, H., & Kiryu, H. (2013). MixSIH: a mixture model for single individual haplotyping. BMC Genomics, 14(Suppl 2), S5. [PubMed]


Talks

  1. Inference of gene regulatory network and drivers of differentiation from time-course single-cell RNA-Seq, 第5回生命医薬情報連合大会(IIBMP2016), Tokyo, Japan, Oct 2016

  2. １細胞発現データと確率過程から読み解く細胞分化機序, Yamagata, Japan, Oct 2015

  3. (1) BS-Seqを用いたDNAメチル化状態の定量化手法の開発と、(2) 1細胞RNA-Seqを用いたガンゲノム進化解析法の提案, 生命情報若手の会・第4回年会, Aichi, Japan, Mar 2013

  4. MixSIH: a mixture model for single individual haplotyping, ISCB-Asia/SCCG 2012, Shenzhen, China, Dec 2012

  5. 確率モデルによるハプロタイプアセンブリ手法の開発, 生命情報若手の会・第3回年会, Aichi, Japan, Oct 2011


Posters

  1. Modeling gene expression dynamics along differentiation with single-cell data and stochastic process, 第4回生命医薬情報連合大会(IIBMP2015),Kyoto, Japan, Oct 2015

  2. A stochastic process for time series analysis of gene expression dynamics, 8th AYRCOB, Hshinchu, Taiwan, Jan 2015

  3. A stochastic process for time series analysis of gene expression dynamics, GIW/ISCB-Asia2014, Tokyo, Japan, Dec 2014

  4. Modeling expression dynamics with stochastic process, 第3回生命医薬情報連合大会(IIBMP2014), Miyagi, Japan, Oct 2014

  5. Modeling dynamic biological processes in the sequencing era, 生命情報若手の会・第5回年会, Chiba, Japan, Feb 2014

  6. A probabilistic model for extracting highly reliable haplotype regions in single individual haplotyping, 東京大学GCOE「ゲノム情報ビッグバンから読み解く生命圏」ワークショップ2012, Chiba, Japan, Nov 2012

  7. A probabilistic model for extracting highly reliable haplotype regions in single individual haplotyping, BiWO2012, Tokyo, Japan, Oct 2012

  8. bisulfite sequencingからアレル特異的なDNAメチル化状態を推定する手法の開発, NGS現場の会第二回研究会, Osaka, Japan, May 2012

  9. A probabilistic model for haplotype assembly, 第34回日本分子生物学会, Yokohama, Japan, Dec 2011


Book Chapters

  1. 松本 拡高, 1細胞RNA-seqを用いた細胞タイプの同定技術, 「機械学習を生命科学に使う！」(羊土社)[羊土社]

  2. 松本 拡高, 木立 尚孝, 二階堂 愛, 分化過程の再構築と擬時間に基づく発現変動解析, 「実験医学別冊 シングルセル解析プロトコル」(羊土社)[amazon]

  3. 松本 拡高, 二階堂 愛, 網羅的な1細胞発現から知識を取り出すデータ解析技術の新展開, 「細胞 2017年 5月臨時増刊号 日常化するシングルセル遺伝子発現解析」(ニュー・サイエンス社) [amazon]


Seminars

  1. An efficient regulatory network inference algorithm from single-cell RNA-seq during differentiation, T-LSI and C-AIR Joint Symposium on Life Science Innovation and Artificial Intelligence, Tsukuba, Japan, May 2017

  2. (1.Mixture modelを用いたハプロタイプ推定と、(2.確率過程を用いた遺伝子発現ダイナミクス解析, 早稲田バイオインフォマティクスセミナー, Tokyo, Japan, Dec 2014

  3. Detection of chimeric fragment in long fragment read technology by using statistical phasing method, CBRC seminar, Tokyo, Japan, Jul 2013

  4. MixSIH: a mixture model for single individual haplotyping, CBRC seminar, Tokyo, Japan, Mar 2012


Awards

  1. 最優秀口頭発表賞, 第5回生命医薬情報連合大会(IIBMP2016), 2016

  2. 2nd Prize of DDBJ Challenge Awards 2016, http://www.ddbj.nig.ac.jp/whatsnew/wn160930-e.html

  3. Top Award of "Excellent Research Award (Doctoral Course)", Department of Computational Biology and Medical Sciences, the University of Tokyo, 2016

  4. Best Presentation Prize, 生命情報若手の会・第5回年会, 2014

  5. Dean's Prize (Master's Course), Graduate School of Frontier Sciences, the University of Tokyo, 2013


Fellowships