Abstract
Prostate cancer is one of the most lethal malignancies worldwide, owing to the lack of precise markers for early diagnosis. Researchers are now routinely identifying biomarkers for prostate cancer using whole-genome expression profiling along with proteomic technologies. Although there has been some success in this field, many efforts have been complicated by the fact that individual markers are highly divergent. Prostate cancer is a systems biology disease that results from the accumulated mutations acting in concert. Hence the individual markers would fail to capture the heterogeneity of carcinogenesis. As molecular interaction networks become available for human, network-level biomarker evolves as a promising methodology that can address this challenge. In this chapter we first describe some foundations of network analysis, and then introduce the recent progress in network biomarker discovery for diagnosis and prognosis of human prostate cancer.
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Chen, J., Shen, B. (2013). Network Biomarkers for Diagnosis and Prognosis of Human Prostate Cancer. In: Shen, B. (eds) Bioinformatics for Diagnosis, Prognosis and Treatment of Complex Diseases. Translational Bioinformatics, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7975-4_11
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DOI: https://doi.org/10.1007/978-94-007-7975-4_11
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