Tenhunen, S., Thomasen, J. R., Sørensen, L. P., Berg, P. & Kargo, M. (2024). Genomic Analysis of Inbreeding and Coancestry in Nordic Jersey and Holstein Dairy Cattle Populations. Journal of Dairy Science, 107(8), 5897-5912. https://doi.org/10.3168/jds.2023-24553

Tang, X., Liu, P., Luo, N., Wen, J., Li, H., Zhao, G. & An, B. (2024). Mining Candidate Genes and Identifying Risk Factors for Leg Disease in Broilers: A Mendelian Randomization Study. International Journal of Molecular Sciences , 25(16), Article 8890. https://doi.org/10.3390/ijms25168890

Zaalberg, R. M., Nielsen, H. M., Noer, N. K., Schou, T. M., Jensen, K., Thormose, S., Kargo, M. & Slagboom, M. (2024). A bio-economic model for estimating economic values of important production traits in the black soldier fly (Hermetia illucens). Journal of Insects as Food and Feed, 10(8), 1411-1421. https://doi.org/10.1163/23524588-00001126

Chu, T. T., Kristensen, P. S. & Jensen, J. (2024). Simulation of functional additive and non-additive genetic effects using statistical estimates from quantitative genetic models. Heredity, 133(1), 33-42. https://doi.org/10.1038/s41437-024-00690-5

Roy, D. B., Alison, J., August, T. A., Bélisle, M., Bjerge, K., Bowden, J. J., Bunsen, M. J., Cunha, F., Geissmann, Q., Goldmann, K., Gomez-Segura, A., Jain, A., Huijbers, C., Larrivée, M., Lawson, J. L., Mann, H. M., Mazerolle, M. J., McFarland, K. P., Pasi, L. ... Høye, T. T. (2024). Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects. Philosophical Transactions of the Royal Society B: Biological Sciences, 379(1904), Article 20230108. https://doi.org/10.1098/rstb.2023.0108

Li, T., Xu, H., Teng, S., Suo, M., Bahitwa, R., Xu, M., Qian, Y., Ramstein, G. P., Song, B., Buckler, E. S. & Wang, H. (2024). Modeling 0.6 million genes for the rational design of functional cis-regulatory variants and de novo design of cis-regulatory sequences. Proceedings of the National Academy of Sciences of the United States of America, 121(26), Article e2319811121. https://doi.org/10.1073/pnas.2319811121

Zhao, F., Xie, R., Fang, L., Xiang, R., Yuan, Z., Liu, Y. & Wang, L. (2024). Analysis of 206 whole-genome resequencing reveals selection signatures associated with breed-specific traits in Hu sheep. Evolutionary Applications, 17(6), Article e13697. https://doi.org/10.1111/eva.13697

Jensen, I. T., Janss, L., Radutoiu, S. & Waagepetersen, R. (2024). Compositionally aware estimation of crosscorrelations for microbiome data. PLOS ONE, 19(6), Article e0305032. https://doi.org/10.1371/journal.pone.0305032

Giagnoni, G., Lassen, J., Lund, P., Foldager, L., Johansen, M. & Weisbjerg, M. R. (2024). Feed intake in housed dairy cows: validation of a three-dimensional camera−based feed intake measurement system. ANIMAL, 18(6), Article 101178. https://doi.org/10.1016/j.animal.2024.101178

Legarra, A., Bermann, M., Mei, Q. & Christensen, O. F. (2024). Redefining and interpreting genomic relationships of metafounders. Genetics, selection, evolution : GSE, 56(1), Article 34. https://doi.org/10.1186/s12711-024-00891-w

Legarra, A., Bermann, M., Mei, Q. & Christensen, O. F. (2024). Estimating genomic relationships of metafounders across and within breeds using maximum likelihood, pseudo-expectation-maximization maximum likelihood and increase of relationships. Genetics Selection Evolution, 56(1), 35. Article 35. https://doi.org/10.1186/s12711-024-00892-9

