| Budget Amount *help |
¥101,920,000 (Direct Cost: ¥78,400,000、Indirect Cost: ¥23,520,000)
Fiscal Year 2021: ¥20,020,000 (Direct Cost: ¥15,400,000、Indirect Cost: ¥4,620,000)
Fiscal Year 2020: ¥20,020,000 (Direct Cost: ¥15,400,000、Indirect Cost: ¥4,620,000)
Fiscal Year 2019: ¥20,020,000 (Direct Cost: ¥15,400,000、Indirect Cost: ¥4,620,000)
Fiscal Year 2018: ¥20,020,000 (Direct Cost: ¥15,400,000、Indirect Cost: ¥4,620,000)
Fiscal Year 2017: ¥21,840,000 (Direct Cost: ¥16,800,000、Indirect Cost: ¥5,040,000)
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| Outline of Final Research Achievements |
To capture the whole picture and behavior leading to diseases by metabolic adaptation, it is necessary to integrate multi-omics data across the omics layers. In this study, we arranged trans-omics statistical analysis methods based on knowledge-based, causal-hierarchical, and integrated methods, and analyzed omics data to decipher trans-omics and systematically and comprehensively clarify changes in metabolic states in diseases and living organisms. As a result, we derived a new original methodology based on deep learning and conducted trans-omics analysis of diabetes, Alzheimer's disease, cancer immunity and tumor-microenvironment using clinical samples and model animals to discover novel genes, pathways, interactions, new sub-classes and their underlying mechanisms across humans and mice.
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