| Deep learning for population genetic inference S Sheehan, YS Song PLoS computational biology 12 (3), e1004845, 2016 | 271 | 2016 |
| Estimating variable effective population sizes from multiple genomes: a sequentially Markov conditional sampling distribution approach S Sheehan, K Harris, YS Song Genetics 194 (3), 647-662, 2013 | 215 | 2013 |
| FADS1 and the Timing of Human Adaptation to Agriculture S Mathieson, I Mathieson Molecular biology and evolution 35 (12), 2957-2970, 2018 | 123 | 2018 |
| A likelihood-free inference framework for population genetic data using exchangeable neural networks J Chan, V Perrone, J Spence, P Jenkins, S Mathieson, Y Song Advances in neural information processing systems 31, 2018 | 110 | 2018 |
| ImaGene: a convolutional neural network to quantify natural selection from genomic data L Torada, L Lorenzon, A Beddis, U Isildak, L Pattini, S Mathieson, ... BMC bioinformatics 20 (Suppl 9), 337, 2019 | 85 | 2019 |
| Automatic inference of demographic parameters using generative adversarial networks Z Wang, J Wang, M Kourakos, N Hoang, HH Lee, I Mathieson, ... Molecular ecology resources 21 (8), 2689-2705, 2021 | 47 | 2021 |
| Telescoper: de novo assembly of highly repetitive regions M Bresler, S Sheehan, AH Chan, YS Song Bioinformatics 28 (18), i311-i317, 2012 | 31 | 2012 |
| Decoding coalescent hidden Markov models in linear time K Harris, S Sheehan, JA Kamm, YS Song Research in Computational Molecular Biology: 18th Annual International …, 2014 | 15 | 2014 |
| Ancestral haplotype reconstruction in endogamous populations using identity-by-descent K Finke, M Kourakos, G Brown, HT Dang, SJS Tan, YB Simons, ... PLoS computational biology 17 (2), e1008638, 2021 | 8 | 2021 |
| Advances in Neural Information Processing Systems J Chan, V Perrone, J Spence, P Jenkins, S Mathieson, Y Song, S Bengio, ... | 5 | 2018 |
| Interpreting generative adversarial networks to infer natural selection from genetic data R Riley, I Mathieson, S Mathieson Genetics 226 (4), iyae024, 2024 | 1 | 2024 |
| Distributed Pipeline for Genomic Variant Calling R Xia, S Sheehan, Y Zhang, A Talwalkar, M Zaharia, J Terhorst, M Jordan, ... NIPS Workshop on BIG Learning, 2012 | 1 | 2012 |
| The genomic footprint of social stratification in admixing American populations A Mas-Sandoval, S Mathieson, M Fumagalli Elife 12, e84429, 2023 | | 2023 |
| Comparison of cohort-based identical-by-descent (IBD) segment finding methods for endogamous populations HT Dang, SJS Tan, S Mathieson Proceedings of the 13th ACM International Conference on Bioinformatics …, 2022 | | 2022 |
| CSC# 390# Topics# in# Artificial# Intelligence S Mathieson | | 2016 |
| Deep Learning for Population Genetic Inference S Mathieson, YS Song | | 2016 |
| Scalable algorithms for population genomic inference S Sheehan University of California, Berkeley, 2015 | | 2015 |
| Estimating variable effective population sizes from multiple genomes: A sequentially Markov conditional sampling distribution approach S Mathieson, K Harris, YS Song | | 2013 |
Kelley HarrisAssociate Professor of Genome Sciences, University of WashingtonПотвърден имейл адрес: uw.edu