Tang, Y., Zhang, J., Li, W., Liu, X., Chen, S., Mi, S., Yang, J., Teng, J., Fang, L. & Yu, Y. (2024). Identification and characterization of whole blood gene expression and splicing quantitative trait loci during early to mid-lactation of dairy cattle. BMC Genomics, 25(1), Article 445. https://doi.org/10.1186/s12864-024-10346-7

Yang, L., Yin, H., Bai, L., Yao, W., Tao, T., Zhao, Q., Gao, Y., Teng, J., Xu, Z., Lin, Q., Diao, S., Pan, Z., Guan, D., Li, B., Zhou, H., Zhou, Z., Zhao, F., Wang, Q., Pan, Y. ... Liu, G. E. (2024). Mapping and functional characterization of structural variation in 1060 pig genomes. Genome Biology, 25(1), Article 116. https://doi.org/10.1186/s13059-024-03253-3

Zaalberg, R. M., Clasen, J. B., Bovbjerg, H., Jensen, J., Villumsen, T. M. & Chu, T. T. (2024). The effects of phenotyping and genotyping strategies, and the use of conventional or organic sires on genetic gain in an organic pig population. Livestock Science, 283, Article 105456. https://doi.org/10.1016/j.livsci.2024.105456

Kazemi Naeini, M., Akbarzadeh, M., Kazemi, I., Speed, D. & Hosseini, S. M. (2024). Using the Bayesian variational spike and slab model in a genome-wide association study for finding associated loci with bipolar disorder. Annals of Human Genetics, 88(3), 212-246. https://doi.org/10.1111/ahg.12538

Song, H., Chu, J., Li, W., Li, X., Fang, L., Han, J., Zhao, S. & Ma, Y. (2024). A Novel Approach Utilizing Domain Adversarial Neural Networks for the Detection and Classification of Selective Sweeps. Advanced Science, 11(14), Article 2304842. https://doi.org/10.1002/advs.202304842

Speed, D. & Evans, D. M. (2024). Estimating disease heritability from complex pedigrees allowing for ascertainment and covariates. American Journal of Human Genetics, 111(4), 680-690. https://doi.org/10.1016/j.ajhg.2024.02.010

Gebreyesus, G., Secher, J. B., Lund, M. S., Kupisiewicz, K., Ivask, M., Hallap, T., Pärn, P. & Su, G. (2024). Genetic parameters for bull effects on in vitro embryo production (IVP) and relationship between semen quality traits and IVP performance. Animal Reproduction Science, 263, 107436. Article 107436. https://doi.org/10.1016/j.anireprosci.2024.107436

Lund, P., Hojberg, O., Børsting, C. F., Nielsen, M. O., Villumsen, T. M. & Weisbjerg, M. R. (2024). Kan koen blive klimavenlig? Køer og andre drøvtyggere producerer metan, men gennem fodringsstrategier kan emissionen reduceres. Dansk Kemi, 105(2), 16-18.

Bernstorff, M., Vistisen, S. T. & Enevoldsen, K. C. (2024). Natural language processing for electronic health records in anaesthesiology: an introduction to clinicians with recommendations and pitfalls. Journal of Clinical Monitoring and Computing, 38(2), 241-245. https://doi.org/10.1007/s10877-024-01128-3

Tao, K., Jensen, I. T., Zhang, S., Villa-Rodríguez, E., Blahovska, Z., Salomonsen, C. L., Martyn, A., Björgvinsdóttir, Þ. N., Kelly, S., Janss, L., Glasius, M., Waagepetersen, R. & Radutoiu, S. (2024). Nitrogen and Nod factor signaling determine Lotus japonicus root exudate composition and bacterial assembly. Nature Communications, 15(1), Article 3436. https://doi.org/10.1038/s41467-024-47752-0

Noer, N. K., Rohde, P. D., Sørensen, P., Bahrndorff, S. & Kristensen, T. N. (2024). Diurnal variation in genetic parameters for locomotor activity in Drosophila melanogaster assessed under natural thermal conditions. Journal of Evolutionary Biology, 37(3), 336-345. https://doi.org/10.1093/jeb/voae020

