2019 Fiscal Year Final Research Report
Development of gene-function prediction models with highly predictive and sustainable construction by integrated network analysis
| Project/Area Number |
17K07663
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Horticultural science
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| Research Institution | Institute of Physical and Chemical Research |
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Principal Investigator |
Fukushima Atsushi 国立研究開発法人理化学研究所, 環境資源科学研究センター, 研究員 (80415281)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Keywords | バイオインフォマティクス / 園芸ゲノム科学 |
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| Outline of Final Research Achievements |
This study tried to integrate existing knowledge related to gene functions and correlation-based biomolecular networks using different types of omics data for deeper understanding a genotype-environment interaction in physiological events of plants. The results include (i) advanced development of gene-function prediction methods with high predictive accuracy by integrating omics data and (ii) evaluation of correlation networks constructed by Pearson correlation coefficient and information-theoretic inference methods. We developed the method to quantify and predict gene-gene functional links. By using the developed method, we performed differential regulation analysis (DRA) to predict candidate regulators based on differential co-expression data.
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| Free Research Field |
植物システム生物学
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| Academic Significance and Societal Importance of the Research Achievements |
断続的に産出されるオミックスデータに対応し、遺伝子機能予測モデルの構築を“持続的に”行うことができる統計モデルは、利用可能なオミックスデータが増えるに従って、予測精度の改善が見込まれる。このため、持続的にその構築を行うソフトウェア実装が重要となる。植物の持つ環境応答の頑健さと柔軟さとを理解するため、生理機能の背後にある遺伝子ネットワークの特性解明に大きく寄与する。本研究課題の遺伝子機能予測モデルおよび解析手法は、将来的に総合的な「環境適応型植物設計システム」の重要なモジュールの一つとなりうる(新技術の創製)。
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