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
Job experiences
  • 2016.04-present: Research Fellow of the Japan Society for the Promotion of Science (PD) in RIKEN ACCC Bioinformatics Research Unit
  • 2013.04-2016.03: Research Fellow of the Japan Society for the Promotion of Science (DC1, Biology)

Publications
Under submission


Journal Articles
  1. 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, btx194. [PubMed]
  2. Matsumoto, H., & Kiryu, H. (2016). SCOUP: a probabilistic model based on the Ornstein–Uhlenbeck process to analyze single-cell expression data during differentiation. BMC Bioinformatics17, 232.
  3. Matsumoto, H., & Kiryu, H. (2014). Integrating dilution-based sequencing and population genotypes for single individual haplotyping. BMC Genomics15(1), 733[PubMed]
  4. Matsumoto, H., & Kiryu, H. (2013). MixSIH: a mixture model for single individual haplotyping. BMC Genomics14(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, 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. (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
  2. Detection of chimeric fragment in long fragment read technology by using statistical phasing method, CBRC seminar, Tokyo, Japan, Jul 2013
  3. 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
  1. 平成24年度(後期)東京大学学術研究活動等奨励事業(国外)