Publications

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Christiansen, C., Mailund , Pedersen, C. N. S. & Randers, M. (2005). Quartet Distance between General Trees. In Proceedings of International Conference on Numerical Analysis and Applied Mathematics (ICNAAM) (pp. 796-799)

Anderson, J. W., Novák, A., Sükösd, Z., Golden, M., Arunapuram, P., Edvardsson, I. & Hein, J. (2013). Quantifying variances in comparative RNA secondary structure prediction. BMC Bioinformatics, 14, Article 149. https://doi.org/10.1186/1471-2105-14-149

Østergaard, S. D., Dinesen, P. T. & Foldager, L. (2010). Quantifying the Value of Markers in Screening Programmes. European Journal of Epidemiology, 25(3), 151-4. https://doi.org/10.1007/s10654-010-9430-z

Kristensen, L. S., Wojdacz, T. K., Thestrup, B. B., Wiuf, C. H., Hager, H. & Hansen, L. L. (2009). Quality assessment of DNA derived from up to 30 years old formalin fixed paraffin embedded (FFPE) tissue for PCR-based methylation analysis using SMART-MSP and MS-HRM. B M C Cancer, 9(453), 453.

Gokuldass, A., Draghi, A., Papp, K., Borch, T., Nielsen, M., Wulff Westergaard, M. C., Andersen, R., Schina, A., Bol, K. F., Chamberlain, C. A., Presti, M., Met, Ö., Harbst, K., Lauss, M., Soraggi, S., Csabai, I., Szallasi, Z., Jönsson, G., Svane, I. M. & Donia, M. (2020). Qualitative Analysis of Tumor-Infiltrating Lymphocytes across Human Tumor Types Reveals a Higher Proportion of Bystander CD8⁺ T Cells in Non-Melanoma Cancers Compared to Melanoma. Cancers, 12(11), 1-15. Article 3344. https://doi.org/10.3390/cancers12113344

Mailund & Pedersen, C. N. S. (2004). QDist—Quartet Distance Between Evolutionary Trees. Bioinformatics, 20(10), 1636-1637.

Mailund, T. & Pedersen, C. N. S. (2004). QDist - Quartet Distance between Evolutionary Trees. Bioinformatics, 20(10), 1636-1637.

Kjeldsen, K. U., Bataillon, T., Pinel, N., De Mita, S., Lund, M. B., Panitz, F., Bendixen, C., Stahl, D. A. & Schramm, A. (2012). Purifying selection and molecular adaptation in the genome of Verminephrobacter, the heritable symbiotic bacteria of earthworms. Genome Biology and Evolution, 4(3), 307-315. https://doi.org/10.1093/gbe/evs014

Nissen, P., Reshetnikova, L., Siboska, G., Polekhina, G., Thirup, S., Kjeldgaard, M., Clark, B. F. & Nyborg, J. (1994). Purification and crystallization of the ternary complex of elongation factor Tu:GTP and Phe-tRNA(Phe). FEBS Letters, 356(2-3), 165-8.

Biswas, D., Birkbak, N. J., Rosenthal, R., Hiley, C. T., Lim, E. L., Papp, K., Boeing, S., Krzystanek, M., Djureinovic, D., La Fleur, L., Greco, M., Döme, B., Fillinger, J., Brunnström, H., Wu, Y., Moore, D. A., Skrzypski, M., Abbosh, C., Litchfield, K. ... TRACERx Consortium (2020). Publisher Correction: A clonal expression biomarker associates with lung cancer mortality . Nature Medicine, 26(7), Article 1148. https://doi.org/10.1038/s41591-020-0899-z

