MARC details
000 -LEADER |
fixed length control field |
03075nab a22004817a 4500 |
001 - CONTROL NUMBER |
control field |
G96948 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
MX-TxCIM |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240919020947.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
220421s2012 gw ||||| |||| 00| 0 eng d |
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
International Standard Serial Number |
1432-2242 (Online) |
022 0# - INTERNATIONAL STANDARD SERIAL NUMBER |
International Standard Serial Number |
0040-5752 |
024 8# - OTHER STANDARD IDENTIFIER |
Standard number or code |
https://doi.org/10.1007/s00122-012-1868-9 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
MX-TxCIM |
041 ## - LANGUAGE CODE |
Language code of text/sound track or separate title |
eng |
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
CIS-6766 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
González-Camacho, J.M. |
9 (RLIN) |
5411 |
245 10 - TITLE STATEMENT |
Title |
Genome-enabled prediction of genetic values using radial basis function neural networks |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc. |
Berlin (Germany) : |
Name of publisher, distributor, etc. |
Springer, |
Date of publication, distribution, etc. |
2012 |
500 ## - GENERAL NOTE |
General note |
Peer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0040-5752 |
500 ## - GENERAL NOTE |
General note |
Peer review |
500 ## - GENERAL NOTE |
General note |
Open Access |
520 ## - SUMMARY, ETC. |
Summary, etc. |
The availability of high density panels of molecular markers has prompted the adoption of genomic selection (GS) methods in animal and plant breeding. In GS, parametric, semi-parametric and non-parametric regressions models are used for predicting quantitative traits. This article shows how to use neural networks with radial basis functions (RBFs) for prediction with dense molecular markers. We illustrate the use of the linear Bayesian LASSO regression model and of two non-linear regression models, reproducing kernel Hilbert spaces (RKHS) regression and radial basis function neural networks (RBFNN) on simulated data and real maize lines genotyped with 55,000 markers and evaluated for several trait?environment combinations. The empirical results of this study indicated that the three models showed similar overall prediction accuracy, with a slight and consistent superiority of RKHS and RBFNN over the additive Bayesian LASSO model. Results from the simulated data indicate that RKHS and RBFNN models captured epistatic effects; however, adding non-signal (redundant) predictors (interaction between markers) can adversely affect the predictive accuracy of the non-linear regression models. |
536 ## - FUNDING INFORMATION NOTE |
Text of note |
Genetic Resources Program|Global Maize Program |
546 ## - LANGUAGE NOTE |
Language note |
Text in English |
591 ## - CATALOGING NOTES |
Affiliation |
CIMMYT Informa No. 1805|Springer |
594 ## - STAFFID |
StaffID |
INT2948|CCJL01|INT2822|INT2925 |
595 ## - COLLECTION |
Collection |
CIMMYT Staff Publications Collection |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
9 (RLIN) |
8685 |
Topical term or geographic name as entry element |
Artificial Selection |
Source of heading or term |
AGROVOC |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
9 (RLIN) |
9056 |
Topical term or geographic name as entry element |
Neural Networks |
Source of heading or term |
AGROVOC |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
9 (RLIN) |
1848 |
Topical term or geographic name as entry element |
Genetic markers |
Source of heading or term |
AGROVOC |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
9 (RLIN) |
2624 |
Topical term or geographic name as entry element |
Statistical methods |
Source of heading or term |
AGROVOC |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
9 (RLIN) |
2701 |
Topical term or geographic name as entry element |
Forecasting |
Source of heading or term |
AGROVOC |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
De los Campos, G. |
Field link and sequence number |
CCAG01 |
9 (RLIN) |
2349 |
Miscellaneous information |
Genetic Resources Program |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Perez-Rodriguez, P. |
9 (RLIN) |
2703 |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Gianola, D. |
9 (RLIN) |
7797 |
700 1# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
879 |
Personal name |
Cairns, J.E. |
Miscellaneous information |
Global Maize Program |
Field link and sequence number |
INT2948 |
700 1# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
861 |
Personal name |
Mahuku, G. |
Miscellaneous information |
Global Maize Program |
Field link and sequence number |
INT2822 |
700 1# - ADDED ENTRY--PERSONAL NAME |
9 (RLIN) |
875 |
Personal name |
BABU, R. |
Miscellaneous information |
Global Maize Program |
Field link and sequence number |
INT2925 |
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 |
Theoretical and Applied Genetics |
Related parts |
v. 125, no. 4, p. 759-771 |
Place, publisher, and date of publication |
Berlin (Germany) : Springer, 2012. |
Record control number |
G444762 |
International Standard Serial Number |
0040-5752 |
856 4# - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
http://hdl.handle.net/10883/1889 |
Link text |
Open Access through DSpace |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
Article |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Suppress in OPAC |
No |