Ching-Min Huang

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Recently, cluster computing has successfully provided a cost-effective solution for data-intensive applications. In order to make the programming on clusters easy, many programming toolkits such as MPICH, PVM, and DSM have been proposed in past researches. However, these programming toolkits are not easy enough for common users to develop parallel(More)
We reported an integrated platform to explore serum protein variant pattern in cancer and its utility as a new class of biomarker panel for diagnosis. On the model study of serum amyloid A (SAA), we employed nanoprobe-based affinity mass spectrometry for enrichment, identification and quantitation of SAA variants from serum of 105 gastric cancer patients in(More)
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