Tataru, P. & Bataillon, T. (2019). polyDFEv2.0: testing for invariance of the distribution of fitness effects within and across species. Bioinformatics (Oxford, England), 35(16), 2868-2869. https://doi.org/10.1093/bioinformatics/bty1060

Tahamtani, F., Herskin, M. S., Foldager, L., Murrell, J., Sandercock, D. & Riber, A. B. (2021). Assessment of mobility and pain in broiler chickens with identifiable gait defects. Applied Animal Behaviour Science, 234, Article 105183. https://doi.org/10.1016/j.applanim.2020.105183

Szalay, P. G., Thøgersen, L. S., Olsen, J., Kállay, M. & Gauss, J. (2004). Equilibrium Geometry of the Ethynyl (CCH) Radical. Journal of Physical Chemistry Part A: Molecules, Spectroscopy, Kinetics, Environment and General Theory, 108, 3030-3034.

Świtnicki, M. P., Rasmussen, M. J., Madsen, T., Sørensen, K. D. & Pedersen, J. S. (2016). PINCAGE: Probabilistic integration of cancer genomics data for perturbed gene identification and sample classification. Bioinformatics, 32(9), 1353-1365. https://doi.org/10.1093/bioinformatics/btv758

Swenson, M. S., Anderson, J., Ash, A., Gaurav, P., Sükösd, Z., Bader, D. A., Harvey, S. C. & Heitsch, C. E. (2012). GTfold: Enabling parallel RNA secondary structure prediction on multi-core desktops. BMC Research Notes, 5(341). https://doi.org/10.1186/1756-0500-5-341

Svenstrup, M. & Christiansen, F. B. (2000). Biker’s Dilemma: Cooperation between Foes. Selection, Vol. 1, 147–152.

Suppli, N. P., Andersen, K. K., Agerbo, E., Rajagopal, V. M., Appadurai, V., Coleman, J. R. I., Breen, G., Bybjerg-Grauholm, J., Bækvad-Hansen, M., Pedersen, C. B., Pedersen, M. G., Thompson, W. K., Munk-Olsen, T., Benros, M. E., Als, T. D., Grove, J., Werge, T., Børglum, A. D., Hougaard, D. M. ... Musliner, K. L. (2022). Genome-wide by Environment Interaction Study of Stressful Life Events and Hospital-Treated Depression in the iPSYCH2012 Sample. Biological Psychiatry: Global Open Science, 2(4), 400-410. https://doi.org/10.1016/j.bpsgos.2021.11.003

Sun, C., Luecke, S., Bodda, C., Jønsson, K. L., Cai, Y., Zhang, B. C., Jensen, S. B., Nordentoft, I., Jensen, J. M., Jakobsen, M. R. & Paludan, S. R. (2019). Cellular Requirements for Sensing and Elimination of Incoming HSV-1 DNA and Capsids. Journal of Interferon and Cytokine Research, 39(4), 191-204. https://doi.org/10.1089/jir.2018.0141

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

Sükösd, Z., Swenson, M. S., Kjems, J. & Heitsch, C. E. (2013). Evaluating the accuracy of SHAPE-directed RNA secondary structure predictions. Nucleic Acids Research, 41(5), 2807-2816. https://doi.org/10.1093/nar/gks1283

Sükösd, Z., Knudsen, B., Anderson, J. WJ., Novák, A., Kjems, J. & Pedersen, C. N. S. (2013). Characterising RNA secondary structure space using information entropy. B M C Bioinformatics, 14 (Suppl 2), 1-9. Article S22. https://doi.org/10.1186/1471-2105-14-S2-S22

Sükösd, Z., Andersen, E. S. & Lyngsø, R. (2014). SCFGs in RNA secondary structure prediction: a hands-on approach. Methods in Molecular Biology, 1097, 143-62. https://doi.org/10.1007/978-1-62703-709-9__8, https://doi.org/10.1007/978-1-62703-709-9_8

Sukosd, Z., Andersen, E. S., Seemann, S. E., Jensen, M., Hansen, M. B., Gorodkin, J. & Kjems, J. (2015). Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain. Nucleic Acids Research, 43(21), 10168-10179. https://doi.org/10.1093/nar/gkv1039

Subrahmaniam, H. J., Pico, X., Bataillon, T., Salomonsen, C. L., Glasius, M. & Ehlers, B. (2025). Natural variation in root exudate composition in the genetically structured Arabidopsis thaliana in the Iberian Peninsula. New Phytologist, 245(4), 1437-1449. https://doi.org/10.1111/nph.20314

Stumpf, MPH. & Wiuf, C. (2005). Sampling properties of random graphs: The degree distribution. Physical Review E, 72(036118), 1-7.

Stumpf, MPH., Ingram, PJ., Nouvel, I. & Wiuf, C. (2005). Statistical model selection methods applied to biological network data. Transactions on Computational Systems Biology, 3, 65-77.

Stumpf, MPH., Wiuf, C. & May, RM. (2005). Subnets of scale-free networks are not scale-free: Sampling properties of networks. Proceedings of the National Academy of Sciences (PNAS), 102, 4221-4224.

Stumpf, M. P., Kelly, W. P., Thorne, T. & Wiuf, C. (2007). Evolution at the system level: The natural history of protein interaction networks. TREE, 22(7), 366-372.

Stumpf, M. PH., Thorne, T., Silva, E., Stewart, R., An, HJ., Lappe, M. & Wiuf, C. H. (2008). Estimating the size of the human interactome. Proceedings of the National Academy of Sciences (PNAS), 105, 6059.

