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| Edwin Wang. |
| In the past few years, many high-throughput techniques have been developed and applied to biological studies. These techniques such as “next generation” genome sequencing, chip-on-chip, microarray and so on can be used to measure gene expression and gene regulatory elements in a genome-wide scale. Moreover, as these technologies become more affordable and accessible, they have become a driving force in modern biology. As a result, huge amount biological data have been produced, with the expectation of increasing number of such datasets to be generated in the future. High-throughput data are more comprehensive and unbiased, but ‘real signals’ or biological insights, molecular mechanisms and biological principles... |
| Tipo: Manuscript |
Palavras-chave: Cancer; Genetics & Genomics; Bioinformatics. |
| Ano: 2008 |
URL: http://precedings.nature.com/documents/2737/version/1 |
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| Edwin Wang. |
| We conducted a comprehensive analysis of a manually curated human signaling network containing 1634 nodes and 5089 signaling regulatory relations by integrating cancer-associated genetically and epigenetically altered genes. We find that cancer mutating genes are enriched in positive signaling regulatory loops, whereas the cancer-associated methylating genes are enriched in negative signaling regulatory loops. We further characterized an overall picture of the cancer-signaling architectural and functional organization. From the network, we extracted an oncogene-signaling map, which contains 326 nodes, 892 links and the interconnections of mutated and methylated genes. The map can be decomposed into 12 topological regions or oncogene-signaling blocks,... |
| Tipo: Presentation |
Palavras-chave: Cancer; Genetics & Genomics; Bioinformatics. |
| Ano: 2008 |
URL: http://precedings.nature.com/documents/2238/version/1 |
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