| Technical Name | Deep learning approach for predicting aging-associated genes | ||
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| Project Operator | National Central University | ||
| Project Host | 王家慶 | ||
| Summary | The co-expression genes are found in the blood tissue as the key factors for aging detection. In the future, blood tests can be used to assess the aging level of vital organs in the body. This study will further apply to the development of anti-aging medicine and evaluation of humans aging. |
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| Scientific Breakthrough | We found the important gene sets of aging for many important organs in the body. Furthermore, we integrated into gene sets with co-expression analysis in the blood. In the future, we only need to blood samples for evaluation aging level of the lung, brain, heart, and liver tissues. |
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| Industrial Applicability | The phenomenon of human aging is a process of accumulating time. It is necessary to confirm the aging effect of drugs in clinical trials for a long time. Therefore, the development of biomarkers that effectively and objectively measure the degree of human aging will be used for anti-aging drug development and physical examination. Aging assessment can achieve the effect of preventive medicine |
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| Keyword | deep learning gene sequencing aging artificial intelligence gene marker brain blood lung liver heart | ||
- syicncu@g.ncu.edu.tw
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