Development of SMAD for big query on big data

• Project/Area Number: 17H01693
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Theory of informatics
• Research Institution: The University of Tokyo
• Principal Investigator: Shibuya Tetsuo 東京大学, 医科学研究所, 教授 (60396893)
• Project Period (FY): 2017-04-01 – 2021-03-31
• Project Status: Completed (Fiscal Year 2020)
• Budget Amount: ¥11,570,000 (Direct Cost: ¥8,900,000、Indirect Cost: ¥2,670,000); Fiscal Year 2020: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000); Fiscal Year 2019: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000); Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000); Fiscal Year 2017: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
• Keywords: アルゴリズム理論 / アルゴリズム / バイオインフォマティクス / ビッグデータ / 次世代シークエンサー / 差分プライバシー / 秘匿検索 / 検索技術 / ビッグクエリー / SMAD / ＳＭＡＤ

Outline of Final Research Achievements

A new technology for searching big data is desired. SMAD (Statistical Model-based Algorithm Design) is a candidate for improving these searching algorithms. In this research, we explored applications of SMAD technology to big query/big data searching problems. In particular, we developed new searching technologies for individual genome databases, protein 3-D databases, and natural language text databases. Moreover we succeeded in developing technologies for privacy preserving, memory distribution for PCM memories, and next generation sequencer read analysis.

Academic Significance and Societal Importance of the Research Achievements

近年のデータ爆発は、大規模ビッグデータに対する大規模なクエリーを著しく困難にしており、それに対する超効率な検索基盤技術の開発が求められている。本研究では、SMAD技術を核に、ゲノムデータベース、タンパク質立体構造データベース、自然言語テキストデータベースなど様々なデータベースに対する検索技術の開発に成功したほか、プライバシー保護、PCMメモリの活用、次世代シークエンサー解析など、様々なデータ解析の基盤技術の高度化にも貢献することに成功している。これらの技術によって、今後さらにビッグデータの利活用が高度化されることが期待できる。

Research Products

• [Journal Article] Transfer Learning for Biomedical Question Answering (2020)
  • Author(s): Arda Akdemir, Tetsuo Shibuya
  • Journal Title: Proc. CLEF 2020, CEUR Workshop Proceedings Volume: 2696(66) Pages: 1-15
  • Peer Reviewed / Open Access
• [Journal Article] Wear Leveling Revisited (2020)
  • Author(s): Taku Onodera, Tetsuo Shibuya
  • Journal Title: Leibniz International Proceedings in Informatics (LIPIcs) Volume: 181(65) Pages: 1-17
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] Subword Contextual Embeddings for Languages with Rich Morphology (2020)
  • Author(s): Arda Akdemir, Tetsuo Shibuya, Tunga Gungor
  • Journal Title: Proc. ICMLA 2020 Volume: 1 Pages: 994-1001
  • DOI: 10.1109/icmla51294.2020.00161
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Nanopore base-calling from a perspective of instance segmentation (2020)
  • Author(s): Zhang Y-Z, Akdemir A, Tremmel G, Imoto S, Miyano S, Shibuya T, Yamaguchi R.
  • Journal Title: BMC Bioinformatics Volume: 23;21(Suppl 3) Issue: S3 Pages: 136-136
  • DOI: 10.1186/s12859-020-3459-0
  • Peer Reviewed / Open Access
• [Journal Article] FOREWORD (2019)
  • Author(s): Yoichi Sasaki, Tetsuo Shibuya, Kimihito Ito, and Hiroki Arimura
  • Journal Title: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences Volume: E102.A Issue: 9 Pages: 986-986
  • DOI: 10.1587/transfun.E102.A.986
  • NAID: 130007699535
  • ISSN: 0916-8508, 1745-1337
  • Year and Date: 2019-09-01
  • Peer Reviewed
• [Journal Article] Application-Oriented Succinct Data Structures for Big Data, The Review of Socionetwork Strategies (2019)
  • Author(s): Tetsuo Shibuya
  • Journal Title: The Review of Socionetwork Strategies Volume: 13 Issue: 2 Pages: 227-236
  • DOI: 10.1007/s12626-019-00045-1
  • Peer Reviewed / Open Access
• [Journal Article] Succinct Oblivious RAM (2018)
  • Author(s): Taku Onodera, Tetsuo Shibuya
  • Journal Title: Proc. STACS Volume: 96
  • DOI: 10.4230/LIPIcs.STACS.2018.52
  • Peer Reviewed / Open Access
• [Journal Article] Revealing phenotype-associated functional differences by genome-wide scan of ancient haplotype blocks (2017)
  • Author(s): Onuki Ritsuko、Yamaguchi Rui、Shibuya Tetsuo、Kanehisa Minoru、Goto Susumu
  • Journal Title: PLOS ONE Volume: 12 Issue: 4 Pages: 0176530-0176530
  • DOI: 10.1371/journal.pone.0176530
  • NAID: 120006309307
  • Peer Reviewed / Open Access
• [Presentation] Algorithmic Challenges for Biomedical Big Data (2021)
  • Author(s): Tetsuo Shibuya
  • Organizer: The 11th International Conference on Bioscience, Biochemistry and Bioinformatics
  • Int'l Joint Research / Invited
• [Presentation] スパコンシステム「SHIROKANE」とゲノム医療 (2020)
  • Author(s): 渋谷哲朗
  • Organizer: 第9回生命医薬情報連合大会
  • Invited
• [Presentation] Nanopore base-calling from a perspective of instance segmentation (2019)
  • Author(s): Yao-zhong Zhang, Arda Akdemir, Georg Tremmel, Seiya Imoto, Satoru Miyano, Tetsuo Shibuya, Rui Yamaguchi
  • Organizer: ISMB-ECCB 2019
  • Int'l Joint Research
• [Presentation] 重み付き有向非巡回グラフに対する効率良いテキスト索引の構築アルゴリズム (2018)
  • Author(s): 山岸大騎，髙木拓也，渋谷哲朗，有村博紀．
  • Organizer: 第17回情報科学技術フォーラム
• [Presentation] 簡潔Oblivious RAM (2018)
  • Author(s): 小野寺拓，渋谷哲朗
  • Organizer: 電子情報通信学会 情報セキュリティ研究会