Abstract

The Data Analysis Core is responsible for providing the investigators in this Project Grant with the capability of analyzing large datasets consisting of hundreds of spectra in efficient and reproducible ways. To this end, we will implement and automated easily used Principal Component Analysis (PCA) procedure to provide a quantitative analysis of spectral peak amplitudes as well as develop techniques to extract coherent patterns in CSI and kinetic datasets. A variety of applications are presented as preliminary results which suggest that this technique will be very effective in providing quantitative information from datasets in a very efficient way.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
2P01CA041078-10
Application #
6269208
Study Section
Project Start
1998-04-01
Project End
1999-03-31
Budget Start
1997-10-01
Budget End
1998-09-30
Support Year
10
Fiscal Year
1998
Total Cost
Indirect Cost

  Institution

Name
Fox Chase Cancer Center
Department
Type
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19111

  Publications

Lee, Seung-Cheol; Arias-Mendoza, Fernando; Poptani, Harish et al. (2012) Prediction and Early Detection of Response by NMR Spectroscopy and Imaging. PET Clin 7:119-26
Hultman, Kristi L; Raffo, Anthony J; Grzenda, Adrienne L et al. (2008) Magnetic resonance imaging of major histocompatibility class II expression in the renal medulla using immunotargeted superparamagnetic iron oxide nanoparticles. ACS Nano 2:477-84
Stoyanova, Radka; Querec, Troy D; Brown, Truman R et al. (2004) Normalization of single-channel DNA array data by principal component analysis. Bioinformatics 20:1772-84
Stoyanova, Radka; Nicholls, Andrew W; Nicholson, Jeremy K et al. (2004) Automatic alignment of individual peaks in large high-resolution spectral data sets. J Magn Reson 170:329-35
Stoyanova, Radka; Nicholson, Jeremy K; Lindon, John C et al. (2004) Sample classification based on Bayesian spectral decomposition of metabonomic NMR data sets. Anal Chem 76:3666-74
Sajda, Paul; Du, Shuyan; Brown, Truman R et al. (2004) Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain. IEEE Trans Med Imaging 23:1453-65
Nahum, Alan E; Movsas, Benjamin; Horwitz, Eric M et al. (2003) Incorporating clinical measurements of hypoxia into tumor local control modeling of prostate cancer: implications for the alpha/beta ratio. Int J Radiat Oncol Biol Phys 57:391-401
Stoyanova, R; Brown, T R (2002) NMR spectral quantitation by principal component analysis. III. A generalized procedure for determination of lineshape variations. J Magn Reson 154:163-75
Stoyanova, R; Brown, T R (2001) NMR spectral quantitation by principal component analysis. NMR Biomed 14:271-7
Ochs, M F; Stoyanova, R S; Arias-Mendoza, F et al. (1999) A new method for spectral decomposition using a bilinear Bayesian approach. J Magn Reson 137:161-76

Showing the most recent 10 out of 46 publications