Prostate cancer biomarker discovery using high performance mass spectral serum profiling

[1]  A. Jemal,et al.  Cancer Statistics, 2008 , 2008, CA: a cancer journal for clinicians.

[2]  Kevin P. Rosenblatt,et al.  A Robust Biomarker Discovery Pipeline for High-Performance Mass Spectrometry Data , 2007, J. Bioinform. Comput. Biol..

[3]  Jung Hun Oh,et al.  Biomarker Selection for Predicting Alzheimer Disease Using High-Resolution MALDI-TOF Data , 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

[4]  Animesh Nandi,et al.  Serum biomarkers for Alzheimer's disease: proteomic discovery. , 2007, Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie.

[5]  David A Bennett,et al.  High-resolution serum proteomic profiling of Alzheimer disease samples reveals disease-specific, carrier-protein-bound mass signatures. , 2005, Clinical chemistry.

[6]  P. Tempst,et al.  Correcting common errors in identifying cancer-specific serum peptide signatures. , 2005, Journal of proteome research.

[7]  Hari Nair,et al.  Controlling matrix suppression for matrix‐assisted laser desorption/ionization analysis of small molecules , 2004 .

[8]  J. Crowley,et al.  Prevalence of prostate cancer among men with a prostate-specific antigen level < or =4.0 ng per milliliter. , 2004, The New England journal of medicine.

[9]  S. Shariat,et al.  Serum BPSA outperforms both total PSA and free PSA as a predictor of prostatic enlargement in men without prostate cancer. , 2004, Urology.

[10]  E. Diamandis.  Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. , 2004, Journal of the National Cancer Institute.

[11]  Alan W Partin,et al.  PSA markers in prostate cancer detection. , 2003, The Urologic clinics of North America.

[12]  Bao-Ling Adam,et al.  Diagnostic potential of serum proteomic patterns in prostate cancer. , 2003, The Journal of urology.

[13]  J. Roboz,et al.  Putative protein markers in the sera of men with prostatic neoplasms , 2003, BJU international.

[14]  Stephen D Mikolajczyk,et al.  Pro PSA: a more cancer specific form of prostate specific antigen for the early detection of prostate cancer. , 2003, The Keio journal of medicine.

[15]  E. Petricoin,et al.  Serum proteomic patterns for detection of prostate cancer. , 2002, Journal of the National Cancer Institute.

[16]  P. Schellhammer,et al.  Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients. , 2002, Clinical chemistry.

[17]  P. Schellhammer,et al.  Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men. , 2002, Cancer research.

[18]  Vineet Bafna,et al.  SCOPE: a probabilistic model for scoring tandem mass spectra against a peptide database , 2001, ISMB.

[19]  S. Weinberger,et al.  Recent advancements in surface‐enhanced laser desorption/ionization‐time of flight‐mass spectrometry , 2000, Electrophoresis.

[20]  Peter R. Baker,et al.  Role of accurate mass measurement (+/- 10 ppm) in protein identification strategies employing MS or MS/MS and database searching. , 1999, Analytical chemistry.

[21]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[22]  Daphne Koller,et al.  Toward Optimal Feature Selection , 1996, ICML.

[23]  C G Chute,et al.  Incidence of prostate cancer diagnosis in the eras before and after serum prostate-specific antigen testing. , 1995, JAMA.

[24]  W. Catalona,et al.  Comparison of different serum prostate specific antigen measures for early prostate cancer detection , 1994, Cancer.

[25]  W. Catalona,et al.  Serial prostatic biopsies in men with persistently elevated serum prostate specific antigen values. , 1994, The Journal of urology.

[26]  Daniel Howard,et al.  Novel Algorithm for MALDI-TOF Baseline Drift Removal , 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.