Publications

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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

Gholipourshahraki, T., Ejlskov, L., Semark, B. D., Maseras, G. T., Steinbach, J., Hansen, O. S., Pedersen, C. B., Bulik, C. M., Benros, M. E., Mortensen, P. B., Agerbo, E., Petersen, L. V. & Vilhjálmsson, B. J. (2025). Polygenic Scores and Environmental Factors in Psychiatric Disorders: Gene-Environment Interaction Analyses Using the iPSYCH Study. Research Square. https://doi.org/10.21203/rs.3.rs-8201911/v1

Gengler, N. & GplusE Consortium (2017). Targeted combination of estimated breeding values for lower accuracy mid-infrared biomarkers increases their usefulness in genetic evaluation of dairy cattle. Abstract from ICAR 2017, United Kingdom. http://www.icar.org/wp-content/uploads/2017/06/5.-Nicolas-Gengler-1.pdf

Gengler, N., Mineur, A., Vanderick, S., Hammami, H. & GplusE Consortium (2018). Milk mid-infrared spectra based biomarkers contributing to genetic improvement for udder health, fertility and longevity. In J. Bryant, M. Burke, R. Cook, B. Harris, C. Mosconi & B. Wickham (Eds.), Proceedings of the ICAR Conference (Vol. 23, pp. 221-227) https://www.icar.org/wp-content/uploads/2018/07/ICAR-Technical-Series-23-Auckland-2018-Proceedings.pdf

Gengler, N., Grelet, C., Soyeurt, H., Dehareng, F. & GplusE Consortium (2019). GplusE: Mid-infrared milk analysis based technologies adding value to gene banks. In Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science (Vol. 25, pp. 443). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-890-2

Ge, F., Wang, Y., Liu, X., Munk-Olsen, T., Madsen, K. B., Pedersen, E. M., Albiñana, C., Agerbo, E., Bulik, C. M., Petersen, L. V., Valdimarsdottir, U. A. & Vilhjálmsson, B. J. (2026). Association Between Maternal Genome-Wide Polygenic Scores for Psychiatric and Neurodevelopmental Disorders and Adverse Perinatal Events: A Danish Population-Based Study. Biological Psychiatry Global Open Science, 6(1), Article 100613. https://doi.org/10.1016/j.bpsgos.2025.100613

Gaspar, H. A., Gerring, Z., Hübel, C., Middeldorp, C. M., Derks, E. M., Breen, G. & Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium (2019). Using genetic drug-target networks to develop new drug hypotheses for major depressive disorder. Translational Psychiatry, 9(1), Article 117. https://doi.org/10.1038/s41398-019-0451-4

Garcia-Erill, G., Wang, X., Rasmussen, MS., Quinn, L., Khan, A., Bertola, LD., Santander, CG., Balboa, RF., Ogutu, JO., Pečnerová, P., Hanghøj, K., Kuja, J., Nursyifa, C., Masembe, C., Muwanika, V., Bibi, F., Moltke, I., Siegismund, HR., Albrechtsen, A. & Heller, R. (2024). Extensive Population Structure Highlights an Apparent Paradox of Stasis in the Impala (Aepyceros melampus). Molecular Ecology, 33(22), Article e17539. https://doi.org/10.1111/mec.17539

Garcia-Erill, G., Liu, S., Le, M. D., Hurley, M. M., Nguyen, H. D., Nguyen, D. Q., Nguyen, D. H., Santander, C. G., Sánchez Barreiro, F., Gomes Martins, N. F., Hanghøj, K., Salleh, F. M., Ramos-Madrigal, J., Wang, X., Sinding, M. H. S., Morales, H. E., Stæger, F. F., Wilkinson, N., Meng, G. ... Heller, R. (2025). Genomes of critically endangered saola are shaped by population structure and purging. Cell, 188(12), 3102-3116.e22. https://doi.org/10.1016/j.cell.2025.03.040

Gao, F., Li, S., Lin, L., Li, J., Luo, Y., Zhang, X., Nielsen, A. L. & Bolund, L. (2011). DNA methylation in peripheral blood cells of pigs cloned by somatic cell nuclear transfer. Cellular Reprogramming, 13(4), 307-14. https://doi.org/10.1089/cell.2010.0099, https://doi.org/10.1089/cell.2010.0099

Gao, S., Hu, X., Xu, F., Gao, C., Xiong, K., Zhao, X., Chen, H., Zhao, S., Wang, M., Fu, D., Zhao, X., Bai, J., Mao, L., Li, B., Wu, S., Wang, J., Li, S., Yang, H., Bolund, L. & Pedersen, C. N. S. (2018). BS-virus-finder: virus integration calling using bisulfite sequencing data. GigaScience, 7(1), 1-7. https://doi.org/10.1093/gigascience/gix123