Antaki, D., Guevara, J., Maihofer, A. X., Klein, M., Gujral, M., Grove, J., Carey, C. E., Hong, O., Arranz, M. J., Hervas, A., Corsello, C., Vaux, K. K., Muotri, A. R., Iakoucheva, L. M., Courchesne, E., Pierce, K., Gleeson, J. G., Robinson, E. B., Nievergelt, C. M. & Sebat, J. (2022). Publisher Correction: A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex. Nature Genetics, 54(8), Article 1259. https://doi.org/10.1038/s41588-022-01145-5

Larsen, A., Bøggild, H., Mortensen, J. T., Foldager, L., Hansen, J., Christensen, A., Arendt, M., Rosenberg, N. & Munk-Jørgensen, P. (2010). Psychopathology, defence mechanisms, and the psychosocial work environment. International Journal of Social Psychiatry, 56(6), 563-77. https://doi.org/10.1177/0020764008099555

Abdallah, M., Greaves-Lord, K., Grove, J., Nørgaard-Pedersen, B., Hougaard, D. M. & Mortensen, E. L. (2011). Psychiatric Comorbidities in Autism Spectrum Disorders: Findings from a Danish Historic Birth Cohort. European Child & Adolescent Psychiatry, 20(11-12), 599-601. https://doi.org/10.1007/s00787-011-0220-2

Østergaard, S. D., Foldager, L., Allgulander, C., Dahl, A. A., Huuhtanen, M.-T., Rasmussen, I. & Munk-Jørgensen, P. (2010). Psychiatric caseness is a marker of major depressive episode in general practice. Scandinavian Journal of Primary Health Care, 28(4), 211-5. https://doi.org/10.3109/02813432.2010.501235

Christensen, O. F. (2006). Pseudo-likelihood for non-reversible nucleotide substitution models with neighbour dependent rates. Statistical Applications in Genetics and Molecular Biology, 5(18).

Christensen, O. F., Hobolth, A. & Jensen, J. L. (2005). Pseudo-likelihood analysis of codon substitution models with neighbor dependent rates. Journal of Computational Biology, 12, 1166-1182.

Musgaard, M., Thøgersen, L. & Schiøtt, B. (2011). Protonation States of Important Acidic Residues in the Central Ca²⁺ Ion Binding Sites of the Ca²⁺-ATPase: A Molecular Modeling Study. Biochemistry, 50(51), 11109-11120. https://doi.org/10.1021/bi201164b

Ludvigsen, M., Bjerregård Pedersen, M., Lystlund Lauridsen, K., Svenstrup Poulsen, T., Hamilton-Dutoit, S. J., Besenbacher, S., Bendix, K., Møller, M. B., Nørgaard, P., d'Amore, F. & Honoré, B. (2018). Proteomic profiling identifies outcome-predictive markers in patients with peripheral T-cell lymphoma, not otherwise specified. Blood Advances, 2(19), 2533-2542. https://doi.org/10.1182/bloodadvances.2018019893

Dam, S., Dyrlund, T. F., Ussatjuk, A., Jochimsen, B., Nielsen, K., Goffard, N., Ventosa, M. A. L., Lorentzen, A. M., Gupta, V., Andersen, S. U., Enghild, J. J., Ronson, C. W., Roepstorff, P. & Stougaard, J. (2014). Proteome reference maps of the Lotus japonicus nodule and root. Proteomics, 14(2-3), 230-240. https://doi.org/10.1002/pmic.201300353

Thøgersen, L. (2009). Protein Domain Model: A preliminary exploration. Poster session presented at Faraday Discussion: Multiscale Modelling of Soft Matter, Groningen, Netherlands.

