James Booth

James
Booth
Professor; Director of Graduate Studies
PhD
Biological Statistics & Computational Biology

I am currently Chair of the Department of Biological Statistics and Computational Biology in the College of Agriculture and Life Sciences at Cornell University. I came to Cornell in 2003 as a visitor to the Department of Operations Research and Information Engineering, and was hired in BSCB the following year. From 1987 to 2003 I was a faculty member in the Department of Statistics at the University of Florida. My research has covered a range of statistical topics including the bootstrap and Monte Carlo methods, clustering, exact inference, mixed models, generalized linear models, applications of the saddlepoint and Laplace approximations and model fitting algoritms. More recently I have focused on the development of statistical methods for analyzing modern biological data. Since coming to Cornell I have taught the Statistical Methods II course for graduate students from a wide variety of disciplines, Theory of Linear and Generalized Linear Models primarily for Ph.D. students in the Department of Statistical Sciences, and special topics courses on Categorical Data Analysis, Likelihood and Bayesian Statistical Methods and Linear Models with Matrices. As a faculty member in BSCB I am also actively involved in the Cornell Statistical Consulting Unit which provides free advice on statistical issues to faculty and students at Cornell. 

Publications

Statistical Methodology

  • Gaynanova, Booth, Wells (2015), "Simultaneous sparse estimation of canonical vectors in the p>>n setting". Journal of the American Statistical Association. 
  • http://www.tandfonline.com/doi/abs/10.1080/01621459.2015.1034318
  • Bar, Booth, Wells (2014), "A bivariate model for simultaneous testing in bioinformatics data", Journal of the American Statistical Association 109(506):537-547.
  • Kormaksson, Booth, Figueroa and Melnick (2012) "Integrative model-based clustering of microarray methylation and expression data". Annals of Applied Statistics 6(3):1327-1347.
  • Bar, Booth, Schifano and Wells (2010), "Laplace approximated EM Microarray Analysis: an empirical Bayes approach for comparative microarray experiments". Statistical Science 25(3):388-407. Please contact Haim Bar at the University of Connecticutt with questions about the Lemma software package.
  • Booth, Federer, Wells and Wolfinger (2009), "A multivariate variance component model for analysis of covariance in designed experiments", Statistical Science 24(2):223-237.

Applications

  • Eilertson, Booth, Bustamante (2012) "SnIPRE: Selection inference using a Poisson random effects model" PLoS Computational Biology 8(12): e1002806. doi:10.1371/journal.pcbi.1002806.
  • Hirschl, Booth, Glenna and Green (2012), "Politics, religion, and society: Is the United States experiencing a period of religious-political polarization?", Review of European Studies 4(4) (Aug 3, 2012 Epub ahead of print). Data for the RES paper can be found here.
  • Rosenbaum, Bar, Beg, Segrč, Booth, Cotta and Angenent (2012), "Transcriptional analysis of Shewanella oneidensis MR-1 with an electrode compared to Fe(III)citrate or oxygen as terminal electron acceptor", PLoS ONE 7(2):e30827.
  • Booth, Eilertson, Olinares and Yu (2011), "A Bayesian mixture model for comparative spectral count data in shotgun proteomics". Molecular and Cellular Proteomics10(8):M110.007203. Data analyzed in this paper can be found here.
  • Rosenbaum, Bar, Beg, Segrè, Booth, Cotta and Angenent (2011), "Shewanella oneidensis in a lactate-fed pure-culture and a glucose-fed co-culture with Lactococcuslactis with an electrode as electron acceptor". Bioresource Technology 102(3):2623-2628 (Oct 12, 2010 Epub ahead of print).