Gao, H., Hamp, T., Ede, J., Schraiber, J. G., McRae, J., Singer-Berk, M., Yang, Y., Dietrich, A. S. D., Fiziev, P. P., Kuderna, L. F. K., Sundaram, L., Wu, Y., Adhikari, A., Field, Y., Chen, C., Batzoglou, S., Aguet, F., Lemire, G., Reimers, R. ... Farh, K. K. H. (2023). The landscape of tolerated genetic variation in humans and primates. Science (New York, N.Y.), 380(6648), Article abn8197. https://doi.org/10.1126/science.abn8197

Galtier, N. & Rousselle, M. (2020). How much does Ne vary among species? Genetics, 216(2), 559-572. https://doi.org/10.1534/genetics.120.303622

Gallasch, G. E., Kristensen, L. M. & Mailund (2002). Sweep-Line State Space Exploration for Coloured Petri Nets. In Proceedings of Fourth Workshop on Practical Use of Coloured Petri Nets and the CPN Tools (CPN 2002) (pp. 101-119)

Furrow, R., Christiansen, F. & Feldman, M. (2011). Environment-sensitive Epigenetics and the Heritability of Complex Diseases. Genetics, 189(4), 1377-1387. https://doi.org/10.1534/genetics.111.131912

Furrow, R. E., Christiansen, F. B. & Feldman, M. W. (2014). Epigenetic variation, phenotypic heritability, and evolution. In A. Naumova & C. Greenwood (Eds.), Epigenetics and Complex Traits (pp. 233-246). Springer. https://doi.org/10.1007/978-1-4614-8078-5_1

Fukai, E., Madsen, L. H., Radutoiu, E. S., Dobrowolska, A., Yost, C. K., Sandal, N. N., Schauser, L. & Stougaard, J. (2006). Identification and characterisation of LORE1 and LORE2, active retrotransposons in model legume Lotus japonicus. Poster session presented at Plant Biotech Denmark Annual meeting 2006, København, Denmark.

Frydendahl, A., Rasmussen, M. H., Jensen, S. Ø., Henriksen, T. V., Demuth, C., Diekema, M., Ditzel, H. J., Wen, S. W. C., Pedersen, J. S., Dyrskjøt, L. & Andersen, C. L. (2024). Error-Corrected Deep Targeted Sequencing of Circulating Cell-Free DNA from Colorectal Cancer Patients for Sensitive Detection of Circulating Tumor DNA. International Journal of Molecular Sciences , 25(8), Article 4252. https://doi.org/10.3390/ijms25084252

Fredsted, T. & Villesen, P. (2005). Genetik og bevaring af truede aber. Aktuel Naturvidenskab, 4, 16-19.

Fredsted, T., Schierup, M. H., Pertoldi, C. & Kappeler, M. (2005). Microsatellite analyses reveal fine-scale genetic structure in grey mouse lemurs (Microcebus murinus). Molecular Ecology, 14, 2363-2372.

Fredsted, T. & Villesen, P. (2006). Operation "Red Aben". Jyllands-Posten, 8-8.

Fredsted, T., Wincentz, T. & Villesen, P. (2006). Introgression of mountain hare (Lepus timidus) mitochondrial DNA into wild brown hares (Lepus europaeus) in Denmark. BMC Ecology, 6(17).

Fredsted, T. & Villesen, P. (2004). Fast, reliable sexing of prosimian DNA. American Journal of Primatology, 64, 345-350.

Fredsted, T., Schierup, M. H., Groenevald, L. F. & Kappeler, P. M. (2007). Genetic structure, lack of sex-biased dispersal and behavioral flexibility in the pair-living fat-tailed dwarf lemur, Cheirogaleus medius. Behavioral Ecology and Sociobiology. https://doi.org/10.1007/s00265-006-0323-9

Fredsted, T. & Villesen, P. (2005). Genetik og bevaring af truede aber. Aktuel Naturvidenskab, (4).

Fredsted, T. & Villesen, P. (2006). Operation "Red aben". Jyllands-Posten.

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.

Fredslund, J. & Andersen, E. S. (2005). Superjordnøddernes hemmelighed. Aktuel Naturvidenskab, (6), 12-15.

Fredslund, J., Madsen, L. H., Hougaard, B. K., Sandal, N. N., Stougaard, J., Bertioli, D. & Schauser, L. (2006). GeMprospector - online design of cross-species genetic marker candidates in legumes and grasses. Nucleic Acids Research, 34, W670-W675.

Fredslund, J., Madsen, L. H., Hougaard, B. K., Nielsen, A. M., Nielsen, A. M., Bertioli, D., Sandal, N. N., Schauser, L. & Stougaard, J. (2006). A general pipeline for the development of anchor markers for comparative genomics in plants. BMC Genomics, 7, 207.

