Functional Data Analysis

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Microproteomics: Analysis of protein diversity in small samples (with Howard B. Gutstein, Suresh P. Annangudi, and Jonathan V. Sweedler), Mass Spectrometry Reviews (2008)
Proteomics, the large-scale study of protein expression in organisms, offers the potential to evaluate global...
 

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Pinnacle: A Fast, Automatic Method for Detecting and Quantifying Protein Spots in 2-Dimensional Gel Electrophoresis Data (with Brittain C. Walla and Howard B. Gutstein), Bioinformatics (2008)

Motivation: One of the key limitations for proteomic studies using 2-dimensional gel electrophoresis (2DE) is...

 

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Statistical Issues in Proteomic Research, Bulletin of the International Society for Bayesian Analysis (2007)
 

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Bayesian Analysis of Mass Spectrometry Proteomics Data using Wavelet Based Functional Mixed Models (with Philip J. Brown, Richard C. Herrick, Keith A. Baggerly, and Kevin R. Coombes), Biometrics (2007)
In this paper, we analyze MALDI-TOF mass spectrometry proteomics data using Bayesian wavelet-based functional mixed...
 

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Wavelet-Based Functional Mixed Models to characterize Population Heterogeneity in Accelerometer Profiles: A Case Study. (with Cassandra Arroyo, Brent A. Coull, Louise M. Ryan, and Steven L. Gortmaker), Journal of the American Statstical Association (2006)
We present a case study illustrating the challenges of analyzing accelerometer data taken from a...
 

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Wavelet-based functional mixed model analysis: Computational considerations (with Richard C. Herrick), Proceedings, Joint Statistical Meetings, ASA Section on Statistical Computing (2006)
Wavelet-based Functional Mixed Models is a new Bayesian method extending mixed models to irregular functional...
 

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Wavelet-Based Functional Mixed Models (with Raymond J. Carroll), Journal of the Royal Statistical Society, Series B (2006)
Increasingly, Increasingly, scientific studies yield functional data, in which the ideal units of observation are...
 

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Analysis of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models (with Philip J. Brown, Keith A. Baggerly, and Kevin R. Coombes), Bayesian Inference for Gene Expression and Proteomics (2006)
In this chapter, we demonstrate how to analyze MALDI-TOF/SELDITOF mass spectrometry data using the wavelet-based...
 

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Bayesian Mixture Models for Gene Expression and Protein Profiles (with Michele Guindani, Kim-Anh Do, and Peter Mueller), Bayesian Inference for Gene Expression and Proteomics (2006)
We review the use of semi-parametric mixture models for Bayesian inference in high throughput genomic...
 

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Improved Peak Detection and Quantification of Mass Spectrometry Data Acquired from Surface-Enhanced Laser Desorption and Ionization by Denoising Spectra with the Undecimated Discrete Wavelet Transform (with Kevin R. Coombes, Spiros Tsavachidis, Keith A. Baggerly, and Henry M. Kuerer), Proteomics (2005)

Background: Mass spectrometry, especially surface enhanced laser desorption and ionization (SELDI) is increasingly being used...

 

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Feature Extraction and Quantification for Mass Spectrometry Data in Biomedical Applications Using the Mean Spectrum. (with Kevin R. Coombes, John Koomen, Keith A. Baggerly, and Ryuji Kobayashi), Bioinformatics (2005)

Motivation: Mass spectrometry yields complex functional data for which the features of scientific interest are...

 

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Quality Control and Peak Finding for Proteomics Data Collected from Nipple Aspirate Fluid Using Surface Enhanced Laser Desorption and Ionization. (with Kevin R. Coombes, Herbert A. Fritsche, Charlotte Clarke, Jeng-Neng Chen, Keith A. Baggerly, Lian-Chun Xiao, Mien-Chie Hung, and Henry M. Kuerer), Clinical Chemistry (2003)

Background: Recently, researchers have been using mass spectroscopy to study cancer. For use of proteomics...

 

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Rejoinder to "“Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis.” (with Marina Vannucci, Philip J. Brown, and Raymond J. Carroll), Journal oftthe American Statistical Association (2003)
 

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Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis. (with Marina Vannucci, Philip J. Brown, and Raymond J. Carroll), Journal of the American Statistical Association (2003)
In this article we develop new methods for analyzing the data from an experiment using...
 

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A Bayesian Analysis Involving Colonic Crypt Structure and Coordinated Response to Carcinogens Incorporating Missing Crypts (with Naisyin Wang, Joanne R. Lupton, Robert S. Chapkin, Nancy D. Turner, Mee-Young Hong, and Raymond J. Carroll), Biostatistics (2002)
This paper is concerned with modeling the architecture of colonic crypts and the implications of...
 

