Results 11 to 20 of about 536,771 (324)

Application of Genomic Data for Reliability Improvement of Pig Breeding Value Estimates

Animals, 2021
Replacement pigs’ genomic prediction for reproduction (total number and born alive piglets in the first parity), meat, fatness and growth traits (muscle depth, days to 100 kg and backfat thickness over 6–7 rib) was tested using single-step genomic best ...
Ekaterina Melnikova, Artem Kabanov, Sergey Nikitin, Maria Somova, Sergey Kharitonov, Petr Otradnov, Olga Kostyunina, Tatiana Karpushkina, Elena Martynova, Aleksander Sermyagin, Natalia Zinovieva   +10 more
doaj   +1 more source

Promoter prediction in the human genome [PDF]

Bioinformatics, 2001
Abstract Computational prediction of eukaryotic polII promoters has been one of the most elusive problems despite considerable effort devoted to the study. Researchers have looked for various types of signals around the transcriptional start site (TSS), viz.
S, Hannenhalli, S, Levy
openaire   +2 more sources

Genomics-aided structure prediction [PDF]

Proceedings of the National Academy of Sciences, 2012
We introduce a theoretical framework that exploits the ever-increasing genomic sequence information for protein structure prediction. Structure-based models are modified to incorporate constraints by a large number of non-local contacts estimated from direct coupling analysis (DCA) of co-evolving genomic sequences.
Sulkowska, Joanna I., Morcos, Faruck, Weigt, Martin, Hwa, Terence, Onuchic, Jose N.   +4 more
openaire   +3 more sources

Evaluation of the efficiency of genomic versus pedigree predictions for growth and wood quality traits in Scots pine

BMC Genomics, 2020
Background Genomic selection (GS) or genomic prediction is a promising approach for tree breeding to obtain higher genetic gains by shortening time of progeny testing in breeding programs.
Ainhoa Calleja-Rodriguez, Jin Pan, Tomas Funda, Zhiqiang Chen, John Baison, Fikret Isik, Sara Abrahamsson, Harry X. Wu   +7 more
doaj   +1 more source

Machine learning for genomic prediction of growth traits in aquaculture: a case study of the Australasian snapper (Chrysophrys auratus). [PDF]

BMC Bioinformatics
Chen Z, Blommaert J, Mei Y, Jesson L, Wellenreuther M, Zhang M.   +5 more
europepmc   +3 more sources

Utility and First Clinical Application of Screening Embryos for Polygenic Disease Risk Reduction

Frontiers in Endocrinology, 2019
For over 2 decades preimplantation genetic testing (PGT) has been in clinical use to reduce the risk of miscarriage and genetic disease in patients with advanced maternal age and risk of transmitting disease.
Nathan R. Treff, Nathan R. Treff, Jennifer Eccles, Jennifer Eccles, Lou Lello, Lou Lello, Elan Bechor, Jeffrey Hsu, Kathryn Plunkett, Kathryn Plunkett, Raymond Zimmerman, Raymond Zimmerman, Bhavini Rana, Bhavini Rana, Artem Samoilenko, Steven Hsu, Laurent C. A. M. Tellier, Laurent C. A. M. Tellier, Laurent C. A. M. Tellier   +18 more
doaj   +1 more source

Genomic Prediction Using LD-Based Haplotypes in Combined Pig Populations

Frontiers in Genetics, 2022
The size of reference population is an important factor affecting genomic prediction. Thus, combining different populations in genomic prediction is an attractive way to improve prediction ability.
Haoqiang Ye, Zipeng Zhang, Duanyang Ren, Xiaodian Cai, Qianghui Zhu, Xiangdong Ding, Hao Zhang, Zhe Zhang, Jiaqi Li   +8 more
doaj   +1 more source

Pitfalls and Remedies for Cross Validation with Multi-trait Genomic Prediction Methods. [PDF]

, 2019
Incorporating measurements on correlated traits into genomic prediction models can increase prediction accuracy and selection gain. However, multi-trait genomic prediction models are complex and prone to overfitting which may result in a loss of ...
Cheng, Hao, Runcie, Daniel
core   +1 more source

Predictive Genomics of Cardioembolic Stroke [PDF]

Stroke, 2009
Cardioembolic stroke is a complex disease resulting from the interaction of numerous factors. Using data from Genes Affecting Stroke Risk and Outcome Study (GASROS), we show that a multivariate predictive model built using Bayesian networks is able to achieve a predictive accuracy of 86% on the fitted values as computed by the area under the receiver ...
Rachel Badovinac, Ramoni, Blanca E, Himes, Michele M, Sale, Karen L, Furie, Marco F, Ramoni   +4 more
openaire   +2 more sources

Genomic selection in rubber tree breeding: A comparison of models and methods for managing G×E interactions [PDF]

, 2019
Several genomic prediction models combining genotype × environment (G×E) interactions have recently been developed and used for genomic selection (GS) in plant breeding programs. G×E interactions reduce selection accuracy and limit genetic gains in plant
Francisco, Felipe O., Fritsche-Neto, Roberto, Gonçalves, Paulo De Souza, Le Guen, Vincent, Scaloppi Junior, Erivaldo José, Souza, Anete Pereira, Souza, Livia Moura   +6 more
core   +2 more sources