Publications

Peer-reviewed publications at QGG

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Hansen, L. S., Laursen, S. F., Bahrndorff, S., Kargo, M., Sørensen, J. G., Sahana, G., Nielsen, H. M. & Kristensen, T. N. (2024). Selective breeding in commercial insects with a house fly model system. Abstract from Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya. https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf

Manunza, A., Ramirez-Diaz, J., Guldbrandtsen, B., Schönherz, A. A., Cozzi, P., Kusza, S., Sahana, G. & Stella, A. (2024). Sheep along the trading routes: what may we tell from their demographic history? A case study from Hungary. In EAAP 2024 Book of Abstracts (pp. 421). EAAP. https://docs.eaap.org/boa/2024_Florence_EAAP_Book_Abstracts.pdf

Kempe, R. M., Koivula, M., Pitkänen, T. J., Stephansen, R. B., Pösö, J., Nielsen, U. S., Fikse, W. F., Aamand, G. P. & Lidauer, M. H. (2024). Single-step genomic prediction models for metabolic body weight in Nordic Holstein, Red dairy cattle, and Jersey. In Proceedings of the 2024 Interbull Meeting (pp. 92-96). Swedish University of Agricultural Sciences. https://journal.interbull.org/index.php/ib/article/view/1935

Ssemakula, F., Kabuye, A., Geoffrey, S., Akol, R., Mwikirize, C., Nkirote Kunyanga , C., Cheruiyot Bett , R., Nakimbugwe, D., Katumba, A. & Gebreyesus, G. (2024). Technological prediction of protein and fat in black soldier fly larvae. Abstract from Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya. https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf

Hansen, L. S., Laursen, S. F., Bahrndorff, S., Sørensen, J. G., Sahana, G., Kristensen, T. N. & Nielsen, H. M. (2024). The unpaved road towards efficient selective breeding in insects for food and feed. https://arxiv.org/abs/2406.16364

Bonifazi, R., Heidaritabar, M., Barlow, L., Bouwman, A. C., Plastow, G., Stothard, P., Chen, L., Basarab, J., Li, C., Karaman, E., Moreira, GCM. & Gredler-Grandl, B. (2024). Within and across population genomic predictions incorporating functional genomic annotations. 73-74.

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

Wang, X., Gao, Y., Li, C. J., Fang, L., Liu, G. E., Zhao, X., Zhang, Y., Cai, G., Xue, G., Liu, Y., Wang, L., Zhang, F., Wang, K., Zhang, M., Li, R., Gao, Y. & Li, J. (2023). The single-cell transcriptome and chromatin accessibility datasets of peripheral blood mononuclear cells in Chinese holstein cattle. BMC genomic data, 24(1), Article 39. https://doi.org/10.1186/s12863-023-01139-0

Zhao, P., Gu, L., Gao, Y., Pan, Z., Liu, L., Li, X., Zhou, H., Yu, D., Han, X., Qian, L., Liu, G. E., Fang, L. & Wang, Z. (2023). Young SINEs in pig genomes impact gene regulation, genetic diversity, and complex traits. Communications Biology, 6(1), Article 894. https://doi.org/10.1038/s42003-023-05234-x

Enevoldsen, K., Hansen, L., Nielsen, D. S., Egebæk, R., Holm, S., Nielsen, M. C., Bernstorff, M., Larsen, R., Jørgensen, P. B., Højmark-Bertelsen, M., Vahlstrup, P. B., Møldrup-Dalum, P. & Nielbo, K. L. (2023). Danish Foundation Models: Danish Foundation Models. ArXiv. https://arxiv.org/abs/2311.07264

Bokde, N. D., Milkevych, V., Nielsen, R. K., Villumsen, T. M. & Sahana, G. (2023). A novel approach for anomaly detection in dairy cow gas emission records. Computers and Electronics in Agriculture, 214, Article 108286. https://doi.org/10.1016/j.compag.2023.108286