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Parametric and Nonparametric Methods for Understanding the Relationship Between Carcinogen-Induced DNA Adduct Levels in Distal and Proximal Regions of the Colon. (with Naisyin Wang, Joanne R. Lupton, Robert S. Chapkin, Nancy D. Turner, Mee-Young Hong, and Raymond J. Carroll), Journal of the American Statistical Association (2001)
An important problem in studying the etiology of colon cancer is understanding the relationship between...
 

Genomics

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Alternative Probeset Definitions for Combining Microarray Data Across Studies Using Different Versions of Affymetrix Oligonucleotide Arrays (with Chunlei Wu, Kevin R. Coombes, Keith A. Baggerly, Jing Wang, and Li Zhang), Meta-Analysis in Genetics (2006)

Many published microarray studies have small to moderate sample sizes, and thus have low statistical...

 

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Some Statistical Issues in Microarray Gene Expression Data (with Matthew S. Mayo and Byron J. Gajewski), Radiation Research (2006)
In this paper we discuss some of the statistical issues that should be considered when...
 

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An Introduction to High-Throughput Bioinformatics Data (with Keith A. Baggerly and Kevin R. Coombes), Bayesian Inference in Gene Expression and Proteomics (2006)
High throughput biological assays supply thousands of measurements per sample, and the sheer amount of...
 

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Bayesian Mixture Models for Gene Expression and Protein Profiles (with Michele Guindani, Kim-Anh Do, and Peter Mueller), Bayesian Inference for Gene Expression and Proteomics (2006)
We review the use of semi-parametric mixture models for Bayesian inference in high throughput genomic...
 

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Shrinkage Estimation for SAGE Data using a Mixture Dirichlet Prior (with Keith A. Baggerly and Kevin R. Coombes), Bayesian Inferene for Gene Expression and Proteomics (2006)
Serial Analysis of Gene Expression (SAGE) is a technique for estimating the gene expression profile...
 

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Pooling Information Across Different Studies and Oligonucleotide Microarray Chip Types to Identify Prognostic Genes for Lung Cancer. (with Guosheng Yin, Keith A. Baggerly, Chunlei Wu, and Li Zhang), Methods of Microarray Data Analysis IV (2005)
Our goal in this work is to pool information across microarray studies conducted at different...
 

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The Importance of Experimental Design in Proteomic Mass Spectrometry Experiments: Some Cautionary Tales (with Jianhua Hu, Kevin R. Coombes, and Keith A. Baggerly), Briefings in Genomics and Proteomics (2005)
Proteomic expression patterns derived from mass spectrometry have been put forward as potential biomarkers for...
 

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Overdispersed logistic regression for SAGE: Modelling multiple groups and covariates (with Keith A. Baggerly, Li Deng, and C. Marcelo Aldaz), BMC Bioninformatics (2004)
Background: Two major identifiable sources of variation in data derived from the Serial Analysis of...
 

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Differential Expression in SAGE: accounting for normal between-library variation (with Keith A. Baggerly, Li Deng, and C. Marcelo Aldez), Bioinformatics (2003)

Motivation: In contrasting levels of gene expression between groups of SAGE libraries, the libraries within...

 

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Bayesian Shrinkage Estimation of the Relative Abundance of mRNA Transcripts using SAGE (with Keith A. Baggerly and Kevin R. Coombes), Biometrics (2003)
Serial analysis of gene expression (SAGE) is a technology for quantifying gene expression in biological...
 

Proteomics

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Microproteomics: Analysis of protein diversity in small samples (with Howard B. Gutstein, Suresh P. Annangudi, and Jonathan V. Sweedler), Mass Spectrometry Reviews (2008)
Proteomics, the large-scale study of protein expression in organisms, offers the potential to evaluate global...
 

Link

Pinnacle: A Fast, Automatic Method for Detecting and Quantifying Protein Spots in 2-Dimensional Gel Electrophoresis Data (with Brittain C. Walla and Howard B. Gutstein), Bioinformatics (2008)

Motivation: One of the key limitations for proteomic studies using 2-dimensional gel electrophoresis (2DE) is...

 

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Statistical Issues in Proteomic Research, Bulletin of the International Society for Bayesian Analysis (2007)
 

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Statistical contributions to proteomic research (with Keith A. Baggerly, Howard B. Gutstein, and Kevin R. Coombes), The Urine Proteome (2007)
Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases....
 

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Bayesian Analysis of Mass Spectrometry Proteomics Data using Wavelet Based Functional Mixed Models (with Philip J. Brown, Richard C. Herrick, Keith A. Baggerly, and Kevin R. Coombes), Biometrics (2007)
In this paper, we analyze MALDI-TOF mass spectrometry proteomics data using Bayesian wavelet-based functional mixed...
 

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Laser capture sampling and analytical issues in proteomics (with Howard Gutstein), Expert Reviews in Proteomics (2007)
Proteomics holds the promise of evaluating global changes in protein expression and post-translational modificaiton in...
 

