Optimisation of autoencoders for prediction of SNPs determining phenotypes in wheat

Optimisation of autoencoders for prediction of SNPs determining phenotypes in wheat

The increase in demand for food has resulted in increased demand for tools that help streamline plant breeding process in order to create new varieties of crops. Identifying the underlying genetic mechanism of favourable characteristics is essential in order to make the best breeding decisions. In t...

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Bibliographic Details
Main Author: Nair, Karthik
Format: Others
Language:English
Published: Uppsala universitet, Institutionen för biologisk grundutbildning 2021
Subjects:
Deep Learning
Machine Learning
Convolutional Neural Networks
Convolutional Variational Autoencoders
Autoencoders
SNP-Phenotype relationships
Genetics
Agricultural Bioinformatics
Neural Networks
Unsupervised Learning
Bioinformatics (Computational Biology)
Bioinformatik (beräkningsbiologi)
Bioinformatics and Systems Biology
Bioinformatik och systembiologi
Agricultural Biotechnology
Bioteknologi med applikationer på växter och djur
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-437451

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-437451

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