2015
DOI: 10.1093/jmcb/mjv025
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Diagnosing phenotypes of single-sample individuals by edge biomarkers

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Cited by 67 publications
(59 citation statements)
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“…Biological network information includes only a small number of genes; 20,000~40,000 transcripts are generally observed in the whole transcriptome data but only ~10,000 genes are used in the interaction data. There could be another approaches with de novo network construction with edge probability using statistical approaches8485. As more comprehensive interaction data, including regulatory data, is available, our method can be more accurate in predicting ITH.…”
Section: Discussionmentioning
confidence: 99%
“…Biological network information includes only a small number of genes; 20,000~40,000 transcripts are generally observed in the whole transcriptome data but only ~10,000 genes are used in the interaction data. There could be another approaches with de novo network construction with edge probability using statistical approaches8485. As more comprehensive interaction data, including regulatory data, is available, our method can be more accurate in predicting ITH.…”
Section: Discussionmentioning
confidence: 99%
“…To determine a person's state of health, many studies have shown that network-based biomarkers, e.g. subnetwork markers (5,6), network biomarkers (8) and edge biomarkers (9,10), are superior to traditional single-molecule biomarkers for accurately characterizing disease states due to their additional information on interactions and networks. In particular, an individual-specific network is considered to be reliable for accurately characterizing the specific disease state of an individual.…”
Section: Introductionmentioning
confidence: 99%
“…In this study, our method was applied to select a panel of biomarkers to improve the diagnosis of CRC. In future we will apply our method to other cancer analysis by further considering dynamical information for dynamical network biomarkers [49][50][51][52][53]69] and network information for network biomarkers [54][55][56][57][58][59] or edge biomarkers [64][65].…”
Section: Discussionmentioning
confidence: 99%