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- W4240540587 abstract "Abstract 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 are buried in the flood of data. In current biological studies, the bottleneck is no longer a lack of data, but the lack of ingenuity and computational means to extract biological insights and principles by integrating knowledge and high-throughput data. Here I am reviewing the concepts and principles of network biology and the computational methods which can be applied to cancer research. Furthermore, I am providing a practical guide for computational analysis of cancer gene networks." @default.
- W4240540587 created "2022-05-12" @default.
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- W4240540587 date "2009-01-06" @default.
- W4240540587 modified "2023-09-27" @default.
- W4240540587 title "Computational methods in cancer gene networking" @default.
- W4240540587 doi "https://doi.org/10.1038/npre.2008.2737.1" @default.
- W4240540587 hasPublicationYear "2009" @default.
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