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2011 Fiscal Year Final Research Report

Prediction of Glycan Interacting Structur e using GlycanSample Interaction Database

Research Project

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Project/Area Number 22650060
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeSingle-year Grants
Research Field Bioinformatics/Life informatics
Research InstitutionTokyo Institute of Technology (2011)
Ochanomizu University (2010)

Principal Investigator

SESE Jun  東京工業大学, 大学院・情報理工学研究科, 准教授 (40361539)

Project Period (FY) 2010 – 2011
Keywords機械学習 / クラスタリング / クラス分類 / 糖鎖
Research Abstract

Although most glycan research has focused on a few interactions between glycans and samples, recent technology has made it possible to observe many glycan-sample interactions at once. Consortium for Functional Glycomics(CFG) has collected data and compiled a database that contains glycan-sample interactions for more than three thousand samples. The large CFG database gives us "birds-eye view" of glycan interactions and the data from this database can be used to generate new hypothesis about interactions between glycans and samples or provide new rules about protein binding sites on glycans. In this work, we investigated the best combination of clustering technique and distance metrics for analyzing the large CFG datasets. We then developed an algorithm to extract glycan sub-structure which interacts target sample by combining the CFG data and glycan structure. The analysis results infer substructures interacting with influenza or galectin.

  • Research Products

    (2 results)

All Other

All Journal Article (2 results)

  • [Journal Article] Data Analys is of Large Scale Glyc an Sample Int eracti on

    • Author(s)
      Jun Sese
    • Journal Title

      Trends i n Glycosci ence and Glyc otechnology

      Volume: (in press)

  • [Journal Article] クラスタリングによる糖鎖認識パターン解析

    • Author(s)
      伊藤真和吏, 寺井はるな, 瀬々潤
    • Journal Title

      DBSJ Jo urnal

      Volume: Vol.2 0109 Pages: 59-63

URL: 

Published: 2013-07-31  

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