| Polygenic modeling with Bayesian sparse linear mixed models X Zhou, P Carbonetto, M Stephens PLoS genetics 9 (2), e1003264, 2013 | 862 | 2013 |
| A simple new approach to variable selection in regression, with application to genetic fine mapping G Wang, A Sarkar, P Carbonetto, M Stephens Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020 | 572 | 2020 |
| A statistical model for general contextual object recognition P Carbonetto, N de Freitas, K Barnard 8th European Conference on Computer Vision, 350-362, 2004 | 373 | 2004 |
| Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies P Carbonetto, M Stephens | 343 | 2012 |
| Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions SM Urbut, G Wang, P Carbonetto, M Stephens Nature genetics 51 (1), 187-195, 2019 | 298 | 2019 |
| Genetic background limits generalizability of genotype-phenotype relationships L Sittig, P Carbonetto, K Engel, K Krauss, C Barrios-Camacho, A Palmer Neuron 91, 1253-1259, 2016 | 258 | 2016 |
| Fine-mapping from summary data with the “Sum of Single Effects” model Y Zou, P Carbonetto, G Wang, M Stephens PLoS genetics 18 (7), e1010299, 2022 | 140 | 2022 |
| Genome-wide association study of behavioral, physiological and gene expression traits in outbred CFW mice CC Parker, S Gopalakrishnan, P Carbonetto, NM Gonzales, E Leung, ... Nature Genetics, 2016 | 136 | 2016 |
| Clustering of 770,000 genomes reveals post-colonial population structure of North America E Han, P Carbonetto, RE Curtis, Y Wang, JM Granka, J Byrnes, K Noto, ... Nature Communications 8, 14238, 2017 | 128 | 2017 |
| Integrated enrichment analysis of variants and pathways in genome-wide association studies indicates central role for IL-2 signaling genes in type 1 diabetes, and cytokine … P Carbonetto, M Stephens PLoS genetics 9 (10), e1003770, 2013 | 86 | 2013 |
| Mapping of Craniofacial Traits in Outbred Mice Identifies Major Developmental Genes Involved in Shape Determination LF Pallares, P Carbonetto, S Gopalakrishnan, CC Parker, ... PLoS Genetics 11 (11), e1005607, 2015 | 78 | 2015 |
| Learning to recognize objects with little supervision P Carbonetto, G Dorkó, C Schmid, H Kück, N De Freitas International Journal of Computer Vision 77, 219-237, 2008 | 61 | 2008 |
| Creating and sharing reproducible research code the workflowr way JD Blischak, P Carbonetto, M Stephens F1000Research 8, 2019 | 60 | 2019 |
| Accurate genomic prediction of Coffea canephora in multiple environments using whole-genome statistical models LFV Ferrão, RG Ferrão, MAG Ferrão, A Fonseca, P Carbonetto, ... Heredity 122 (3), 261-275, 2019 | 52 | 2019 |
| High-resolution genetic mapping of complex traits from a combined analysis of F2 and advanced intercross mice C Parker, P Carbonetto, G Sokoloff, Y Park, M Abney, A Palmer Genetics 198, 103-116, 2014 | 51 | 2014 |
| Discovering population structure from patterns of identity-by-descent E Han, RE Curtis, P Carbonetto US Patent 10,223,498, 2019 | 45 | 2019 |
| Bayesian feature weighting for unsupervised learning, with application to object recognition P Carbonetto, N De Freitas, P Gustafson, N Thompson Artificial Intelligence and Statistics, 2003 | 38 | 2003 |
| A fast algorithm for maximum likelihood estimation of mixture proportions using sequential quadratic programming Y Kim, P Carbonetto, M Stephens, M Anitescu Journal of Computational and Graphical Statistics, 2019 | 37 | 2019 |
| Nonparametric Bayesian logic P Carbonetto, J Kisynski, N de Freitas, DL Poole 21st Conference on Uncertainty in Artificial Intelligence, 85-93, 2005 | 37* | 2005 |
| A constrained semi-supervised learning approach to data association H Kück, P Carbonetto, N de Freitas 8th European Conference on Computer Vision, 1-12, 2004 | 32 | 2004 |
Matthew StephensUniversity of Chicago在 uchicago.edu 的电子邮件经过验证