Kringelbach, T., Højgaard, M., Rohrberg, K., Spanggaard, I., Laursen, B. E., Ladekarl, M., Haslund, C. A., Harsløf, L., Belcaid, L., Gehl, J., Søndergaard, L., Eefsen, R. L., Hansen, K. H., Kodahl, A. R., Jensen, L. H., Holt, M. I., Oellegaard, T. H., Yde, C. W., Ahlborn, L. B. & Lassen, U. (2023). ProTarget: a Danish Nationwide Clinical Trial on Targeted Cancer Treatment based on genomic profiling – a national, phase 2, prospective, multi-drug, non-randomized, open-label basket trial. BMC Cancer, 23(1), Article 182. https://doi.org/10.1186/s12885-023-10632-9

Cheng, Z., McLaughlin, D. L., Little, M. W., Ferris, C., Salavati, M., Ingvartsen, K. L., Crowe, M. A., Wathes, D. C. & GplusE Consortium (2023). Proportion of Concentrate in the Diet of Early Lactation Dairy Cows Has Contrasting Effects on Circulating Leukocyte Global Transcriptomic Profiles, Health and Fertility According to Parity. International Journal of Molecular Sciences , 24(1), Article 39. https://doi.org/10.3390/ijms24010039

Blanquart, F., Achaz, G., Bataillon, T. & Tenaillon, O. (2014). Properties of selected mutations and genotypic landscapes under Fisher's geometric model. Evolution, 68(12), 3537-54. https://doi.org/10.1111/evo.12545

Villesen, P. & Stride Nielsen, L. (2017). Profiling of cocaine using ratios of GC-MS peaks. Scientific Reports, 7(1), 11646. Article 11646. https://doi.org/10.1038/s41598-017-12042-x

Fredslund, J. & Lange, M. (2007). primique: automatic design of specific PCR primers for each sequence in a family. BMC Bioinformatics, 8(369). https://doi.org/10.1186/1471-2105-8-369

Fredslund, J., Schauser, L., Madsen, L. H., Sandal, N. N. & Stougaard, J. (2005). PriFi - Using a Multiple Alignment of Related Sequences to Find Primers for Amplification of Homologs. Nucleic Acids Research, 33(W), 516-520.

Larsen, J. K., Foldager, L., Bendsen, B. B. & Munk-Jørgensen, P. (2011). Prematurity and low birth weight as risk factors for the development of affective disorder, especially depression and schizophrenia: a register study. Poster session presented at American Psychiatric Association 164th Annual Meeting, Honolulu, Hawaii, United States.

Winters, J., Kobek-Kjeldager, C., Foldager, L. & Pedersen, L. J. (2021). Preliminary results on the effect of keeping pigs in home environment post weaning. In E. Strandberg, L. Pinotti, S. Messori, D. Kenny, M. Lee, J. F. Hocquette, V. A. P. Cadavez, S. Millet, R. Evans, T. Veldkamp, M. Pastell & G. Pollott (Eds.), Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (pp. 356-356). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-918-3

Kjældgaard, A. L., Pilely, K., Olsen, K. S., Jessen, A. H., Lauritsen, A. Ø., Pedersen, S. W., Svenstrup, K., Karlsborg, M., Thagesen, H., Blaabjerg, M., Theódórsdóttir, Á., Elmo, E. G., Møller, A. T., Bonefeld, L., Berg, M., Garred, P. & Møller, K. (2021). Prediction of survival in amyotrophic lateral sclerosis: a nationwide, Danish cohort study. BMC Neurology, 21(1), Article 164. https://doi.org/10.1186/s12883-021-02187-8

Søndergaard, D., Nielsen, S., Pedersen, C. N. S. & Besenbacher, S. (2017). Prediction of Primary Tumors in Cancers of Unknown Primary. Journal of Integrative Bioinformatics, 14(2). https://doi.org/10.1515/jib-2017-0013

Thorup, V. M., Foldager, L., Pastell, M., Frandsen, M., Jensen, B. B. & Krogh, M. A. (2024). Prediction of mortality in recirculation aquaculture systems. Poster session presented at AQUA Conference 2025, Copenhagen, Denmark.