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Pre-Processing Mass Spectrometry Data (with Kevin R. Coombes and Keith A. Baggerly), Fundamentals of Data Mining in Genomics and Proteomics (2007)
 

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PrepMS: TOF MS Data Graphical Preprocessing Tool (with Yuliya V. Karpievitch, Elizabeth G. Hill, Adam J. Smolka, Kevin R. Coombes, Keith A. Baggerly, and Jonas S. Almeida), Bioinformatics (2006)
We introduce a simple-to-use graphical tool that enables researchers to easily prepare time-of-flight mass spectrometry...
 

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An Introduction to High-Throughput Bioinformatics Data (with Keith A. Baggerly and Kevin R. Coombes), Bayesian Inference in Gene Expression and Proteomics (2006)
High throughput biological assays supply thousands of measurements per sample, and the sheer amount of...
 

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Analysis of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models (with Philip J. Brown, Keith A. Baggerly, and Kevin R. Coombes), Bayesian Inference for Gene Expression and Proteomics (2006)
In this chapter, we demonstrate how to analyze MALDI-TOF/SELDITOF mass spectrometry data using the wavelet-based...
 

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Improved Peak Detection and Quantification of Mass Spectrometry Data Acquired from Surface-Enhanced Laser Desorption and Ionization by Denoising Spectra with the Undecimated Discrete Wavelet Transform (with Kevin R. Coombes, Spiros Tsavachidis, Keith A. Baggerly, and Henry M. Kuerer), Proteomics (2005)

Background: Mass spectrometry, especially surface enhanced laser desorption and ionization (SELDI) is increasingly being used...

 

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Feature Extraction and Quantification for Mass Spectrometry Data in Biomedical Applications Using the Mean Spectrum. (with Kevin R. Coombes, John Koomen, Keith A. Baggerly, and Ryuji Kobayashi), Bioinformatics (2005)

Motivation: Mass spectrometry yields complex functional data for which the features of scientific interest are...

 

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Understanding the Characteristics of Mass Spectrometry Data Through the Use of Simulation (with Kevin R. Coombes, John Koomen, Keith A. Baggerly, and Ryuji Kobayashi), Cancer Informatics (2005)

Background: Mass spectrometry is actively being used to discover disease-related proteomic patterns in complex mixtures...

 

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Bias, Randomization, and Ovarian Proteomic Data: A Reply to "Producers and Consumers" (with Keith A. Baggerly and Kevin R. Coombes), Cancer Informatics (2005)
Proteomic patterns derived from mass spectrometry have recently been put forth as potential biomarkers for...
 

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The Importance of Experimental Design in Proteomic Mass Spectrometry Experiments: Some Cautionary Tales (with Jianhua Hu, Kevin R. Coombes, and Keith A. Baggerly), Briefings in Genomics and Proteomics (2005)
Proteomic expression patterns derived from mass spectrometry have been put forward as potential biomarkers for...
 

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Serum Proteomics Profiling: A Young Technology Begins to Mature (with Kevin R. Coombes, Jianhua Hu, Sarah R. Edmondson, and Keith A. Baggerly), Nature Biotechnology (2005)
 

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Signal in Noise: Evaluating Reported Reproducibility of Serum Proteomic Tests for Ovarian Cancer (with Keith A. Baggerly, Sarah R. Edmonson, and Kevin R. Coombes), Journal of the National Cancer Institute (2005)
Proteomic profi ling of serum initially appeared to be dramatically effective for diagnosis of early-stage...
 

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High-resolution serum proteomic patterns for ovarian cancer detection (with Keith A. Baggerly, Sarah R. Edmonson, and Kevin R. Coombes), Endocrine-Related Cancer (2004)
 

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Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments (with Keith A. Baggerly and Kevin R. Coombes), Bioinformatics (2004)

Motivation: There has been much interest in using patterns derived from surface-enhanced laser desorption and...

 

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Quality Control and Peak Finding for Proteomics Data Collected from Nipple Aspirate Fluid Using Surface Enhanced Laser Desorption and Ionization. (with Kevin R. Coombes, Herbert A. Fritsche, Charlotte Clarke, Jeng-Neng Chen, Keith A. Baggerly, Lian-Chun Xiao, Mien-Chie Hung, and Henry M. Kuerer), Clinical Chemistry (2003)

Background: Recently, researchers have been using mass spectroscopy to study cancer. For use of proteomics...

 

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A comprehensive approach to the analysis of MALDI-TOF proteomics spectra from serum samples. (with Keith A. Baggerly, Jing Wang, David Gold, Lian-Chun Xiao, and Kevin R. Coombes), Proteomics (2003)
For our analysis of the data from the First Annual Proteomics Data Mining Conference, we...
 

Statistical Methods: Bootstrap

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The BLUPs Are Not “Best” When It Comes To Bootstrapping, Statistics and Probability Letters (2002)
In the setting of mixed models, some researchers may construct a semiparametric bootstrap by sampling...