An Age dynamic network for human phenotypes and disease prevalence
碩士 === 國立中央大學 === 生物資訊與系統生物研究所 === 97 === Social networks have been investigated on genetic, proteomic, and metabolic fields as a viable path toward elucidating the origins of specific diseases. Here we use epidemiology view to summarizing correlations obtained from hospital dataset in an age dynami...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2009
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/41604361447045141704 |
| Summary: | 碩士 === 國立中央大學 === 生物資訊與系統生物研究所 === 97 === Social networks have been investigated on genetic, proteomic, and metabolic fields as a viable path toward elucidating the origins of specific diseases. Here we use epidemiology view to summarizing correlations obtained from hospital dataset in an age dynamic phenotypic disease network (ADPDN). We show the evidence that the progression of disease connect by the links of the network is different for patients according to age and genders. Our study show that human phenotypes and disease prevalence can be demonstrated and by using network analysis, facilitating the potential to enhance our understanding of the origin and evolution of human diseases.
|
|---|