Foldager, L., Thorup, V. M., Pastell, M., Jensen, B. B. & Krogh, M. A. (2024). Prediction of mortality in land-based recirculating aquaculture system (RAS) trout farms. In P. Linde (Ed.), Symposium i Anvendt Statistik 2024 (pp. 17-24). Økonomisk Institut, Københavns Universitet & Symposium i Anvendt Statistik. http://www.statistiksymposium.dk/Symposium 2024 WEB.pdf

De Koster, J., Salavati, M., Grelet, C., Crowe, M. A., Matthews, E., O'Flaherty, R., Opsomer, G., Foldager, L., GplusE Consortium & Hostens, M. (2019). Prediction of metabolic clusters in early lactation dairy cows using models based on milk biomarkers. Journal of Dairy Science, 102(3), 2631-2644. https://doi.org/10.3168/jds.2018-15533

Grelet, C., Vanlierde, A., Dehareng, F., Froidmont, E. & GplusE Consortium (2017). Prediction of energy status of dairy cows using MIR milk spectra. In Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science (Vol. 23, pp. 403-403). Wageningen Academic Publishers.

Grelet, C., Vanlierde, A., Salavati, M., Hostens, M., Foldager, L., Dehareng, F. & GplusE Consortium (2017). Prediction of energy status of dairy cows using MIR milk spectra. Abstract from ICAR 2017, United Kingdom. http://www.icar.org/wp-content/uploads/2017/06/1.-Clement-Grelet.pdf

Foldager, L., Gaillard, C., Sørensen, M. T., Larsen, T., Matthews, E., O'Flaherty, R., Carter, F., Crowe, M., Grelet, C., Salavati, M., Hostens, M., GplusE Consortium, Ingvartsen, K. L. & Krogh, M. A. (2020). Predicting physiological imbalance in Holstein dairy cows by three different sets of milk biomarkers. Preventive Veterinary Medicine, 179, Article 105006. https://doi.org/10.1016/j.prevetmed.2020.105006

Foldager, L., Munksgaard, L., Trénel, P. & Thomsen, P. T. (2015). Predicting daily eating activity of dairy cows from 3D accelerometer data and RFID signals by use of a random forests model. In C. H. Knight (Ed.), Proceedings of the Third DairyCare Conference 2015 (pp. 31-31)

Bang Jensen, B., Thorup, V. M., Foldager, L., Nielsen, K. V., Frandsen, M., Pastell, M. & Krogh, M. A. (2024). Precision fish farming in recirculated aquaculture systems - from theory to implementation. Poster session presented at 17th International Symposium on Veterinary Epidemiology and Economics, Sydney, New South Wales, Australia. https://isvee2024-c10000.eorganiser.com.au/data/clients/1/791/submissions/177854/abstract.pdf

Cavassim, M. I. A., Baker, Z., Hoge, C., Schierup, M. H., Schumer, M. & Przeworski, M. (2022). PRDM9 losses in vertebrates are coupled to those of paralogs ZCWPW1 and ZCWPW2. Proceedings of the National Academy of Sciences (PNAS), 119(9), Article e2114401119. https://doi.org/10.1073/pnas.2114401119

Sükösd, Z., Knudsen, B., Kjems, J. & Pedersen, C. N. S. (2012). PPfold 3.0: fast RNA secondary structure prediction using phylogeny and auxiliary data. Bioinformatics, 28(20), 2691-2692. https://doi.org/10.1093/bioinformatics/bts488

Grelet, C., Vanlierde, A., Hostens, M., Foldager, L., Salavati, M., Ingvartsen, K. L., Crowe, M., Sorensen, M. T., Froidmont, E., Ferris, C. P., Marchitelli, C., Becker, F., Larsen, T., Carter, F., GplusE Consortium & Dehareng, F. (2019). Potential of milk mid-IR spectra to predict metabolic status of cows through blood components and an innovative clustering approach. Animal, 13(3), 649-658. https://doi.org/10.1017/S1751731118001751

