Jeffrey S. Morris

Talks

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2007

 

  1. Bayesian Wavelet-Based Mixed Models for Functional Data, Given at McGill University, Montreal, QC January 2007, Columbia University Department of Biostatistics and Brown University Department of Biostatistics, February 2007, and Biostatistics Research Branch of the National Institute of Allergy and Infectious Diseases (NIAID), University of North Carolina Department of Biostatistics, and North Carolina State University Department of Statistics, March 2007.

  2. Spot Detection and Quantification for 2-d Proteomic Data, ENAR Meetings of the International Biometric Society, Atlanta, GA,

 

2006

  1. Bayesian Wavelet-Based Mixed Models for Functional Data, Noether Award Session, Joint Statistical Meetings, Seattle, WA, August 2006.

  2. Statistical Contributions for Clinical Proteomic Research, Clinical Proteomics in Oncology, Plenary Lecture, Dijon, France, July 2006.

  3. Dealing with Incomplete Profiles in Wavelet-Based Functional Mixed ModelsInternational Chinese Statistical Association Applied Statistics Symposium, Storrs, CT, June 2006.

  4. Bayesian Analysis of Mass Spectrometry Data Using Wavelet Based Functional Mixed Models.  International Workshop of Applied Probability, Storrs, CT, May 2006.

  5. Bayesian Mixed Models for Functional Data. University of Washington, Department of Statistics, Seattle, WA, April 2006.

  6. Wavelet-Based Functional Mixed Models. ENAR Meetings of the International Biometrics Society, Tampa, FL, March 2006.

 

2005

  1. Wavelet-Based Functional Mixed Models. Joint Statistical Meetings, Minneapolis, MN, Focused Research Group Conference "Nonparametric Models for Complex Biological Data", Davis, CA, August 2005.

  2. Wavelet-Based Functional Mixed Models. WNAR Meetings of the International Biometrics Society, Fairbanks, AK, June 2005.

  3. Wavelet-Based Functional Mixed Models. ICSA Applied Statistics Symposium, Washington, DC, June 2005.

  4. Pooling Data Across Microarray Experiments Using Different Versions of Affymetrix Oligonucleotide Arrays. EMR Meetings of the International Biometrics Society, Kerkyra, Greece, May 2005.

  5. Wavelet-Based Preprocessing Methods for Mass Spectrometry Data. University of Texas, Dallas, Dallas, TX, April 2005.

  6. Bayesian Modeling and Inference for Mass Spectrometry Data using Functional Mixed Models.  ENAR Meetings of the International Biometrics Society, Austin, TX, March 2005.

  7. Using Wavelet-Based Functional Mixed Models to Characterize Population Heterogeneity in Accelerometer Profiles: A Case StudyJohns Hopkins University, Department of Biostatistics Grand Rounds, Baltimore, MD, February 2005.

2004

  1. Analyzing Accelerometer Data using Wavelet-Based Functional Mixed Models Harvard University School of Public Health, Department of Biostatistics, Boston, MA, December 2004.

  2. Functional Data Analysis for Accelerometer Data.  Harvard University School of Public Health, Department of Society, Human Development, and Health, December 2004.

  3. Wavelet-Based Preprocessing Methods for Mass Spectrometry Data. Ninth Annual Conference on Advancing Practice, Instruction, and Innovation through Informatics; APIII 2004, Pittsburgh, PA, October 2004.

  4. Wavelet-Based Functional Mixed Models, Joint Statistical Meetings, Toronto, ON, August 2004

  5. Wavelet-Based Functional Mixed Models.  XXIInd International Biometrics Conference; IBC 2004, Cairns, Queensland, Australia, July 2004.

  6. Bayesian Wavelet-Based Functional Mixed Models.  International Society for Bayesian Analysis (ISBA) 2004 World Meetings, Vina del Mar, Chile, May 2004.

  7. Wavelet-Based Functional Mixed Models.  University of Pennsylvania, November 2004, Yale University, November 2004, Los Alamos National Laboratories, October 2004, Rice University, Texas A&M University, April 2004.

  8. Pooling Information Across Different Studies and Affymetrix Chip Types to Identify Prognostic Genes for Lung Cancer. ENAR Meetings of the International Biometrics Society, Pittsburgh, PA, March 2004.


2003

  1.   Identification of Prognostic Genes, Combining Information Across Different Institutions and Oligonucleotide Arrays. CAMDA 2003, Durham, NC, November 2003.

  2. Analyzing Mass Spectrometry Proteomic Data from Serum Samples, Texas A&M University Nutrition Group, College Station, TX, September 2003.

  3. Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis. (with discussion and rejoinder)  Joint Statistical Meetings, San Francisco, CA,  August 2003.

  4. Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis.  WNAR Meetings of the International Biometrics Society, Golden, CO, June 2003.

  5. Bayesian Shrinkage Estimation of the Relative Abundance of mRNA Transcripts using SAGE.  ENAR Meetings of the International Biometrics Society, Tampa, FL, March 2003


2002
 

  1. Bayesian Wavelet-Based Nonparametric Modeling of Hierarchical Functions, 7th Valencia International Meeting on Bayesian Statistics, Canary Islands, Spain, June 2002.

  2. Statistical Issues in Serial Analysis of Gene Expression Data (SAGE), St. Cloud State University, Department of Statistics, St. Cloud, MN, April 2002, Texas A&M University, October 2002.

  3. Introduction to Bayesian Data Analysis and Markov Chain Monte Carlo, University of North Carolina, Department of Quantitative Psychology, Chapel Hill, NC, September 2002.

  4. Analysis of DNA Damage and Repair in Colonic Crypts, ENAR meetings of the International Biometrics Society, Arlington, VA, March 2002.

2001

  1. Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis.  University College of London, July 2001, University of Kent, Canterbury, July 2001, Southern Methodist University, October 2001, Texas A&M University, October 2001, Mississippi State University, October 2001, Harvard University, November 2002, Yale University, November 2002, University of Texas, October 2003, Rice University, February 2004.

 

2000

  1. Parametric and Nonparametric Methods for Understanding the Relationship of Carcinogen-Induced DNA Adduct Levels in Distal and Proximal Regions of the Colon, Mayo Clinic, January 2000, University of Michigan, University of Florida, February 2000, University of New Mexico, University of Chicago, Duke University, North Carolina State University, MD Anderson Cancer Center, March 2000, University of Washington, Texas A&M University, April 2000, Rice University, April 2001.

 




 

 

 

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