Shewale, A., Mokhade, A., Lipare, A. & Bokde, N. D. (2024). Efficient Techniques for Residential Appliances Scheduling in Smart Homes for Energy Management Using Multiple Knapsack Problem. Arabian Journal for Science and Engineering, 49(3), 3793-3813. https://doi.org/10.1007/s13369-023-08178-w

Rovere, G., de Los Campos, G., Gebreyesus, G., Savegnago, R. P. & Buitenhuis, A. J. (2024). Energy balance of dairy cows predicted by mid-infra-red spectra data of milk using Bayesian approaches. Journal of Dairy Science, 107(3), 1561-1576. https://doi.org/10.3168/jds.2023-23772

Degalez, F., Charles, M., Foissac, S., Zhou, H., Guan, D., Fang, L., Klopp, C., Allain, C., Lagoutte, L., Lecerf, F., Acloque, H., Giuffra, E., Pitel, F. & Lagarrigue, S. (2024). Enriched atlas of lncRNA and protein-coding genes for the GRCg7b chicken assembly and its functional annotation across 47 tissues. Scientific Reports, 14(1), Article 6588. https://doi.org/10.1038/s41598-024-56705-y

Houlahan, K., Schenkel, F. S., Miglior, F., Jamrozik, J., Stephansen, R. B., González-Recio, O., Charfeddine, N., Segelke, D., Butty, A. M., Stratz, P., VandeHaar, M. J., Tempelman, R. J., Weigel, K., White, H., Peñagaricano, F., Koltes, J. E., Santos, J. E. P., Baldwin, R. L. & Baes, C. F. (2024). Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle. Journal of Dairy Science, 107(3), 1523-1534. https://doi.org/10.3168/jds.2022-23124

Tao, H., Abba, S. I., Al-Areeq, A. M., Tangang, F., Samantaray, S., Sahoo, A., Siqueira, H. V., Maroufpoor, S., Demir, V., Dhanraj Bokde, N., Goliatt, L., Jamei, M., Ahmadianfar, I., Bhagat, S. K., Halder, B., Guo, T., Helman, D. S., Ali, M., Sattar, S. ... Yaseen, Z. M. (2024). Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions. Engineering Applications of Artificial Intelligence, 129, Article 107559. https://doi.org/10.1016/j.engappai.2023.107559

Wang, A., Su, G., Brito, L. F., Zhang, H., Shi, R., Liu, D., Guo, G. & Wang, Y. (2024). Investigating the relationship between fluctuations in daily milk yield as resilience indicators and health traits in Holstein cattle. Journal of Dairy Science, 107(3), 1535-1548. https://doi.org/10.3168/jds.2023-23495

van Staaveren, N., de Oliveira, H., Houlahan, K., Chud, T., Oliveira, G., Hailemariam, D., Kistemaker, G., Miglior, F., Plastow, G., Schenkel, F. S., Cerri, R., Sirard, M.-A., Stothard, P., Pryce, J., Butty, A., Stratz, P., Abdalla, E., Segelke, D., Stamer, E. ... Baes, C. F. (2024). The Resilient Dairy Genome Project: a general overview of methods and objectives related to feed efficiency and methane emissions. Journal of Dairy Science, 107(3), 1510-1522. https://doi.org/10.3168/jds.2022-22951

Paina, C., Fois, M., Asp, T., Jensen, J., Hansen, P. B. & Rohde, P. D. (2024). The soil microbiome of Lolium perenne L. depends on host genotype, is modified by nitrogen level and varies across season. Scientific Reports, 14(1), Article 5767. https://doi.org/10.1038/s41598-024-56353-2

Bokde, N. D., Patil, P. K., Sengupta, S., Sawant, M. & Feijóo-Lorenzo, A. E. (2024). VedicDateTime: An R package to implement Vedic calendar system. Multimedia Tools and Applications, 83(11), 32141-32157. https://doi.org/10.1007/s11042-023-16553-w

Chen, S., Liu, S., Shi, S., Yin, H., Tang, Y., Zhang, J., Li, W., Liu, G., Qu, K., Ding, X., Wang, Y., Liu, J., Zhang, S., Fang, L. & Yu, Y. (2024). Cross-Species Comparative DNA Methylation Reveals Novel Insights into Complex Trait Genetics among Cattle, Sheep, and Goats. Molecular Biology and Evolution, 41(2), Article msae003. https://doi.org/10.1093/molbev/msae003

