Biomarker discovery on high-throughput and high-resolution mass spectrometry oral cancer data using statistical methods
碩士 === 國立中央大學 === 資訊工程研究所 === 94 === Due to the high death rate in advanced stage diseases, the diagnosis of early-stage cancer is needed for public health. Recent advances in the biotechnology of high-throughput and high-resolution MALDI-TOF mass spectrometry (MS) has made such diagnosis possible (...
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| Format: | Others |
| Language: | en_US |
| Published: |
2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/56cbf4 |
| Summary: | 碩士 === 國立中央大學 === 資訊工程研究所 === 94 === Due to the high death rate in advanced stage diseases, the diagnosis of early-stage cancer is needed for public health. Recent advances in the biotechnology of high-throughput and high-resolution MALDI-TOF mass spectrometry (MS) has made such diagnosis possible (Petricoin and Liotta 2003). From then on, high-resolution mass spectrometers are increasingly used for disease classification and therapeutic guidance. Due to instrument resolution and/or instrument calibration, the mass spectrometry (MS) data may be poor in quality. The problem makes it difficult and time consuming to trace each spectrum with thousands of features for biomarkers. We proposed a region-based alignment method to deal with peak shifting problem and applied statistical method to select most discriminatory peaks as biomarker candidates. Finally, we test our methodology on the oral cancer dataset from CHANG GUNG UNIVERSITY in Taiwan.
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