Thomasen, J. R., Lassen, J. & Borchersen, S. (2023). Camera technology to bring large scale data from commercial herds. Poster session presented at 15th World Holstein Friesian Federation (WHFF) Conference, Puy-du-Fou, France. https://whff.info/wp-content/uploads/2023/11/WHFF_JornRindThomasen_CameraTech.pdf

Forte, F. P., Malinowska, M., Nagy, I., Schmid, J., Dijkwel, P., Hume, D. E., Johnson, R. D., Simpson, W. R. & Asp, T. (2023). Corrigendum: Methylome changes in Lolium perenne associated with long-term colonisation by the endophytic fungus Epichloë sp. LpTG-3 strain AR37 (Frontiers in Plant Science, (2023), 14, (1258100), 10.3389/fpls.2023.1258100). Frontiers in Plant Science, 14, Article 1332690. https://doi.org/10.3389/fpls.2023.1332690

Rohde, P. D., Fourie Sørensen, I. & Sørensen, P. (2023). Expanded utility of the R package, qgg, with applications within genomic medicine. Bioinformatics (Oxford, England), 39(11), Article btad656. https://doi.org/10.1093/bioinformatics/btad656

Cai, Z., Wu, X., Thomsen, B., Lund, M. S. & Sahana, G. (2023). Genome-wide association study identifies functional genomic variants associated with young stock survival in Nordic Red Dairy Cattle. Journal of Dairy Science, 106(11), 7832-7845. https://doi.org/10.3168/jds.2023-23252

Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023). Hierarchical classification of insects with multitask learning and anomaly detection. Ecological Informatics, 77, Article 102278. https://doi.org/10.1016/j.ecoinf.2023.102278

Stephansen, R. B., Manzanilla Pech, C. I. V., Gebreyesus, G., Sahana, G. & Lassen, J. (2023). Prediction of body condition in Jersey dairy cattle from 3D-images using machine learning techniques. Journal of Animal Science, 101, Article skad376. https://doi.org/10.1093/jas/skad376

Sørensen, J. T. (Ed.), Jensen, M. B., Thomsen, P. T., Kongsted, H., Pedersen, L. J., Riber, A. B., Kargo, M., Hein, L., Villumsen, T. M., Manzanilla Pech, C. I. V., Buitenhuis, A. J. & Christensen, O. F. (2023). Samspil mellem klima, miljø og dyrevelfærd: En vurdering af konsekvenser for dyrevelfærden af tiltag på besætningsniveau til reduktion af husdyrproduktionens klima- og miljøpåvirkning. DCA - Nationalt Center for Fødevarer og Jordbrug. DCA rapport No. 222 https://dcapub.au.dk/djfpublikation/djfpdf/DCArapport222.pdf

Balbuena, L., Peters, E. & Speed, D. (2023). Using polygenic risk scores to investigate the evolution of smoking and mental health outcomes in UK biobank participants. Acta Psychiatrica Scandinavica, 148(5), 447-456. https://doi.org/10.1111/acps.13601, https://doi.org/10.1111/acps.13601

Friggens, N. C., Ithurbide, M. & Bouquet, A. E. R. (2023). Novel traits related to productive life. Abstract from 45th ADSA Discover Conference, Itasca, Illinois, United States.

Dorosh, R., Allen, J., He, Z., Ninatanta, C., Coleman, J., Spieker, J., Tuck, E., Kurtz, J., Zhang, Q., Whiting, M. D., Luo, J., Karkee, M. & Luo, M. (2023). Design, Modeling, and Control of a Low-Cost and Rapid Response Soft-Growing Manipulator for Orchard Operations. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 4184-4190. https://doi.org/10.1109/IROS55552.2023.10341507

