The Experts below are selected from a list of 417 Experts worldwide ranked by ideXlab platform
Weida Tong - One of the best experts on this subject based on the ideXlab platform.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS).
BMC bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS)
BMC Bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Background Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. Results The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. Conclusion This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.
Richard A Mathies - One of the best experts on this subject based on the ideXlab platform.
-
Integrated microfluidic Bioprocessor for solid phase capture immunoassays
Lab on a chip, 2011Co-Authors: Jungkyu Kim, Erik C. Jensen, Mischa Megens, Bernhard E. Boser, Richard A MathiesAbstract:A microfluidic device for solid-phase immunoassays based on microparticle labeling is developed using microvalve-control structures for automated sample processing. Programmable microvalve control in a multilayer structure provides automated sample delivery, adjustable hydrodynamic washing and compatibility with a wide range of substrates. Capture antibodies are derivatized on glass surfaces within the processor using an APTES patterning method, and magnetic microspheres conjugated with a secondary detection antibody are used as labels in a capture-sandwich format. In this microfluidic processor, washing force can be precisely controlled to remove the nonspecifically bound microparticles. Automated microfluidic immunoassays are demonstrated for mouse immunoglobulin (IgG) and human prostate specific antigen (PSA) with limits of detection of 1.8 and 3 pM, respectively. The sample processor architecture is easily parallelized for high-throughput analysis and easily interfaced with various assay substrates.
-
integrated microfluidic Bioprocessor for single cell gene expression analysis
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Nicholas Toriello, Erik S Douglas, Numrin Thaitrong, Sonny C Hsiao, Matthew B Francis, Carolyn R Bertozzi, Richard A MathiesAbstract:An integrated microdevice is developed for the analysis of gene expression in single cells. The system captures a single cell, transcribes and amplifies the mRNA, and quantitatively analyzes the products of interest. The key components of the microdevice include integrated nanoliter metering pumps, a 200-nL RT-PCR reactor with a single-cell capture pad, and an affinity capture matrix for the purification and concentration of products that is coupled to a microfabricated capillary electrophoresis separation channel for product analysis. Efficient microchip integration of these processes enables the sensitive and quantitative examination of gene expression variation at the single-cell level. This microdevice is used to measure siRNA knockdown of the GAPDH gene in individual Jurkat cells. Single-cell measurements suggests the presence of 2 distinct populations of cells with moderate (≈50%) or complete (≈0%) silencing. This stochastic variation in gene expression and silencing within single cells is masked by conventional bulk measurements.
-
microfabricated Bioprocessor for integrated nanoliter scale sanger dna sequencing
Proceedings of the National Academy of Sciences of the United States of America, 2006Co-Authors: Robert G Blazej, Palani Kumaresan, Richard A MathiesAbstract:An efficient, nanoliter-scale microfabricated Bioprocessor integrating all three Sanger sequencing steps, thermal cycling, sample purification, and capillary electrophoresis, has been developed and evaluated. Hybrid glass–polydimethylsiloxane (PDMS) wafer-scale construction is used to combine 250-nl reactors, affinity-capture purification chambers, high-performance capillary electrophoresis channels, and pneumatic valves and pumps onto a single microfabricated device. Lab-on-a-chip-level integration enables complete Sanger sequencing from only 1 fmol of DNA template. Up to 556 continuous bases were sequenced with 99% accuracy, demonstrating read lengths required for de novo sequencing of human and other complex genomes. The performance of this miniaturized DNA sequencer provides a benchmark for predicting the ultimate cost and efficiency limits of Sanger sequencing.
-
Microchip Bioprocessor for Integrated Nanovolume Sample Purification and DNA Sequencing
Analytical chemistry, 2002Co-Authors: Brian M Paegel, And Stephanie H. I. Yeung, Richard A MathiesAbstract:A microfabricated electrophoretic Bioprocessor for integrated DNA sequencing sample desalting, template removal, preconcentration, and CE analysis is presented. A low-viscosity gel capture matrix, containing an acrylamide−copolymerized oligonucleotide complementary to the 20-base sequence directly 3‘ of the M13−40 universal forward priming site, is introduced into the 60-nL capture chamber. Unpurified DNA sequencing reaction products are electrophoretically driven through the chamber; extension products hybridize to the matrix, while contaminating buffering ions, Cl-, excess primer, and template DNA are unretained. Purification under optimized conditions is complete in only 120 s (binding temperature 50 °C, driving voltage 250 V). High-speed, integrated sequencing analysis is accomplished by releasing the gel-purified duplex at 67 °C and directly injecting onto a 15.9-cm effective length CE microchannel. Electrophoretic resolution of the sequencing products is complete in 32 min, producing a total of 560 ...
