603 related articles for article (PubMed ID: 30558534)
21. Including gene networks to predict calving difficulty in Holstein, Brown Swiss and Jersey cattle.
Tiezzi F; Arceo ME; Cole JB; Maltecca C
BMC Genet; 2018 Apr; 19(1):20. PubMed ID: 29609562
[TBL] [Abstract][Full Text] [Related]
22. Gene networks for three feed efficiency criteria reveal shared and specific biological processes.
Taussat S; Boussaha M; Ramayo-Caldas Y; Martin P; Venot E; Cantalapiedra-Hijar G; Hozé C; Fritz S; Renand G
Genet Sel Evol; 2020 Nov; 52(1):67. PubMed ID: 33167870
[TBL] [Abstract][Full Text] [Related]
23. RNA sequencing for global gene expression associated with muscle growth in a single male modern broiler line compared to a foundational Barred Plymouth Rock chicken line.
Kong BW; Hudson N; Seo D; Lee S; Khatri B; Lassiter K; Cook D; Piekarski A; Dridi S; Anthony N; Bottje W
BMC Genomics; 2017 Jan; 18(1):82. PubMed ID: 28086790
[TBL] [Abstract][Full Text] [Related]
24. Transcriptome analyses reveal reduced hepatic lipid synthesis and accumulation in more feed efficient beef cattle.
Mukiibi R; Vinsky M; Keogh KA; Fitzsimmons C; Stothard P; Waters SM; Li C
Sci Rep; 2018 May; 8(1):7303. PubMed ID: 29740082
[TBL] [Abstract][Full Text] [Related]
25. Liver transcriptomic networks reveal main biological processes associated with feed efficiency in beef cattle.
Alexandre PA; Kogelman LJ; Santana MH; Passarelli D; Pulz LH; Fantinato-Neto P; Silva PL; Leme PR; Strefezzi RF; Coutinho LL; Ferraz JB; Eler JP; Kadarmideen HN; Fukumasu H
BMC Genomics; 2015 Dec; 16():1073. PubMed ID: 26678995
[TBL] [Abstract][Full Text] [Related]
26. Random Forests approach for identifying additive and epistatic single nucleotide polymorphisms associated with residual feed intake in dairy cattle.
Yao C; Spurlock DM; Armentano LE; Page CD; VandeHaar MJ; Bickhart DM; Weigel KA
J Dairy Sci; 2013 Oct; 96(10):6716-29. PubMed ID: 23932129
[TBL] [Abstract][Full Text] [Related]
27. Systems biology analysis merging phenotype, metabolomic and genomic data identifies Non-SMC Condensin I Complex, Subunit G (NCAPG) and cellular maintenance processes as major contributors to genetic variability in bovine feed efficiency.
Widmann P; Reverter A; Weikard R; Suhre K; Hammon HM; Albrecht E; Kuehn C
PLoS One; 2015; 10(4):e0124574. PubMed ID: 25875852
[TBL] [Abstract][Full Text] [Related]
28. Co-Expression Network Analysis Identifies miRNA⁻mRNA Networks Potentially Regulating Milk Traits and Blood Metabolites.
Ammah AA; Do DN; Bissonnette N; Gévry N; Ibeagha-Awemu EM
Int J Mol Sci; 2018 Aug; 19(9):. PubMed ID: 30149509
[TBL] [Abstract][Full Text] [Related]
29. Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens.
Xu Z; Ji C; Zhang Y; Zhang Z; Nie Q; Xu J; Zhang D; Zhang X
BMC Genomics; 2016 Aug; 17():594. PubMed ID: 27506765
[TBL] [Abstract][Full Text] [Related]
30. Identifying the key genes and functional enrichment pathways associated with feed efficiency in cattle.
Yang C; Zhu Y; Ding Y; Huang Z; Dan X; Shi Y; Kang X
Gene; 2022 Jan; 807():145934. PubMed ID: 34478820
[TBL] [Abstract][Full Text] [Related]
31. Integrative approach using liver and duodenum RNA-Seq data identifies candidate genes and pathways associated with feed efficiency in pigs.
Ramayo-Caldas Y; Ballester M; Sánchez JP; González-Rodríguez O; Revilla M; Reyer H; Wimmers K; Torrallardona D; Quintanilla R
Sci Rep; 2018 Jan; 8(1):558. PubMed ID: 29323241
[TBL] [Abstract][Full Text] [Related]
32. Global gene expression profiling reveals genes expressed differentially in cattle with high and low residual feed intake.
Chen Y; Gondro C; Quinn K; Herd RM; Parnell PF; Vanselow B
Anim Genet; 2011 Oct; 42(5):475-90. PubMed ID: 21906099
[TBL] [Abstract][Full Text] [Related]
33. Expression of genes involved in energy homeostasis in the duodenum and liver of Holstein-Friesian and Jersey cows and their F(1) hybrid.
Alam T; Kenny DA; Sweeney T; Buckley F; Prendiville R; McGee M; Waters SM
Physiol Genomics; 2012 Feb; 44(2):198-209. PubMed ID: 22147267
[TBL] [Abstract][Full Text] [Related]
34. Feeding, production, and efficiency of Holstein-Friesian, Jersey, and mixed-breed lactating dairy cows in commercial Danish herds.
Kristensen T; Jensen C; Østergaard S; Weisbjerg MR; Aaes O; Nielsen NI
J Dairy Sci; 2015 Jan; 98(1):263-74. PubMed ID: 25468701
[TBL] [Abstract][Full Text] [Related]
35. Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic.
Hasankhani A; Bahrami A; Sheybani N; Aria B; Hemati B; Fatehi F; Ghaem Maghami Farahani H; Javanmard G; Rezaee M; Kastelic JP; Barkema HW
Front Immunol; 2021; 12():789317. PubMed ID: 34975885
[TBL] [Abstract][Full Text] [Related]
36. Rumen and Fecal Microbial Community Structure of Holstein and Jersey Dairy Cows as Affected by Breed, Diet, and Residual Feed Intake.
Noel SJ; Olijhoek DW; Mclean F; Løvendahl P; Lund P; Højberg O
Animals (Basel); 2019 Jul; 9(8):. PubMed ID: 31362392
[TBL] [Abstract][Full Text] [Related]
37. Analysis of biological networks and biological pathways associated with residual feed intake in beef cattle.
Karisa B; Moore S; Plastow G
Anim Sci J; 2014 Apr; 85(4):374-87. PubMed ID: 24373146
[TBL] [Abstract][Full Text] [Related]
38. Residual feed intake of lactating Holstein-Friesian cows predicted from high-density genotypes and phenotyping of growing heifers.
Davis SR; Macdonald KA; Waghorn GC; Spelman RJ
J Dairy Sci; 2014 Mar; 97(3):1436-45. PubMed ID: 24472127
[TBL] [Abstract][Full Text] [Related]
39. Gene expression profiling of hormonal regulation related to the residual feed intake of Holstein cattle.
Xi YM; Yang Z; Wu F; Han ZY; Wang GL
Biochem Biophys Res Commun; 2015 Sep; 465(1):19-25. PubMed ID: 26231801
[TBL] [Abstract][Full Text] [Related]
40. In-Depth Duodenal Transcriptome Survey in Chickens with Divergent Feed Efficiency Using RNA-Seq.
Yi G; Yuan J; Bi H; Yan W; Yang N; Qu L
PLoS One; 2015; 10(9):e0136765. PubMed ID: 26418546
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