Xiang, R., Fang, L., Liu, S., Macleod, I. M., Liu, Z., Breen, E. J., Gao, Y., Liu, G. E., Tenesa, A., CattleGTEx Consortium, Mason, B. A., Chamberlain, A. J., Wray, N. R. & Goddard, M. E. (2023). Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle. Cell Genomics, 3(10), Article 100385. https://doi.org/10.1016/j.xgen.2023.100385

Li, J., Zhao, T., Guan, D., Pan, Z., Bai, Z., Teng, J., Zhang, Z., Zheng, Z., Zeng, J., Zhou, H., Fang, L. & Cheng, H. (2023). Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits. Cell Genomics, 3(10), Article 100390. https://doi.org/10.1016/j.xgen.2023.100390

Ahmad, S., Drag, M. H., Mohamad Salleh, S., Cai, Z. & Nielsen, M. O. (2023). Gene coexpression network analysis reveals perirenal adipose tissue as an important target of prenatal malnutrition in sheep. Physiological Genomics, 55(9), 392-413. https://doi.org/10.1152/physiolgenomics.00128.2022

Forte, F. P., Malinowska, M., Nagy, I., Schmid, J., Dijkwel, P., Hume, D. E., Johnson, R. D., Simpson, W. R. & Asp, T. (2023). Methylome changes in Lolium perenne associated with long-term colonisation by the endophytic fungus Epichloë sp. LpTG-3 strain AR37. Frontiers in Plant Science, 14, Article 1258100. https://doi.org/10.3389/fpls.2023.1258100, https://doi.org/10.3389/fpls.2023.1258100

Boggio, G. M., Christensen, O. F., Legarra, A., Meynadier, A. & Marie-Etancelin, C. (2023). Microbiability of milk composition and genetic control of microbiota effects in sheep. Journal of Dairy Science, 106(9), 6288-6298. https://doi.org/10.3168/jds.2022-22948

Jensen, N. E., Vestergaard, M., Kargo, M., Keto, L., Ertbjerg, P., Thorkelsson, G., Gudjónsdóttir, M., Kjetså, M., Honkatukia, M., Egelandsdal, B., Svartedal, N., Røe, M., Fikse, F. W., H. Karlsson, A., Hessle, A. & Therkildsen, M. (2023). Carcass characteristics of Nordic native cattle breeds. Abstract from 69th International Congress of Meat Science and Technology (ICoMST), Padova, Italy.

H. Karlsson, A., Svartedal, N., Kjetså, M., Egelandsdal, B., Røe, M., Thorkelsson, G., Guðjónsdóttir, M., Honkatukia, M., Keto, L., Ertbjerg, P., Hessle, A., Vestergaard, M., Kargo, M., Arvidssson-Segerkvist, K. & Therkildsen, M. (2023). Carcass characteristics of Swedish native sheep breeds. Abstract from 69th International Congress of Meat Science and Technology (ICoMST), Padova, Italy.

Londhe, D. S., Katpatal, Y. B., Singh, C. K. & Bokde, N. D. (2023). Assessment of vegetation variation and its response to ENSO and IOD in the semi-arid ecosystem of Western India. Journal of Water and Climate Change, 14(8), 2642-2662. https://doi.org/10.2166/wcc.2023.010

Buitenhuis, A. J., Hein, L., Sørensen, L. P. & Kargo, M. (2023). Correlation between breeding values for milk fatty acids and Nordic Total Merit index traits for Danish Holstein and Danish Jersey. Journal of Dairy Science, 106(8), 5554-5561. https://doi.org/10.3168/jds.2022-22575, https://doi.org/10.3168/jds.2022-22575

Buitenhuis, A. J. & Poulsen, N. A. (2023). Estimation of heritability for milk urea and genetic correlations with milk production traits in 3 Danish dairy breeds. Journal of Dairy Science, 106(8), 5562-5569. https://doi.org/10.3168/jds.2022-22798

Sahana, G., Cai, Z., Sanchez, M. P., Bouwman, A. C. & Boichard, D. (2023). Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle. Journal of Dairy Science, 106(8), 5218-5241. https://doi.org/10.3168/jds.2022-22694

Bouquet, A. E. R., Nielsen, H. M., Milkevych, V., Kargo, M., Thomasen, J. R. & Slagboom, M. (2023). Optimizing dairy cattle breeding goals to improve production and udder health of crossbred cows. In Book of Abstracts of the 74th Annual Meeting of the European Federation of Animal Science Wageningen Academic Publishers.

