Abstract
A crucial work of investigating the mechanisms of cancer development is to unraveling the dynamic nature of gene regulation during the disease process. However, reconstruction of dynamic gene regulatory network requires time-sequence samples of a biological process, which are not available for many bio-medical problems. In this paper, we propose a dynamic cascaded method to reconstruct dynamic gene networks from sample-based transcriptional data. Our method is based on two biologically plausible assumptions, which can characterise the dynamic and continuous nature of gene transcription. Our approach was successfully applied to reconstruct the dynamic gene networks of hepatocellular carcinoma (HCC) progression. The derived HCC networks were verified by functional analysis and network enrichment analysis.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 |
| Pages | 159-165 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2012 |
| Event | 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 - Philadelphia, PA, United States Duration: 4 Oct 2012 → 7 Oct 2012 |
Publication series
| Name | Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 |
|---|
Conference
| Conference | 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012 |
|---|---|
| Country/Territory | United States |
| City | Philadelphia, PA |
| Period | 4/10/12 → 7/10/12 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
User-Defined Keywords
- dynamic network
- Gene regulatory network
- Herpatocellulur Carcinoma
- sample-based transcriptional data
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