Improved candidate biomarker detection based on mass spectrometry data using the hilbert-huang transform

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题名:	Improved candidate biomarker detection based on mass spectrometry data using the hilbert-huang transform
作者:	吳立青;Wu, Li-Ching;Hsieh, Ping-Heng;Horng, Jorng-Tzong;Jou, Yu-Jen;Lin, Chia-Der;Cheng, Kuang-Fu;Lin, Cheng-Wen;Chen, Shih-Yin
贡献者:	生醫理工學院生醫科學與工程學系
关键词:	Algorithms;Antimicrobial Cationic Peptides - urine;Autoimmune Diseases - blood;Autoimmune Diseases - diagnosis;Biomarkers - metabolism;Computational Biology;Data Mining;Databases, Factual;Hepcidins;Humans;Kidney Diseases - diagnosis;Kidney Diseases - metabolism;Mouth Neoplasms - diagnosis;Mouth Neoplasms - metabolism;Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
日期:	2012-01-01
上传时间:	2026-04-23 11:16:23 (UTC+8)
出版者:	Bentham Science Publishers B.V.;Netherlands: Bentham Science Publishers Ltd
摘要:	摘要： Mass spectrometry biomarker discovery may assist patients diagnosis in time and realize the characteristics of new diseases. Our previous work built a preprocess method called HHTmass which is capable of removing noise, but HHTmass only a proof of principle to be peak detectable and did not tested for peak reappearance rate and used on medical data. We developed a modified version of biomarker discovery method called Enhance HHTMass (E-HHTMass) for MALDI-TOF and SELDI-TOF mass spectrometry data which improved old HHTMass method by removing the interpolation and the biomarker discovery process. E-HHTMass integrates the preprocessing and classification functions to identify significant peaks. The results show that most known biomarker can be found and high peak appearance rate achieved comparing to MSCAP and old HHTMass2. E-HHTMass is able to adapt to spectra with a small increasing interval. In addition, new peaks are detected which can be potential biomarker after further validation. 其他題名： PPL 出版者： Netherlands: Bentham Science Publishers Ltd 出版日期： 2012-01 出處： Protein and peptide letters, 2012-01, Vol.19 (1), p.120-129 識別號： ISSN: 0929-8665 識別號： ISSN: 1875-5305 識別號： EISSN: 1875-5305 識別號： DOI: 10.2174/092986612798472929 識別號： PMID: 21919851
显示于类别:	[生醫科學與工程學系] 期刊論文

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