MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02928nab|a22003737a|4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
64838 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
MX-TxCIM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240919021232.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
202112s2021||||sz |||p|op||||00||0|eng|d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1664-8021 |
| 024 8# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
https://doi.org/10.3389/fgene.2021.798840 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MX-TxCIM |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Montesinos-Lopez, O.A. |
| 9 (RLIN) |
2700 |
| Field link and sequence number |
I1706800 |
| Miscellaneous information |
Genetic Resources Program |
| 245 12 - TITLE STATEMENT |
|---|
| Title |
A new deep learning calibration method enhances genome-based prediction of continuous crop traits |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc. |
Switzerland : |
| Name of publisher, distributor, etc. |
Frontiers, |
| Date of publication, distribution, etc. |
2021. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Peer review |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Open Access |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Genomic selection (GS) has the potential to revolutionize predictive plant breeding. A reference population is phenotyped and genotyped to train a statistical model that is used to perform genome-enabled predictions of new individuals that were only genotyped. In this vein, deep neural networks, are a type of machine learning model and have been widely adopted for use in GS studies, as they are not parametric methods, making them more adept at capturing nonlinear patterns. However, the training process for deep neural networks is very challenging due to the numerous hyper-parameters that need to be tuned, especially when imperfect tuning can result in biased predictions. In this paper we propose a simple method for calibrating (adjusting) the prediction of continuous response variables resulting from deep learning applications. We evaluated the proposed deep learning calibration method (DL_M2) using four crop breeding data sets and its performance was compared with the standard deep learning method (DL_M1), as well as the standard genomic Best Linear Unbiased Predictor (GBLUP). While the GBLUP was the most accurate model overall, the proposed deep learning calibration method (DL_M2) helped increase the genome-enabled prediction performance in all data sets when compared with the traditional DL method (DL_M1). Taken together, we provide evidence for extending the use of the proposed calibration method to evaluate its potential and consistency for predicting performance in the context of GS applied to plant breeding. |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
Text in English |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Marker-assisted selection |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
10737 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Genomics |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1132 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
11127 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Plant breeding |
| Miscellaneous information |
AGROVOC |
| Source of heading or term |
|
| 9 (RLIN) |
1203 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Montesinos-Lopez, A. |
| 9 (RLIN) |
2702 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Mosqueda-Gonzalez, B.A. |
| 9 (RLIN) |
19441 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Bentley, A.R. |
| Field link and sequence number |
001712492 |
| Miscellaneous information |
Formerly Global Wheat Program |
| 9 (RLIN) |
9599 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Lillemo, M. |
| 9 (RLIN) |
1659 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Varshney, R.K. |
| 9 (RLIN) |
5901 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Crossa, J. |
| Miscellaneous information |
Genetic Resources Program |
| Field link and sequence number |
CCJL01 |
| 9 (RLIN) |
59 |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Frontiers in Genetics |
| Related parts |
v. 12, art. 798840 |
| Place, publisher, and date of publication |
Switzerland : Frontiers, 2021. |
| International Standard Serial Number |
1664-8021 |
| Record control number |
58093 |
| 856 4# - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
Open Access through DSpace |
| Uniform Resource Identifier |
https://hdl.handle.net/10883/21810 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Article |
| Suppress in OPAC |
No |
| Source of classification or shelving scheme |
Dewey Decimal Classification |