MALDI-TOF MS Data Processing Using Wavelets, Splines and Clustering Techniques.

<p>Mass Spectrometry, especially matrix assisted laser desorption/ionization (MALDI) time of flight (TOF), is emerging as a leading technique in the proteomics revolution. It can be used to find disease-related protein patterns in mixtures of proteins derived from easily obtained samples. In this paper, a novel algorithm for MALDI-TOF MS data processing is developed. The software design includes the application of splines for data smoothing and baseline correction, wavelets for adaptive denoising, multivariable statistics techniques such as clustering analysis, and signal processing techniques to evaluate the complicated biological signals. A MatLab implementation shows the processing steps consecutively including step-interval unification, adaptive wavelet denoising, baseline correction, normalization, and peak detection and alignment for biomarker discovery.</p>

Name thesis:degree_name

MS (Master of Science)

Level thesis:degree_level

Thesis - unrestricted

Discipline thesis:degree_discipline

Mathematical Sciences

Year dc:date.issued

2004

Author dc:creator

• Chen, Shuo

• clustering
• adaptive wavelet denoising
• undecimated wavelet transform
• binning
• peak processing
• splines
• MALDI-TOF
• mass spectrum.
• Physical Sciences and Mathematics

Statement dc:rights

• Copyright by the authors.

Repository record dc:identifier

https://dc.etsu.edu/etd/966

OAI identifier oai:identifier

oai:dc.etsu.edu:etd-2123