Londhe, D. S., Katpatal, Y. B. & Bokde, N. D. (2023). Performance Assessment of Bias Correction Methods for Precipitation and Temperature from CMIP5 Model Simulation. Applied Sciences (Switzerland), 13(16), Article 9142. https://doi.org/10.3390/app13169142

Thorup, V. M., Munksgaard, L., Terré, M., Henriksen, J. C. S., Weisbjerg, M. R. & Lovendahl, P. (2023). The relationship between feed efficiency and behaviour differs between lactating Holstein and Jersey cows. Journal of Dairy Research, 90(3), 257-260. https://doi.org/10.1017/S0022029923000420

Jain, S. K., Bhatia, R., Shrivastava, N., Salunke, S., Hashmi, M. F. & Bokde, N. D. (2023). Virtual Grid-Based Routing for Query-Driven Wireless Sensor Networks. Future Internet, 15(8), Article 259. https://doi.org/10.3390/fi15080259

Nielsen, B., Horndrup, L. V., Turner, S. P., Christensen, O. F., Nielsen, H. M. & Ask, B. (2023). Selection for social genetic effects in purebred pigs improves behaviour and handling of their crossbred progeny. Genetics, selection, evolution : GSE, 55(1), 54. Article 54. https://doi.org/10.1186/s12711-023-00828-9

Ning, M., Zhao, Y., Dai, D., Yao, C., Liu, H., Fang, L., Wang, B., Zhang, Y. & Cao, J. (2023). Gene co-expression network and differential expression analyses of subcutaneous white adipose tissue reveal novel insights into the pathological mechanisms underlying ketosis in dairy cows. Journal of Dairy Science, 106(7), 5018-5028. https://doi.org/10.3168/jds.2022-22941

Raffo, M. A. & Jensen, J. (2023). Gene × gene and genotype × environment interactions in wheat. Crop Science, 63(4), 1779-1793. https://doi.org/10.1002/csc2.20986

Shi, R., Chen, Z., Su, G., Luo, H., Liu, L., Guo, G. & Wang, Y. (2023). Genomic prediction of service sire effect on female reproductive performance in Holstein cattle: A comparison between different methods, validation population and marker densities. Journal of Animal Breeding and Genetics, 140(4), 355-365. https://doi.org/10.1111/jbg.12763

Gautason, E., Sahana, G., Guldbrandtsen, B. & Berg, P. (2023). Impact of kinship matrices on genetic gain and inbreeding with optimum contribution selection in a genomic dairy cattle breeding program. Genetics Selection Evolution, 55(1), Article 48. https://doi.org/10.1186/s12711-023-00826-x

Clasen, J. B., Fikse, W. F., Su, G. & Karaman, E. (2023). Multibreed genomic prediction using summary statistics and a breed-origin-of-alleles approach. Heredity, 131(1), 33-42. https://doi.org/10.1038/s41437-023-00619-4

Schoeler, T., Speed, D., Porcu, E., Pirastu, N., Pingault, J. B. & Kutalik, Z. (2023). Participation bias in the UK Biobank distorts genetic associations and downstream analyses. Nature Human Behaviour, 7(7), 1216-1227. https://doi.org/10.1038/s41562-023-01579-9

Zhao, P., Peng, C., Fang, L., Wang, Z. & Liu, G. E. (2023). Taming transposable elements in livestock and poultry: a review of their roles and applications. Genetics Selection Evolution, 55(1), Article 50. https://doi.org/10.1186/s12711-023-00821-2

Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023). Hierarchical Classification of Insects with Multitask Learning and Anomaly Detection. bioRxiv. https://doi.org/10.1101/2023.06.29.546989

Adlam, D., Berrandou, T. E., Georges, A., Nelson, C. P., Giannoulatou, E., Henry, J., Ma, L., Blencowe, M., Turley, T. N., Yang, M. L., Chopade, S., Finan, C., Braund, P. S., Sadeg-Sayoud, I., Iismaa, S. E., Kosel, M. L., Zhou, X., Hamby, S. E., Cheng, J. ... DISCO register (2023). Genome-wide association meta-analysis of spontaneous coronary artery dissection identifies risk variants and genes related to artery integrity and tissue-mediated coagulation. Nature Genetics, 55(6), 964-972. https://doi.org/10.1038/s41588-023-01410-1

Wang, X., Li, W., Feng, X., Li, J., Liu, G. E., Fang, L. & Yu, Y. (2023). Harnessing male germline epigenomics for the genetic improvement in cattle. Journal of Animal Science and Biotechnology, 14(1), Article 76. https://doi.org/10.1186/s40104-023-00874-9

Bolormaa, S., Haile-Mariam, M., Marett, L., Miglior, F., Baes, C. F., Schenkel, F. S., Connor, E. E., Manzanilla Pech, C. I. V., Wall, E., Coffey, M., Goddard, M., MacLeod, I. & Pryce, J. E. (2023). Use of dry-matter intake recorded at multiple time periods during lactation increases the accuracy of genomic prediction for dry-matter intake and residual feed intake in dairy cattle. Animal Production Science, 63(11), 1113-1125. Article AN23022. https://doi.org/10.1071/AN23022

Wu, Y., Li, D., Hu, Y., Li, H., Ramstein, G., Zhou, S., Zhang, X., Bao, Z., Zhang, Y., Song, B., Zhou, Y., Zhou, Y., Gagnon, E., Särkinen, T., Knapp, S., Zhang, C., Städler, T., Buckler, E. S. & Huang, S. (2023). Phylogenomic discovery of deleterious mutations facilitates hybrid potato breeding. Cell, 186(11), 2313-2328.e15. https://doi.org/10.1016/j.cell.2023.04.008

Thorsgaard Jensen, I., Janss, L., Radutoiu, S. & Waagepetersen, R. (2023). Compositionally aware estimation of cross-correlations for microbiome data.

Hsu, Y. H. H., Pintacuda, G., Liu, R., Nacu, E., Kim, A., Tsafou, K., Petrossian, N., Crotty, W., Suh, J. M., Riseman, J., Martin, J. M., Biagini, J. C., Mena, D., Ching, J. K. T., Malolepsza, E., Li, T., Singh, T., Ge, T., Egri, S. B. ... Wellcome Trust Case Control Consortium (2023). Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia. iScience, 26(5), Article 106701. https://doi.org/10.1016/j.isci.2023.106701

Pan, Z., Wang, Y., Wang, M., Wang, Y., Zhu, X., Gu, S., Zhong, C., An, L., Shan, M., Damas, J., Halstead, M. M., Guan, D., Trakooljul, N., Wimmers, K., Bi, Y., Wu, S., Delany, M. E., Bai, X., Cheng, H. H. ... Zhou, H. (2023). An atlas of regulatory elements in chicken: A resource for chicken genetics and genomics. Science Advances, 9(18), Article eade1204. https://doi.org/10.1126/sciadv.ade1204

Skovbjerg, C. K., Angra, D., Robertson-Shersby-Harvie, T., Kreplak, J., Keeble-Gagnère, G., Kaur, S., Ecke, W., Windhorst, A., Nielsen, L. K., Schiemann, A., Knudsen, J., Gutierrez, N., Tagkouli, V., Fechete, L. I., Janss, L., Stougaard, J., Warsame, A., Alves, S., Khazaei, H. ... Andersen, S. U. (2023). Genetic analysis of global faba bean diversity, agronomic traits and selection signatures. Theoretical and Applied Genetics, 136(5), Article 114. https://doi.org/10.1007/s00122-023-04360-8

Lund, P., Børsting, C. F., Albrektsen, R., Nielsen, O.-K. & Villumsen, T. M., (2023). Input til udledningspostnotat om malkekvægs fordøjelse, No. 2023-0504452, 10 p., May 01, 2023.

