Ohtana, Yuki and Abdullah, Azian Azamimi and Altaf-Ul-Amin, Md. and Huang, Ming and Ono, Naoaki and Sato, Tetsuo and Sugiura, Tadao and Horai, Hisayuki and Nakamura, Yukiko and Hirai, Aki Morita and Lange, Klaus W. and Kibinge, Nelson K. and Katsuragi, Tetsuo and Shirai, Tsuyoshi and Kanaya, Shigehiko (2014) Clustering of 3D-Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities. MOLECULAR INFORMATICS, 33 (11-12). pp. 790-801. ISSN 1868-1743, 1868-1751
Full text not available from this repository. (Request a copy)Abstract
Developing database systems connecting diverse species based on omics is the most important theme in big data biology. To attain this purpose, we have developed KNApSAcK Family Databases, which are utilized in a number of researches in metabolomics. In the present study, we have developed a network-based approach to analyze relationships between 3D structure and biological activity of metabolites consisting of four steps as follows: construction of a network of metabolites based on structural similarity (Step 1), classification of metabolites into structure groups (Step 2), assessment of statistically significant relations between structure groups and biological activities (Step 3), and 2-dimensional clustering of the constructed data matrix based on statistically significant relations between structure groups and biological activities (Step 4). Applying this method to a data set consisting of 2072 secondary metabolites and 140 biological activities reported in KNApSAcK Metabolite Activity DB, we obtained 983 statistically significant structure group-biological activity pairs. As a whole, we systematically analyzed the relationship between 3D-chemical structures of metabolites and biological activities.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BIG; METABOLOMICS; ALGORITHM; Clustering of 3D-structure similarity; Network of secondary metabolites; Metabolites; Biological activities; KNApSAcK family databases; Phytochemistry; Structure-property relationships; Visualization, Cheminformatics; 'Bioinformatics |
| Subjects: | 100 Philosophy & psychology > 150 Psychology |
| Divisions: | Psychology and Pedagogy > Institut für Psychologie > Lehrstuhl für Psychologie III (Biologische, Klinische und Rehabilitationspsychologie) - Prof. Dr. Klaus W. Lange |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 07 Aug 2019 11:24 |
| Last Modified: | 07 Aug 2019 11:24 |
| URI: | https://pred.uni-regensburg.de/id/eprint/9131 |
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