Fredslund, J. (2006). PHY∙FI: fast and easy online creation and manipulation of phylogeny color figures. BMC Bioinformatics, 7(315). https://doi.org/10.1186/1471-2105-7-315

Fredslund, J. & Matarić, M. J. (2002). A General Algorithm for Robot Formations Using Local Sensing and Minimal Communication. Transactions on Robotics and Automation, Special Issue on Multi Robot Systems, 18(5), 837-846.

Fredslund, J. & Cañamero, L. D. (2001). I Show You How I Like You: Emotional Human-Robot Interaction through Facial Expression and Tactile Stimulation. I E E E Transactions on Systems, Man and Cybernetics, Part A: Systems & Humans, 31(5), 454-459.

Fredslund, J., Hein, J. & Scharling, T. (2003). A large version of the small parsimony problem. In Proceedings of the 3rd workshop on algorithms in bioinformatics (WABI 2003) (pp. 417-432)

Fredslund, J. & Matarić, M. J. (2002). Huey, Dewey, Louie, and GUI – Commanding Robot Formations. In Proceedings of the 2002 IEEE International Conference on Robotics and Automation (ICRA'02) IEEE.

Fredslund, J. & Matarić, M. J. (2002). Robots in Formation Using Local Information. In Proceedings of the 7th International Conference on Intelligent Autonomous Systems (IAS-7)

Fredslund, J. & Matarić, M. J. (2001). Robot Formations Using Only Local Sensing and Control. In Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA-01)

Fredslund, J. (2005). Feelix. In H. Domaine (Ed.), Robotics: Cool Science Lerner Publications.

Fredslund, J. (2004). Feelix. In R. F. Bridgman (Ed.), Robot: Eyewitness Dorling Kindersley.

Fredslund, J. (2003). Den Hotteste Forskning.

Fredslund, J. & Hein, J. (2003). Determining the Optimal Set of Indels Explaining the Gaps in a Multiple Alignment Using Affine Gap Cost Function. Poster session presented at International Conference on Research in Computational Molecular Biology (RECOMB 2003), Berlin, Germany.

Fredslund, J. (2000). Teaching a new dog old tricks – the Assumption Architecture. Poster session presented at Learning'00 Workshop, Madrid, Spain.

Fredslund, J. & Matarić, M. J. (2001). Robot Formations.

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. (2008). DATFAP: A Database of Primers and Homology Alignments for Transcription Factors from 13 Plant Species. BMC Genomics.

Frankell, A. M., Dietzen, M., Al Bakir, M., Lim, E. L., Karasaki, T., Ward, S., Veeriah, S., Colliver, E., Huebner, A., Bunkum, A., Hill, M. S., Grigoriadis, K., Moore, D. A., Black, J. R. M., Liu, W. K., Thol, K., Pich, O., Watkins, T. B. K., Naceur-Lombardelli, C. ... TRACERx Consortium (2023). The evolution of lung cancer and impact of subclonal selection in TRACERx. Nature, 616(7957), 525-533. https://doi.org/10.1038/s41586-023-05783-5

Frank, M., Fechete, L. I., Tedeschi, F., Nadzieja, M., Nørgaard, M. M. M., Montiel, J., Andersen, K. R., Schierup, M. H., Reid, D. & Andersen, S. U. (2023). Single-cell analysis identifies genes facilitating rhizobium infection in Lotus japonicus. Nature Communications, 14(1), Article 7171. https://doi.org/10.1038/s41467-023-42911-1

Frandsen, J., Hobolth, A., Østergaard, L., Vestergaard-Poulsen, P. & Jensen, E. B. V. (2007). Bayesian regularization of diffusion tensor images. Biostatistics, 8(4), 784-799. https://doi.org/10.1093/biostatistics/kxm005

Frandsen, P., Fontsere, C., Nielsen, S. V., Hanghøj, K., Castejon-Fernandez, N., Lizano, E., Hughes, D., Hernandez-Rodriguez, J., Korneliussen, T. S., Carlsen, F., Siegismund, H. R., Mailund, T., Marques-Bonet, T. & Hvilsom, C. (2020). Targeted conservation genetics of the endangered chimpanzee. Heredity, 125(1-2), 15-27. https://doi.org/10.1038/s41437-020-0313-0

Franceschini, S., Grelet, C., Leblois, J., Gengler, N., Soyeurt, H. & GplusE Consortium (2022). Can unsupervised learning methods applied to milk recording big data provide new insights into dairy cow health? Journal of Dairy Science, 105(8), 6760-6772. https://doi.org/10.3168/jds.2022-21975

Displaying results 901 to 950 out of 1384

Revised 13.01.2026

Palle Villesen