Salimiyekta, Y., Jensen, J., Su, G. & Gebreyesus, G. (2023). Age-dependent genetic and environmental variance of semen quality in Nordic Holstein bulls. Journal of Dairy Science, 106(4), 2598-2612. https://doi.org/10.3168/jds.2022-22442

Si, J., Dai, D., Li, K., Fang, L. & Zhang, Y. (2023). A Multi-Tissue Gene Expression Atlas of Water Buffalo (Bubalus bubalis) Reveals Transcriptome Conservation between Buffalo and Cattle. Genes, 14(4), Article 890. https://doi.org/10.3390/genes14040890

Jayakodi, M., Golicz, A. A., Kreplak, J., Fechete, L. I., Angra, D., Bednář, P., Bornhofen, E., Zhang, H., Boussageon, R., Kaur, S., Cheung, K., Čížková, J., Gundlach, H., Hallab, A., Imbert, B., Keeble-Gagnère, G., Koblížková, A., Kobrlová, L., Krejčí, P. ... Andersen, S. U. (2023). The giant diploid faba genome unlocks variation in a global protein crop. Nature, 615(7953), 652-659. https://doi.org/10.1038/s41586-023-05791-5

Khaipho-Burch, M., Ferebee, T., Giri, A., Ramstein, G., Monier, B., Yi, E., Cinta Romay, M. & Buckler, E. S. (2023). Elucidating the patterns of pleiotropy and its biological relevance in maize. PLoS Genetics, 19(3), Article e1010664. https://doi.org/10.1371/journal.pgen.1010664

Zaalberg, R. M., Chu, T. T., Bovbjerg, H., Jensen, J. & Villumsen, T. M. (2023). Genetic parameters for early piglet weight, litter traits and number of functional teats in organic pigs. Animal, 17(3), Article 100717. https://doi.org/10.1016/j.animal.2023.100717

Jiang, Y. F., Wang, S., Wang, C. L., Xu, R. H., Wang, W. W., Jiang, Y., Wang, M. S., Jiang, L., Dai, L. H., Wang, J. R., Chu, X. H., Zeng, Y. Q., Fang, L. Z., Wu, D. D., Zhang, Q. & Ding, X. D. (2023). Pangenome obtained by long-read sequencing of 11 genomes reveal hidden functional structural variants in pigs. iScience, 26(3), Article 106119. https://doi.org/10.1016/j.isci.2023.106119

Christensen, B., Buitenhuis, A. J., Jacobsen, L. N., Ostenfeld, M. S. & Sørensen, E. S. (2023). The Effect of Human and Bovine Milk Osteopontin on Intestinal Caco-2 Cells: A Transcriptome Comparison. Nutrients, 15(5), Article 1166. https://doi.org/10.3390/nu15051166

Vardhan, B. V. S., Khedkar, M., Srivastava, I., Thakre, P. & Bokde, N. D. (2023). A Comparative Analysis of Hyperparameter Tuned Stochastic Short Term Load Forecasting for Power System Operator. Energies, 16(3), Article 1243. https://doi.org/10.3390/en16031243

Hein, L. & Kargo, M., (2023). Analyse af anvendelse af Blåkvægssæd i økologisk produktion, No. 2021-0244490, 58 p., Feb 09, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Tiwari, S., Sengupta, J. & Bokde, N. D. (2023). Analysis of Individual User Data Rate in a TDMA-RIS-NOMA Downlink System: Beyond the Limitation of Conventional NOMA. Electronics, 12(3), Article 618. https://doi.org/10.3390/electronics12030618