-
High throughput DNA sequencing with a microfabricated 96-lane capillary array electrophoresis Bioprocessor
Proceedings of the National Academy of Sciences, 2002Co-Authors: G. J. Wedemayer, J. R. Scherer, Charles A Emrich, Richard A Mathies, Brian M PaegelAbstract:High throughput DNA sequencing has been performed by using a microfabricated 96-channel radial capillary array electrophoresis (microCAE) microchannel plate detected by a 4-color rotary confocal fluorescence scanner. The microchannel plate features a novel injector for uniform sieving matrix loading as well as high resolution, tapered turns that provide an effective separation length of 15.9 cm on a compact 150-mm diameter wafer. Expanded common buffer chambers for the cathode, anode, and waste reservoirs are used to simplify electrode addressing and to counteract buffering capacity depletion arising from the high electrophoretic current. DNA sequencing data from 95 successful lanes out of 96 lanes run in parallel were batch-processed with basefinder, producing an average read length of 430 bp (phred q > or = 20). Phred quality values were found to exceed 40 (0.01% probability of incorrectly calling a base) for over 80% of the read length. The microCAE system demonstrated here produces sequencing data at a rate of 1.7 kbp/min, a 5-fold increase over current commercial capillary array electrophoresis technology. Additionally, this system permits lower reagent volumes and lower sample concentrations, and it presents numerous possibilities for integrated sample preparation and handling. The unique capabilities of microCAE technology should make it the next generation, high performance DNA sequencing platform.
Huixiao Hong - One of the best experts on this subject based on the ideXlab platform.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS).
BMC bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS)
BMC Bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Background Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. Results The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. Conclusion This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.
Bangzheng Chen - One of the best experts on this subject based on the ideXlab platform.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS).
BMC bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS)
BMC Bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Background Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. Results The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. Conclusion This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.
-
Biomarkers of Myeloma-Associated Lytic Bone Disease Using SELDI-TOF MS.
Blood, 2004Co-Authors: Bangzheng Chen, Hong Huixiao, Tong Weida, Walker Ronald, Barlogie Bart, Epstein JoshuaAbstract:MGUS is a pre-malignant state, with a 1% annual risk of progression to overt myeloma (Kyle, NEJM346:564, 2004). Progression of MGUS to myeloma is preceded and can be predicted by increased rates of bone turnover (Betaille, JCI88:62, 1991). Progress to overt myeloma is associated with lytic bone disease in about 80% of patients. A simple, reliable test that identifies MGUS patients at risk of progression to symptomatic myeloma would elucidate biological mechanisms that govern the process and identify targets for early intervention. The intimate association of progression with changes in bone biology suggested that early recognition of changes in bone turnover would serve such a purpose. Therefore, we sought to identify protein biomarkers of bone disease in the sera of patients with myeloma that can be used as early predictors of progression. Given the limited reliability of individual markers of bone turnover to identify changes in bone metabolism, we elected to adopt a global proteomics approach. Sera from 62 untreated myeloma patients were collected and stored at −80°C for future analysis. 35 serum samples were from myeloma patients with 1–26 lytic bone lesions as identified on X-ray skeletal surveys and 27 serum samples were from patients without lytic lesions. The sera were analyzed by surface-enhanced laser desorption and ionization-time of flight mass spectroscopy (SELDI-TOF MS) using Ciphergen’s ProteinChip Biology System II (PBS II), to identify protein patterns associated with lytic bone disease. Each sample was applied in 4 replicates to randomly assigned spots on 12 IMAC30 ProteinChips placed in a Bioprocessor and activated with Cu++ ions using a Biomek2000 robot. The chips were read on a PBS II reader. The mass spectra of proteins, generated using an average of 66 laser shots, were calibrated using peptide and protein standards and normalized to total ion current using CiphergenExpress 2.0 software. To develop a classification model that separates non-treated patients with focal lesions from those without focal lesions, we identified among the low molecular weight (1500–25000 kDa) proteins a set of 17 protein peaks that were differentially expressed between the two groups at a significance level of p
Roger Perkins - One of the best experts on this subject based on the ideXlab platform.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS).
BMC bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.
-
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS)
BMC Bioinformatics, 2005Co-Authors: Huixiao Hong, Yvonne Dragan, Joshua Epstein, Candee Teitel, Bangzheng Chen, Qian Xie, Hong Fang, Leming Shi, Roger Perkins, Weida TongAbstract:Background Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. Results The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six Bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. Conclusion This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.