Londhe, D. S., Katpatal, Y. B., Mukesh, M. S. & Bokde, N. D. (2024). Vegetation dynamics and its driving factors in agro-climatic zones of Upper Bhima Sub-basin, Western India. International Journal of Environmental Science and Technology, 21(3), 2367-2382. https://doi.org/10.1007/s13762-023-05094-2

Madsen, M. D., Kristensen, P. S., Mahmood, K., Thach, T., Mohlfeld, M., Orabi, J., Sarup, P., Jahoor, A., Hovmøller, M. S., Rodriguez-Algaba, J. & Jensen, J. (2024). Scald resistance in hybrid rye (Secale cereale): genomic prediction and GWAS. Frontiers in Plant Science, 15, Article 1306591. https://doi.org/10.3389/fpls.2024.1306591

Tessema, B. B., Raffo, M. A., Guo, X., Svane, S. F., Krusell, L., Jensen, J. D., Ruud, A. K., Malinowska, M., Thorup-Kristensen, K. & Jensen, J. (2024). Genomic prediction for root and yield traits of barley under a water availability gradient: a case study comparing different spatial adjustments. Plant Methods, 20(1), Article 8. https://doi.org/10.1186/s13007-023-01121-y

Westwood, M. L., Geissmann, Q., O'Donnell, A. J., Rayner, J., Schneider, W., Zuk, M., Bailey, N. W. & Reece, S. E. (2024). Machine learning reveals singing rhythms of male Pacific field crickets are clock controlled. Behavioral Ecology, 35(1), Article arad098. https://doi.org/10.1093/beheco/arad098

The PigGTEx Consortium (2024). A compendium of genetic regulatory effects across pig tissues. Nature Genetics, 56(1), 112-123. https://doi.org/10.1038/s41588-023-01585-7

Bouquet, A. E. R., Slagboom, M., Thomasen, J. R., Friggens, N. C., Kargo, M. & Puillet, L. (2024). Combined mechanistic and genetic modelling to benchmark body reserve traits as proxies of dairy cows’ lifetime efficiency in grass-based production systems. Animal, 18(1), Article 101035. https://doi.org/10.1016/j.animal.2023.101035

Nawoya, S., Ssemakula, F., Akol, R., Geissmann, Q., Karstoft, H., Bjerge, K., Mwikirize, C., Katumba, A. & Gebreyesus, G. (2024). Computer vision and deep learning in insects for food and feed production: A review. Computers and Electronics in Agriculture, 216, Article 108503. https://doi.org/10.1016/j.compag.2023.108503

Mukherjee, A., Cai, Z. & Mukherjee, S. (2024). Editorial: Application of genomics in livestock populations under selection or conservation. Frontiers in Genetics, 15, Article 1363839. https://doi.org/10.3389/fgene.2024.1363839

Zeng, H., Zhang, W., Lin, Q., Gao, Y., Teng, J., Xu, Z., Cai, X., Zhong, Z., Wu, J., Liu, Y., Diao, S., Wei, C., Gong, W., Pan, X., Li, Z., Huang, X., Chen, X., Du, J., Zhao, F. ... PigGTEx Consortium (2024). PigBiobank: a valuable resource for understanding genetic and biological mechanisms of diverse complex traits in pigs. Nucleic Acids Research, 52(D1), D980-D989. https://doi.org/10.1093/nar/gkad1080

Kristensen, T. N., Laursen, S. F. & Hansen, L. S. (2024). Advances in sustainable food production through optimization of insect farming. EU Researcher, 40, 28-29. https://issuu.com/euresearcher/docs/optimization_of_insect_production_for_animal_feed_

Guillenea, A., Lund, M. S., Evans, R., Boerner, V. & Karaman, E. (2023). A breed-of-origin of alleles model that includes crossbred data improves predictive ability for crossbred animals in a multi-breed population. Genetics, selection, evolution : GSE, 55(1), Article 34. https://doi.org/10.1186/s12711-023-00806-1