Sahu, S. K., Mokhade, A. & Bokde, N. D. (2023). An Overview of Machine Learning, Deep Learning, and Reinforcement Learning-Based Techniques in Quantitative Finance: Recent Progress and Challenges. Applied Sciences (Switzerland), 13(3), Article 1956. https://doi.org/10.3390/app13031956

Therkildsen, M., Vestergaard, M., Kargo, M., Keto, L., Ertbjerg, P., Thorkelsson, G., Gudjónsdóttir, M., Kjetså, M., Honkatukia, M., Egelandsdal, B., Svartedal, N., Røe, M., Fikse, F. W., Karlssom, A. H. & Hessle, A. (2023). Carcass characteristics of Nordic native cattle breeds. Genetic Resources, 4(7), 1-19. https://doi.org/10.46265/genresj.LWUP7415

Byg, L. M., Speed, M., Speed, D. & Østergaard, S. D. (2023). Genetic liability to bipolar disorder and body mass index: A bidirectional two-sample mendelian randomization study. Bipolar Disorders, 25(1), 25-31. https://doi.org/10.1111/bdi.13267

Raffo, M. A., Cuyabano, B. C. D., Rincent, R., Sarup, P., Moreau, L., Mary-Huard, T. & Jensen, J. (2023). Genomic prediction for grain yield and micro-environmental sensitivity in winter wheat. Frontiers in Plant Science, 13, Article 1075077. https://doi.org/10.3389/fpls.2022.1075077

Zhang, Z., Shi, S., Zhang, Q., Aamand, G. P., Lund, M. S., Su, G. & Ding, X. (2023). Improving Genomic Prediction Accuracy in the Chinese Holstein Population by Combining with the Nordic Holstein Reference Population. Animals, 13(4), Article 636. https://doi.org/10.3390/ani13040636

Boerner, V., Nguyen, T. T. T. & Nieuwhof, G. J. (2023). Integration of Interbull's multiple across-country evaluation approach breeding values into the multiple-trait single-step random regression test-day genetic evaluation for yield traits of Australian Red breeds. Journal of Dairy Science, 106(2), 1159-1167. https://doi.org/10.3168/jds.2022-21816

Salunke, S., Shrivastava, A. K., Hashmi, M. F., Ahuja, B. & Bokde, N. D. (2023). Quad Key-Secured 3D Gauss Encryption Compression System with Lyapunov Exponent Validation for Digital Images. Applied Sciences (Switzerland), 13(3), Article 1616. https://doi.org/10.3390/app13031616

Rohner, M., Manzanares, C., Yates, S., Thorogood, D., Copetti, D., Lübberstedt, T., Asp, T. & Studer, B. (2023). Fine-Mapping and Comparative Genomic Analysis Reveal the Gene Composition at the S and Z Self-incompatibility Loci in Grasses. Molecular Biology and Evolution, 40(1), Article msac259. https://doi.org/10.1093/molbev/msac259

Gebreyesus, G., Cheruiyot Bett , R., Nkirote Kunyanga , C., MBI Tanga, C., Nakimbugwe, D., Khamis, F., Kinyua, J., Muchina, K., Roos, N., Walusimbi, S., Geoffrey, S. & Sahana, G. (2023, Jan). FLYgene - Stakeholders’ workshop report in WP1. Center for Kvantitativ genetik og genomforskning (QGG), Aarhus Universitet.

