Sara Mathieson
Sara Mathieson
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TitleCited byYear
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
Deep learning for population genetic inference
S Sheehan, YS Song
PLoS computational biology 12 (3), e1004845, 2016
Telescoper: de novo assembly of highly repetitive regions
M Bresler, S Sheehan, AH Chan, YS Song
Bioinformatics 28 (18), i311-i317, 2012
FADS1 and the Timing of Human Adaptation to Agriculture
S Mathieson, I Mathieson
Molecular biology and evolution 35 (12), 2957-2970, 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, 8594-8605, 2018
Decoding coalescent hidden Markov models in linear time
K Harris, S Sheehan, JA Kamm, YS Song
International Conference on Research in Computational Molecular Biology, 100-114, 2014
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
Scalable Algorithms for Population Genomic Inference
S Sheehan
UC Berkeley, 2015
Supplementary material for the paper: A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
J Chan, V Perrone, JP Spence, PA Jenkins, S Mathieson, YS Song
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