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

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

Abstract Background The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determining such genetic bases is an evolutionary f...

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Bibliographic Details
Main Authors: Luis Torada, Lucrezia Lorenzon, Alice Beddis, Ulas Isildak, Linda Pattini, Sara Mathieson, Matteo Fumagalli
Format: Article
Language:English
Published: BMC 2019-11-01
Series:BMC Bioinformatics
Subjects:
Population genetics
Natural selection
Supervised machine learning
Convolutional neural networks
Online Access:http://link.springer.com/article/10.1186/s12859-019-2927-x

Internet

http://link.springer.com/article/10.1186/s12859-019-2927-x

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