BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

189 related articles for article (PubMed ID: 34843488)

  • 1. Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study.
    da Silva Júnior AC; Silva MJD; Cruz CD; Sant'Anna IC; Silva GN; Nascimento M; Azevedo CF
    PLoS One; 2021; 16(11):e0257213. PubMed ID: 34843488
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Genomic prediction ability for beef fatty acid profile in Nelore cattle using different pseudo-phenotypes.
    Chiaia HLJ; Peripolli E; de Oliveira Silva RM; Feitosa FLB; de Lemos MVA; Berton MP; Olivieri BF; Espigolan R; Tonussi RL; Gordo DGM; de Albuquerque LG; de Oliveira HN; Ferrinho AM; Mueller LF; Kluska S; Tonhati H; Pereira ASC; Aguilar I; Baldi F
    J Appl Genet; 2018 Nov; 59(4):493-501. PubMed ID: 30251238
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods.
    Alves AAC; da Costa RM; Bresolin T; Fernandes Júnior GA; Espigolan R; Ribeiro AMF; Carvalheiro R; de Albuquerque LG
    J Anim Sci; 2020 Jun; 98(6):. PubMed ID: 32474602
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction.
    Xu Y; Zhang X; Li H; Zheng H; Zhang J; Olsen MS; Varshney RK; Prasanna BM; Qian Q
    Mol Plant; 2022 Nov; 15(11):1664-1695. PubMed ID: 36081348
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data.
    Lourenço VM; Ogutu JO; Rodrigues RAP; Posekany A; Piepho HP
    BMC Genomics; 2024 Feb; 25(1):152. PubMed ID: 38326768
    [TBL] [Abstract][Full Text] [Related]  

  • 6. MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traits.
    Liang M; Cao S; Deng T; Du L; Li K; An B; Du Y; Xu L; Zhang L; Gao X; Li J; Guo P; Gao H
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36752363
    [TBL] [Abstract][Full Text] [Related]  

  • 7. How powerful are summary-based methods for identifying expression-trait associations under different genetic architectures?
    Veturi Y; Ritchie MD
    Pac Symp Biocomput; 2018; 23():228-239. PubMed ID: 29218884
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Genomic selection in a pig population including information from slaughtered full sibs of boars within a sib-testing program.
    Samorè AB; Buttazzoni L; Gallo M; Russo V; Fontanesi L
    Animal; 2015 May; 9(5):750-9. PubMed ID: 25510405
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Determination of the optimal number of markers and individuals in a training population necessary for maximum prediction accuracy in F
    Peixoto LA; Bhering LL; Cruz CD
    Genet Mol Res; 2016 Nov; 15(4):. PubMed ID: 27886337
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Genome-wide prediction of discrete traits using Bayesian regressions and machine learning.
    González-Recio O; Forni S
    Genet Sel Evol; 2011 Feb; 43(1):7. PubMed ID: 21329522
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.
    Lorenz AJ
    G3 (Bethesda); 2013 Mar; 3(3):481-91. PubMed ID: 23450123
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.
    He D; Kuhn D; Parida L
    Bioinformatics; 2016 Jun; 32(12):i37-i43. PubMed ID: 27307640
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Genome-Wide Search for Quantitative Trait Loci Controlling Important Plant and Flower Traits in Petunia Using an Interspecific Recombinant Inbred Population of
    Cao Z; Guo Y; Yang Q; He Y; Fetouh MI; Warner RM; Deng Z
    G3 (Bethesda); 2018 Jul; 8(7):2309-2317. PubMed ID: 29764961
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Accounting for trait architecture in genomic predictions of US Holstein cattle using a weighted realized relationship matrix.
    Tiezzi F; Maltecca C
    Genet Sel Evol; 2015 Apr; 47(1):24. PubMed ID: 25886167
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genomic prediction in plants: opportunities for ensemble machine learning based approaches.
    Farooq M; van Dijk ADJ; Nijveen H; Mansoor S; de Ridder D
    F1000Res; 2022; 11():802. PubMed ID: 37035464
    [No Abstract]   [Full Text] [Related]  

  • 16. Precision-mapping and statistical validation of quantitative trait loci by machine learning.
    Bedo J; Wenzl P; Kowalczyk A; Kilian A
    BMC Genet; 2008 May; 9():35. PubMed ID: 18452626
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Marker-based estimation of heritability in immortal populations.
    Kruijer W; Boer MP; Malosetti M; Flood PJ; Engel B; Kooke R; Keurentjes JJ; van Eeuwijk FA
    Genetics; 2015 Feb; 199(2):379-98. PubMed ID: 25527288
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A genome-wide association study identified loci for yield component traits in sugarcane (Saccharum spp.).
    Barreto FZ; Rosa JRBF; Balsalobre TWA; Pastina MM; Silva RR; Hoffmann HP; de Souza AP; Garcia AAF; Carneiro MS
    PLoS One; 2019; 14(7):e0219843. PubMed ID: 31318931
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicted accuracy of and response to genomic selection for new traits in dairy cattle.
    Calus MP; de Haas Y; Pszczola M; Veerkamp RF
    Animal; 2013 Feb; 7(2):183-91. PubMed ID: 23031684
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Increased accuracy of artificial selection by using the realized relationship matrix.
    Hayes BJ; Visscher PM; Goddard ME
    Genet Res (Camb); 2009 Feb; 91(1):47-60. PubMed ID: 19220931
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.