Results 41 to 50 of about 333,629 (311)

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds

BMC Genomics, 2017
Background A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction.
Lingzhao Fang, Goutam Sahana, Peipei Ma, Guosheng Su, Ying Yu, Shengli Zhang, Mogens Sandø Lund, Peter Sørensen   +7 more
doaj   +1 more source

Multi-Trait Multi-Environment Genomic Prediction of Agronomic Traits in Advanced Breeding Lines of Winter Wheat

Frontiers in Plant Science, 2021
Genomic prediction is a promising approach for accelerating the genetic gain of complex traits in wheat breeding. However, increasing the prediction accuracy (PA) of genomic prediction (GP) models remains a challenge in the successful implementation of ...
Harsimardeep S. Gill, Jyotirmoy Halder, Jinfeng Zhang, Navreet K. Brar, Teerath S. Rai, Cody Hall, Amy Bernardo, Paul St Amand, Guihua Bai, Eric Olson, Shaukat Ali, Brent Turnipseed, Sunish K. Sehgal   +12 more
doaj   +1 more source

Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform [PDF]

, 2020
Genetic studies increasingly rely on high-throughput phenotyping, but the resulting longitudinal data pose analytical challenges. We used canopy height data from an automated field phenotyping platform to compare several approaches to scanning for ...
Orford, S., Simon Griffiths, Luzie U Wingen, Malcolm J Hawkesford, Virlet, N., Nicolas Virlet, Hassall, K. L., Wingen, L. U., Lyra, D. H., Slavov, G., Simon Orford, Sadeghi-Tehran, P., Griffiths, S., Gancho T Slavov, Pouria Sadeghi-Tehran, Danilo H Lyra, Hawkesford, M. J., Kirsty L Hassall   +17 more
core   +1 more source

GVCHAP: A Computing Pipeline for Genomic Prediction and Variance Component Estimation Using Haplotypes and SNP Markers

Frontiers in Genetics, 2020
Haplotype prediction models open many possibilities to improve the accuracy of genomic selection but require more data processing and computing time than single-SNP prediction models. To facilitate haplotype analysis for genomic prediction and estimation
Dzianis Prakapenka, Chunkao Wang, Zuoxiang Liang, Cheng Bian, Cheng Bian, Cheng Tan, Cheng Tan, Yang Da   +7 more
doaj   +1 more source

AGenDA: gene prediction by cross-species sequence comparison

, 2004
Taher L, Rinner O, Garg S, Sczyrba A, Morgenstern B. AGenDA: gene prediction by cross-species sequence comparison. Nucleic Acids Research. 2004;32(Web Server):W305-W308.Automatic gene prediction is one of the major challenges in computational sequence ...
Sczyrba, Alexander ; https://orcid.org/, Garg, S, Garg, S., Sczyrba, A., Taher, L, Rinner, O, Morgenstern, B, Taher, L., Rinner, O., Morgenstern, Burkhard   +9 more
core   +1 more source

Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources [PDF]

, 2008
Background: Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict ...
Hofstede, K.J., Oscar P Kuipers, Hijum, Sacha A.F.T. van,, Breitling, Rainer, Blom, E.J., Breitling, R., Breitling, Rainer,, Blom Evert, Roerdink, J.B.T.M., Hofstede Klaas, Breitling Rainer, Jos BTM Roerdink, Blom, Evert Jan, Klaas Hofstede, Roerdink, J.B.T.M.; id_orcid, Kuipers, Oscar P.,, van Hijum, S.A F T, Kuipers, O.P., Hofstede, Klaas Jan,, Roerdink, Jos B T M, van Hijum Sacha AFT, Roerdink Jos BTM, Kuipers, Oscar P., Rainer Breitling, van Hijum, S.A.F.T., Kuipers Oscar P, Hofstede, Klaas Jan, van Hijum, Sacha A F T, Blom, Evert Jan,, Sacha AFT van Hijum, Roerdink, Jos B.T.M.,, Evert Blom, Kuipers, O.P.; id_orcid   +32 more
core   +1 more source

Datasets to test the importance of genetic architecture in marker selection decisions for genomic prediction

, 2023
Files include structural variant calls of the maize parental lines, genotypic data for recombinant inbred lines (RILs), simulated trait values for each RIL with different genetic architectures, input data for genomic prediction models with different ...
Hirsch, Candice N, Monnahan, Patrick J, Mikel, Mark A, Della Coletta, Rafael, Fernandes, Samuel B, Bohn, Martin O, Lipka, Alexander E   +6 more
core   +1 more source

The Dimensionality of Genomic Information and Its Effect on Genomic Prediction [PDF]

Genetics, 2016
Abstract The genomic relationship matrix (GRM) can be inverted by the algorithm for proven and young (APY) based on recursion on a random subset of animals. While a regular inverse has a cubic cost, the cost of the APY inverse can be close to linear.
Pocrnic, Ivan, Lourenco, Daniela a L, Masuda, Yutaka, Legarra, Andres, Misztal, Ignacy   +4 more
openaire   +5 more sources

Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship. [PDF]

PLoS ONE, 2017
Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic.
S Hong Lee, Sam Clark, Julius H J van der Werf   +2 more
doaj   +1 more source

Comparison of analyses of the QTLMAS XIII common dataset. I: genomic selection [PDF]

, 2010
Background - Genomic selection, the use of markers across the whole genome, receives increasing amounts of attention and is having more and more impact on breeding programs. Development of statistical and computational methods to estimate breeding values
Coster, A., Albart Coster, Bastiaansen, J.W.M., Bink, M.C.A.M., Chris Maliepaard, Mario Calus, Calus, M.P.L., John Bastiaansen, John W M Bastiaansen, Marco C A M Bink, Marco Bink, Mario P L Calus, Maliepaard, C.A.   +12 more
core   +1 more source