Grelet, C., Froidmont, E., Foldager, L., Salavati, M., Hostens, M., Ferris, C. P., Ingvartsen, K. L., Crowe, M., Sørensen, M. T., Fernandez Pierna, J. A., Vanlierde, A., Gengler, N., GplusE Consortium & Dehareng, F. (2020). Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation. Journal of Dairy Science, 103(5), 4435-4445. https://doi.org/10.3168/jds.2019-17910

Ghouse, J., Ahlberg, G., Rand, S. A., Olesen, M. S., Vilhjalmsson, B., Stender, S. & Bundgaard, H. (2024). Potential Influence of Risk Factor Control on the Association Between Lipoprotein(a) and Atherosclerotic Cardiovascular Disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 44(6), 1455-1457. https://doi.org/10.1161/ATVBAHA.124.320990

Höglund, J., Sørensen, M. T., Larsen, T., Foldager, L., Ferris, C., Bell, M., Carter, F., Santoro, A., Crowe, M. & Ingvartsen, K. L. (2016). Potential for novel metabolite measurements in milk as biomarker phenotypes for dairy traits. In Book of abstracts of the 67th Annual Meeting of the European Federation of Animal Science (pp. 299). Wageningen Academic Publishers, The Netherlands. https://doi.org/10.3920/978-90-8686-830-8

Winters, J. F. M., Foldager, L. & Pedersen, L. J. (2023). Postweaning growth and feeding behaviour in pigs: effect of heavier hybrid and weaning intact litters in farrowing pens for loose-housed sows. Animal, 17(1), Article 100688. https://doi.org/10.1016/j.animal.2022.100688

Riber, A. B., Herskin, M. S., Foldager, L., Sandercock, D. A., Murrell, J. & Tahamtani, F. (2021). Post-mortem examination of fast-growing broilers with different degrees of identifiable gait defects. Veterinary Record, 189(7), Article e454. https://doi.org/10.1002/vetr.454

Privé, F., Aschard, H., Carmi, S., Folkersen, L., Hoggart, C., O'Reilly, P. F. & Vilhjálmsson, B. J. (2022). Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort. American Journal of Human Genetics, 109(1), 12-23. https://doi.org/10.1016/j.ajhg.2021.11.008

Raveane, A., Aneli, S., Montinaro, F., Athanasiadis, G., Barlera, S., Birolo, G., Boncoraglio, G., Di Blasio, A. M., Di Gaetano, C., Pagani, L., Parolo, S., Paschou, P., Piazza, A., Stamatoyannopoulos, G., Angius, A., Brucato, N., Cucca, F., Hellenthal, G., Mulas, A. ... Capelli, C. (2019). Population structure of modern-day Italians reveals patterns of ancient and archaic ancestries in Southern Europe. Science Advances, 5(9), Article eaaw3492. https://doi.org/10.1126/sciadv.aaw3492

Wang, X., Aninta, S. G., Garcia-Erill, G., Li, Z., Khan, A., Liu, X., Bertola, L. D., Dharmayanthi, A. B., Yulianto, Yonathan, Rossi, C., Cauble-Sims, R., Rosen, B. D., Hagen, D. E., Heaton, M. P., Smith, T. P. L., Lenstra, J. A., Martins, N. F. G., Sinding, M. H. S. ... Heller, R. (2026). Population structure and domestication history of the Javan banteng. Current Biology, 36(2), 458-473.e8. https://doi.org/10.1016/j.cub.2025.11.076

Als, T. D., Lescai, F., Dahl, H. A., Grove, J., Demontis, D., Wang, A. G., Andorsdottir, G., Biskopstø, M., Johansen, O., Nyegaard, M., Bolund, L., Mors, O., Wang, J. & Børglum, A. (2014). Population Structure & Cryptic Relatedness of the isolated Population of the Faroe Islands. Poster session presented at XXII World Congress of Psychiatric Genetics, København, Denmark.

Displaying results 351 to 400 out of 1410

Revised 13.01.2026

Palle Villesen