Legarra, A. & Christensen, O. F. (2023). Genomic evaluation methods to include intermediate correlated features such as high-throughput or omics phenotypes. JDS Communications , 4(1), 55-60. https://doi.org/10.3168/jdsc.2022-0276

Berrandou, T.-E., Balding, D. & Speed, D. (2023). LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics. American Journal of Human Genetics, 110(1), 23-29. https://doi.org/10.1016/j.ajhg.2022.11.010

Sahana, J., Cortés-Sánchez, J. L., Sandt, V., Melnik, D., Corydon, T. J., Schulz, H., Cai, Z., Evert, K., Grimm, D. & Wehland, M. (2023). Long-Term Simulation of Microgravity Induces Changes in Gene Expression in Breast Cancer Cells. International Journal of Molecular Sciences , 24(2), Article 1181. https://doi.org/10.3390/ijms24021181

Long, E. M., Romay, M. C., Ramstein, G., Buckler, E. S. & Robbins, K. R. (2023). Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava. Frontiers in Plant Science, 13, Article 1041925. https://doi.org/10.3389/fpls.2022.1041925

Nielsen, H. M., Zaalberg, R. M., Slagboom, M., Schou, T. M., Noer, N. K. & Kargo, M. (2023). A bio-economic model for estimating economic values of important traits in the black soldier fly (Hermetia illucens). Abstract from BSF CON , Cambridge, United Kingdom.

Yousaf, M. F., Zia, M. A. B. & Naeem, M. (2023). Application of SolCAP Genotyping in Potato (Solanum tuberosum L.) Association Mapping. In Y. Shavrukov (Ed.), Plant Genotyping (pp. 415-435). Humana Press. https://doi.org/10.1007/978-1-0716-3024-2_30

Karaman, E. (2023). Bayesian gene regulatory network inference using mixture priors. Abstract from 9th Nordic-Baltic Biometric Conference, Gothenburg, Sweden. https://ibsnbr.org/NBBC23/NBBC23_Abstracts.pdf

Karaman, E., Milkevych, V. & Janss, L. (2023). Biologically informed genomic predictions with the NextGP.jl statistical analysis package. In Book of Abstracts of the 74th Annual Meeting of the European Federation of Animal Science Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-936-7

Laursen, S. F., Hansen, L. S., Bahrndorff, S., Kargo, M., Nielsen, H. M., Sahana, G., Sørensen, J. G. & Kristensen, T. N. (2023). Breeding Insects for Food and Feed. Poster session presented at Agri Food and Climate Circle 2023, København, Denmark.

Kargo, M., Buitenhuis, A. J., Kristensen, T., Nielsen, H. M., Østergaard, S., Munk, A. & Vestergaard, M. (2023). Climate beef – by more beef based on the dairy cow. Abstract from International Agri Food & Climate Circle 2023, Copenhagen, Denmark.

Jensen, S. L., Rühmann, B., Olsen, B. S., Elmengaard, B., Rasmussen, J., Larsen, J. B., Hanisch, K., Lau, L., Tøttrup, M., Jacobsen, P., Kristensen, P. K., Villekjær, S. O., Thillemann, T. M., Issa, Z. & Iversen, P. (2023). Dansk Skulderalloplastik Register: PRO er vigtig for måling af behandlingskvalitet. Ugeskrift for laeger, 185(23), 2223. https://ugeskriftet.dk/videnskab/dansk-skulderalloplastik-register-pro-er-vigtig-maling-af-behandlingskvalitet

Lassen, I. M. S., Almasi, M., Enevoldsen, K. & Kristensen-McLachlan, R. D. (2023). Detecting intersectionality in NER models: A data-driven approach. In EACL 2023 - 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Proceedings of LaTeCH-CLfL 2023 (pp. 116-127). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.latechclfl-1.13

Nielsen, H. M., Kristensen, T. N., Sahana, G., Laursen, S. F., Bahrndorff, S., Sørensen, J. G. & Hansen, L. S. (2023). Expected response to selection on larval size and development time in the housefly (Musca domestica). Abstract from
74th Annual Meeting of European Federation of Animal Science, Lyon, France.

Villumsen, T. M. & Stephansen, R. B. (2023). Fodereffektivitet og avl som redskaber i klima-arbejdet. Abstract from Kvægkongres, Herning.

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Jette Odgaard Villemoes