Paulino Pérez-Rodríguez, Ph.D.

Paulino Perez Rodriguez, Ph.D. Department of Biostatistics
Ryals Public Health Bldg, 307B
University of Alabama at Birmingham
Birmingham, AL 35294
Phone: (205) 975-9189
Fax: (205) 975-2540
E-mail: perpdgo@uab.edu
Full CV

 


I have a MS degree in Statistics and a Doctoral degree in Statistics from the Colegio de Postgraduados, Mexico. In 2011/12 I completed a 1 year postdoc at University of Wisconsin-Madison under the supervision of professor Daniel Gianola. Currently I am visiting scholar at the Section on Statistical Genetics of the Biostatistics Department of University of Alabama at Birmingham and Assistant Professor of Colegio de Postgraduados in Mexico. My research interests include Bayesian statistics, high throughput computing and software development for prediction of complex traits in plants and animals.

Publications
 

  • 2013
  • 2012
  • 2011
  • pre 2011
  1. J. Crossa, P. Pérez-Rodríguez, J. Hickey, J. Burgueño, L. Ornella, J. Cerón-Rojas, X. Zhang, S. Dreisigacker, L. Yongle, D. Bonnet, and K. Mathews, “Genomic Prediction in CIMMyT maize and wheat breeding programs (To appear),” Heredity.
     
  2. M. López, P. Pérez-Rodíguez, J. C. Rojas, M. Soto-Hernández, L. López-Mata, and V. Rico-Gray, “Host use and resource sharing by fruit/seed-infesting insects on Schoepfia schreberi (Olacaceae)”, Environmental Entomology, 42(2): 231-239.
     
  3. K. Haugaard, L. Tusell-Palomero, P. Pérez-Rodríguez, D. Gianola, A. C. Whist, and B. Heringstad, “Prediction of clinical mastitis outcomes within and between environments using whole-genome markers (To appear),” Journal of Diary Science.
     
  4. P. Pérez-Rodíguez, D. Gianola, G. Rosa, K. Weigel, and J. Crossa, “Technical Note: An R package for fitting Bayesian regularized neural networks with applications in animal breeding (To appear),” Journal of Animal Science.
     
  5. L. Tusell-Palomero, P. Pérez-Rodríguez, S. Forni, X. Wu, and D. Gianola, “Genome-enabled methods for predicting litter size in pigs: a comparison (Submitted),” Animal.
     
  1. A. Cano-Salgado, J. A. Zavala-Hurtado, A. Orozco-Segovia, M. T. Valverde-Valdés, and P. Pérez-Rodríguez, “Composición y abundancia del banco de semillas en una región semiárida del trópico mexicano: patrones de variación espacial y temporal,” Revista Mexicana de Biodiversidad, vol. 83, no. 2, pp. 437–443.
     
  2. J. M. González-Camacho, G. de los Campos, P. Pérez-Rodríguez, D. Gianola, J. Cairns, G. Mahuku, R. Babu, and J. Crossa, “Genome-enabled prediction of genetic values using radial basis function neural networks,” TAG Theoretical and Applied Genetics, pp. 1–13.
     
  3. Y. Montes-Rivera, P. Pérez-Rodríguez, and S. Pérez-Elizade, “Ajuste del ingreso en México: Un enfoque Bayesiano,” Estudios Económicos, Colegio de México, vol. 27, no. 2, pp. 273–293.
     
  4. L. Ornella, S. Singh, P. Pérez-Rodríguez, J. Burgueño, R. Singh, E. Tapia, S. Bhavani, S. Dreisigacker, H. J. Braun, K. Mathews, and others, “Genomic Prediction of Genetic Values for Resistance to Wheat Rusts,” The Plant Genome, vol. 5, no. 3, pp. 136–148.
     
  5. P. Pérez-Rodríguez, D. Gianola, J. M. González-Camacho, J. Crossa, Y. Manes, and S. Dreisigacker, “Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat,” G3-Genetics, vol. 2, pp. 1595–1605.
     
  6. P. Pérez-Rodríguez, G. de los Campos, S. Dreisigacker, H. Sánchez, and J. Crossa, “Application of Bayesian Elastic Net and other shrinkage methods in genomic selection and QTL mapping,” Journal of the Indian Society of Agricultural Statistics, vol. 66, no. 3, pp. 413–426.
     
  7. V. Salinas-Ruiz, P. Pérez-Rodríguez, E. González-Estrada, and H. Vaquera-Huerta, “A goodness of fit test for the Gumbel distribution with Type II censored data based on the Kullback-Leibler divergence,” Revista Colombiana de Estadística, vol. 35, no. 3, pp. 407–422.
     
  8. A. Tiessen, P. Pérez-Rodríguez, and L. J. Delaye-Arredondo, “Mathematical modeling and comparison of protein size distribution in different plant, animal, fungal and microbial species reveals a negative correlation between protein size and protein number, thus providing insight into the evolution of proteomes,” BMC Research Notes, vol. 5, no. 1, p. 85.
     
  1. S. Arvidsson, P. Pérez-Rodríguez, and B. Mueller-Roeber, “A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects,” New Phytologist, vol. 191, no. 3, pp. 895–907.
     
  2. J. Crossa, P. Pérez-Rodríguez, G. de los Campos, G. Mahuku, S. Dreisigacker, and C. Magorokosho, “Genomic selection and prediction in plant breeding,” Journal of Crop Improvement, vol. 25, no. 3, pp. 239–261.
     
  3. J. M. González-Camacho, P. Pérez-Rodríguez, and P. Ruelle, “Estimación de índices normalizados de lluvia mediante la distribución gamma generalizada extendida,” Ingeniería Hidráulica en México, vol. 2, no. 4, pp. 65–76.
     
  4. S. Rodríguez-Rodríguez, H. Reyes-Cervantes, P. Pérez-Rodríguez, and H. Vaquera-Huerta, “Selection of a Subset of Meteorological Variables for Ozone Analysis: Case Study of Pedregal Station in Mexico City,” Journal of Environmental Science and Engeeniering (JESE), vol. 1, pp. 11–20.
     
  1. J. Crossa, G. de los Campos, P. Pérez-Rodríguez, D. Gianola, J. Burgueño, J. L. Araus, D. Makumbi, R. P. Singh, S. Dreisigacker, J. Yan, and others, “Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers,” Genetics, vol. 186, no. 2, pp. 713–724.
     
  2. P. Pérez-Rodríguez, G. de los Campos, J. Crossa, and D. Gianola, “Genomic-enabled prediction based on molecular markers and pedigree using the Bayesian linear regression package in R,” The Plant Genome, vol. 3, no. 2, p. 106.
     
  3. P. Pérez-Rodríguez, D. M. Riaño-Pachón, L. G. G. Corrêa, S. A. Rensing, B. Kersten, and B. Mueller-Roeber, “PlnTFDB: updated content and new features of the plant transcription factor database,” Nucleic acids
     
  4. P. Pérez-Rodríguez, H. Vaquera-Huerta, and J. A. Villaseñor-Alva, “A Goodness-of-Fit Test for the Gumbel Distribution Based on Kullback–Leibler Information,” Communications in Statistics—Theory and Methods, vol. 38, no. 6, pp. 842–855.
     

 

Years: 2012 - 2013
Mentor(s): Gustavo de los Campos PhD