From 40657260ea6ed95240f85fdcc4ae87977a34c53e Mon Sep 17 00:00:00 2001 From: Richel Bilderbeek Date: Mon, 20 Dec 2021 09:12:09 +0100 Subject: [PATCH] Added link to the paper --- README.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d21a8b0..3100238 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,9 @@ # Genomic selection using deep learning and saliency map -We provide a deep-learning method to predict five quantitative traits (Yield, Protein, Oil, Moisture and Plant height) of SoyNAM dataset. +We provide a deep-learning method to predict five quantitative traits (Yield, Protein, Oil, Moisture and Plant height) of SoyNAM dataset. We also applied saliency map approach measure phenotype contribution for genome wide association study. -The program is implemented using Keras2.0 and Tensorflow backend with python 2.7 +The program is implemented using Keras2.0 and Tensorflow backend with python 2.7. +See [1] for the full method. ### Prerequisites @@ -39,6 +40,9 @@ python height.py * **Email** - *ylmk2@mail.missouri.edu* * **Email** - *yanglou1990@gmail.com* +## References + + * [1] Liu, Yang, et al. "Phenotype prediction and genome-wide association study using deep convolutional neural network of soybean." Frontiers in genetics 10 (2019): 1091. [here](https://www.frontiersin.org/articles/10.3389/fgene.2019.01091) ## License GNU v2.0