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For: Banerjee P, Carmelo VAO, Kadarmideen HN. Genome-Wide Epistatic Interaction Networks Affecting Feed Efficiency in Duroc and Landrace Pigs. Front Genet 2020;11:121. [PMID: 32184802 DOI: 10.3389/fgene.2020.00121] [Cited by in Crossref: 15] [Cited by in F6Publishing: 18] [Article Influence: 7.5] [Reference Citation Analysis]
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7 Verma RK, Alena K, Mishra A, Ivanchenko M, Jalan S. Role of mitochondrial genetic interactions in determining adaptation to high altitude in human population around the globe.. [DOI: 10.1101/2021.06.21.449348] [Reference Citation Analysis]
8 Xiao C, Deng J, Zeng L, Sun T, Yang Z, Yang X. Transcriptome Analysis Identifies Candidate Genes and Signaling Pathways Associated With Feed Efficiency in Xiayan Chicken. Front Genet 2021;12:607719. [PMID: 33815460 DOI: 10.3389/fgene.2021.607719] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
9 Chen W, Alexandre PA, Ribeiro G, Fukumasu H, Sun W, Reverter A, Li Y. Identification of Predictor Genes for Feed Efficiency in Beef Cattle by Applying Machine Learning Methods to Multi-Tissue Transcriptome Data. Front Genet 2021;12:619857. [PMID: 33664767 DOI: 10.3389/fgene.2021.619857] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
10 Hodge MJ, de Las Heras-Saldana S, Rindfleish SJ, Stephen CP, Pant SD. Characterization of Breed Specific Differences in Spermatozoal Transcriptomes of Sheep in Australia. Genes (Basel) 2021;12:203. [PMID: 33573244 DOI: 10.3390/genes12020203] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
11 Carmelo VAO, Kadarmideen HN. Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs. PLoS One 2020;15:e0239143. [PMID: 32941478 DOI: 10.1371/journal.pone.0239143] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
12 Zhao X, Hu H, Lin H, Wang C, Wang Y, Wang J. Muscle Transcriptome Analysis Reveals Potential Candidate Genes and Pathways Affecting Intramuscular Fat Content in Pigs. Front Genet 2020;11:877. [PMID: 32849841 DOI: 10.3389/fgene.2020.00877] [Cited by in Crossref: 16] [Cited by in F6Publishing: 20] [Article Influence: 8.0] [Reference Citation Analysis]
13 Banerjee P, Carmelo VAO, Kadarmideen HN. Integrative Analysis of Metabolomic and Transcriptomic Profiles Uncovers Biological Pathways of Feed Efficiency in Pigs. Metabolites 2020;10:E275. [PMID: 32640603 DOI: 10.3390/metabo10070275] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
14 Banerjee P, Okstoft Carmelo VA, Kadarmideen HN. Integrative Analysis of Metabolomic and Transcriptomic Profiles Uncovers Biological Mechanism of Feed Efficiency in Pigs.. [DOI: 10.1101/2020.05.21.108050] [Reference Citation Analysis]
15 Wang X, Kadarmideen HN. Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs. Metabolites 2020;10:E201. [PMID: 32429265 DOI: 10.3390/metabo10050201] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
16 Carmelo VA, Kadarmideen HN. Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs.. [DOI: 10.1101/2020.04.17.047027] [Reference Citation Analysis]