2019 Fiscal Year Annual Research Report
A big data approach to function prediction of metabolites by clustering of structural similarity networks
Project/Area Number |
17K00406
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Research Institution | Nara Institute of Science and Technology |
Principal Investigator |
AMIN MD.ALTAFUL 奈良先端科学技術大学院大学, 先端科学技術研究科, 准教授 (30379531)
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Project Period (FY) |
2017-04-01 – 2020-03-31
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Keywords | Metabolomics / Metabolic Network / Metabolite Activity / Systems Biology / Network Clustering / Algorithms |
Outline of Annual Research Achievements |
We collected metabolite activity data and structural information of metabolites from KNApSAcK database and constructed the structural similarity based network of metabolites. Also we developed a network clustering tool called DPClusSBO which we applied for function prediction of metabolites. Structural similarity between metabolites implies functional similarity between them. In light of this fact we propose a method for function prediction of secondary metabolites and published a paper. Also, we have done several other works utilizing the tool DPClusSBO. Based on the research related to this project, we got several publications during last year in good journals including IEEE TRANSACTIONS ON Computational Biology and Bioinformatics, BMC medical genomics, Applied Network Science etc.
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[Book] Databases for Natural Product Research, In book: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering2020
Author(s)
Kanaya, S., Altaf-Ul-Amin, M., Aki, M. H., Huang, M., & Ono, N.
Total Pages
16
Publisher
Elsevier
ISBN
ISBN: 978-0-12-409547-2
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