ImaGene: a convolutional neural network to quantify natural selection from genomic data

被引：0
作者：
Luis Torada
Lucrezia Lorenzon
Alice Beddis
Ulas Isildak
Linda Pattini
Sara Mathieson
Matteo Fumagalli
机构：
[1] Department of Life Sciences,
[2] Silwood Park campus,undefined
[3] Imperial College London,undefined
[4] Department of Electronics,undefined
[5] Information and Bioengineering,undefined
[6] Politecnico di Milano,undefined
[7] Department of Biological Sciences,undefined
[8] Middle East Technical University,undefined
[9] Department of Computer Science,undefined
[10] Swarthmore College,undefined
来源：
BMC Bioinformatics | / 20卷
关键词：
Population genetics; Natural selection; Supervised machine learning; Convolutional neural networks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 262 条
[1]  
Levy SE(2016)Advancements in next-generation sequencing Annu Rev Genomics Hum Genet 17 95-115
[2]  
Myers RM(2014)Population genomics reveal recent speciation and rapid evolutionary adaptation in polar bears Cell 157 785-94
[3]  
Liu S(2018)Human adaptation to extreme environmental conditions Curr Opin Genet Dev 53 77-82
[4]  
Lorenzen ED(2013)The impact of natural selection on health and disease: uses of the population genetics approach in humans Evol Appl 6 596-607
[5]  
Fumagalli M(2014)Natural selection and infectious disease in human populations Nat Rev Genet 15 379-95
[6]  
Li B(2006)A map of recent positive selection in the human genome PLoS Biol 4 72-15
[7]  
Harris K(2017)Detecting positive selection in the genome BMC Biol 15 98-93
[8]  
Xiong Z(1989)Statistical method for testing the neutral mutation hypothesis by dna polymorphism Genetics 123 585-93
[9]  
Zhou L(2007)Genome-wide detection and characterization of positive selection in human populations Nature 449 913-24
[10]  
Korneliussen TS(2010)The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation Curr Biol 20 208-8
12345678910