Zira, S., Bouquet, A. E. R., Rydhmer, L., Kargo, M. & Puillet, L. (2023). Carbon footprint based on lifetime productivity for future cows selected for resilience to climate-related disturbances. Journal of Dairy Science, 106(12), 8953-8968. https://doi.org/10.3168/jds.2023-23492

Wang, X., Li, W., Feng, X., Li, J., Liu, G. E., Fang, L. & Yu, Y. (2023). Correction: Harnessing male germline epigenomics for the genetic improvement in cattle . Journal of Animal Science and Biotechnology, 14(1), Article 110. https://doi.org/10.1186/s40104-023-00917-1

Romé, H., Chu, T. T., Marois, D., Huang, C. H., Madsen, P. & Jensen, J. (2023). Estimation and consequences of direct-maternal genetic and environmental covariances in models for genetic evaluation in broilers. Genetics Selection Evolution, 55(1), Article 58. https://doi.org/10.1186/s12711-023-00829-8

Bornhofen, E., Fé, D., Nagy, I., Lenk, I., Greve, M., Didion, T., Jensen, C. S., Asp, T. & Janss, L. (2023). Genetic architecture of inter-specific and -generic grass hybrids by network analysis on multi-omics data. BMC Genomics, 24(1), Article 213. https://doi.org/10.1186/s12864-023-09292-7

Manzanilla-Pech, C. I. V., Stephansen, R. B. & Lassen, J. (2023). Genetic parameters for feed intake and body weight in dairy cattle using high-throughput 3-dimensional cameras in Danish commercial farms. Journal of Dairy Science, 106(12), 9006-9015. https://doi.org/10.3168/jds.2023-23405

Mei, Q., Liu, H., Zhao, S., Xiang, T. & Christensen, O. F. (2023). Genomic evaluation for two-way crossbred performance in cattle. Genetics Selection Evolution, 55(1), Article 17. https://doi.org/10.1186/s12711-023-00792-4

Liu, C., Huang, R., Su, G., Hou, L., Zhou, W., Liu, Q., Qiu, Z., Zhao, Q. & Li, P. (2023). Introgression of pigs in Taihu Lake region possibly contributed to the improvement of fertility in Danish Large White pigs. BMC Genomics, 24(1), Article 733. https://doi.org/10.1186/s12864-023-09860-x

Guo, X., Sarup, P., Jahoor, A., Jensen, J. & Christensen, O. F. (2023). Metabolomic-genomic prediction can improve prediction accuracy of breeding values for malting quality traits in barley. Genetics Selection Evolution, 55(1), Article 61. https://doi.org/10.1186/s12711-023-00835-w

Stephansen, R. B., Martin, P., Manzanilla-Pech, C. I. V., Gredler-Grandl, B., Sahana, G., Madsen, P., Weigel, K., Tempelman, R. J., Peñagaricano, F., Gaddis, K. L. P., White, H. M., Santos, J. E. P., Koltes, J. E., Schenkel, F., Hailemariam, D., Plastow, G., Abdalla, E., VandeHaar, M., Veerkamp, R. F. ... Lassen, J. (2023). Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe. Journal of Dairy Science, 106(12), 9078-9094. https://doi.org/10.3168/jds.2023-23330, https://doi.org/10.3168/jds.2023-23330

Kristensen, P. S., Sarup, P., Fé, D., Orabi, J., Snell, P., Ripa, L., Mohlfeld, M., Chu, T. T., Herrström, J., Jahoor, A. & Jensen, J. (2023). Prediction of additive, epistatic, and dominance effects using models accounting for incomplete inbreeding in parental lines of hybrid rye and sugar beet. Frontiers in Plant Science, 14, Article 1193433. https://doi.org/10.3389/fpls.2023.1193433

Eiríksson, J. H., Su, G., Strandén, I. & Christensen, O. F. (2023). Segregation between breeds and local breed proportions in genetic and genomic models for crossbreds. Genetics Selection Evolution, 55(1), Article 45. https://doi.org/10.1186/s12711-023-00810-5