Stukenbrock, E., Jørgensen, F., Zala, M., Hansen, T. T., McDonald, B. A. & Schierup, M. H. (2010). Whole-genome and chromosome evolution associated with host adaptation and speciation of the wheat pathogen Mycosphaerella graminicola. P L o S Genetics, 23(6).

Stukenbrock, E. H., Bataillon, T., Dutheil, J. Y., Hansen, T. T., Li, R., Zala, M., McDonald, B. A., Wang, J. & Schierup, M. H. (2011). The making of a new pathogen: Insights from comparative population genomics of the domesticated wheat pathogen Mycosphaerella graminicola and its wild sister species. Genome Research, 21, 2157-2166. https://doi.org/10.1101/gr.118851.110

Stukenbrock, E. H., Christiansen, F. B., Hansen, T. T., Dutheil, J. & Schierup, M. H. (2012). Fusion of two divergent fungal individuals led to the recent emergence of a unique widespread pathogen species. Proceedings of the National Academy of Sciences (PNAS), 107(27). https://doi.org/10.1073/pnas.1201403109

Stukenbrock, E. H. & Bataillon, T. (2012). A population genomics perspective on the emergence and adaptation of new plant pathogens in agro-ecosystems. P L o S Pathogens, 8(9), e1002893. https://doi.org/10.1371/journal.ppat.1002893

PGC TS Working Group & 23andMe Research Team (2025). Genome-Wide Association Study Meta-Analysis of 9619 Cases With Tic Disorders. Biological Psychiatry, 97(7), 743-752. https://doi.org/10.1016/j.biopsych.2024.07.025

Strimmer, K., Wiuf, C. & Moulton, V. (2001). Recombination analysis using directed graphical models. Mol. Biol. Evol., 18, 97-99.

Stride Nielsen, L., Villesen, P. & Lindholst, C. (2017). Variation in chemical profiles within large seizures of cocaine bricks. Forensic Science International, 280, 194-199. https://doi.org/10.1016/j.forsciint.2017.10.007

Streja, E., Wu, C., Uldall, P. V., Grove, J., Arah, O. & Olsen, J. (2013). Congenital cerebral palsy, child sex and parent cardiovascular risk. PLOS ONE, 8(11), e79071. https://doi.org/10.1371/journal.pone.0079071

St Pourcain, B., Robinson, E. B., Anttila, V., Sullivan, B. B., Maller, J., Golding, J., Skuse, D., Ring, S., Evans, D. M., Zammit, S., Fisher, S. E., Neale, B. M., Anney, R. J. L., Ripke, S., Hollegaard, M. V., Werge, T., Ronald, A., Grove, J., Hougaard, D. M. ... iPSYCH-SSI-Broad Autism Group (2017). ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties. Molecular Psychiatry, 23, 263-270. https://doi.org/10.1038/mp.2016.198

Stissing, M., Mailund, T., Pedersen, C. S., Brodal, G. S. & Fagerberg, R. (2008). Computing the all-pairs quartet distance on a set of evolutionary trees. Journal of Bioinformatics and Computational Biology, 6(1), 37-50.

Stiller, J., Feng, S., Chowdhury, A.-A., Rivas-González, I., Duchêne, D. A., Fang, Q., Deng, Y., Kozlov, A., Stamatakis, A., Claramunt, S., Nguyen, J. M. T., Ho, S. Y. W., Faircloth, B. C., Haag, J., Houde, P., Cracraft, J., Balaban, M., Mai, U., Chen, G. ... Zhang, G. (2024). Complexity of avian evolution revealed by family-level genomes. Nature, 629(8013), 851-860. https://doi.org/10.1038/s41586-024-07323-1

Stevison, L. S., Woerner, A. E., Kidd, J. M., Kelley, J. L., Veeramah, K. R., McManus, K. F., Bustamante, C. D., Hammer, M. F., Wall, J. D., Great Ape Genome Project & Schierup, M. H. (2016). The Time Scale of Recombination Rate Evolution in Great Apes. Molecular Biology and Evolution, 33(4), 928-945. https://doi.org/10.1093/molbev/msv331

Steinberg, S., de Jong, S., Andreassen, O. A., Werge, T., Børglum, A. D., Mors, O., Mortensen, P. B., Gustafsson, O., Costas, J., Pietiläinen, O. P. H., Demontis, D., Papiol, S., Huttenlocher, J., Mattheisen, M., Breuer, R., Vassos, E., Giegling, I., Fraser, G., Walker, N. ... Irish Schizophrenia Genomics Consortium (2011). Common Variants at VRK2 and TCF4 Conferring Risk of Schizophrenia. Human Molecular Genetics, 20(20), 4076-81. https://doi.org/10.1093/hmg/ddr325

The Baboon Genome Analysis Consortium (2018). Analysis of lineage-specific Alu subfamilies in the genome of the olive baboon, Papio anubis. Mobile DNA, 9(1), Article 10. https://doi.org/10.1186/s13100-018-0115-6

Staunstrup, N. H., Moldt, B., Mátés, L., Villesen, P., Jakobsen, M., Ivics, Z., Izsvák, Z. & Mikkelsen, J. G. (2009). Hybrid Lentivirus-transposon Vectors With a Random Integration Profile in Human Cells. Molecular Therapy, 17(7), 1205-14. https://doi.org/10.1038/mt.2009.10

Starnawski, P., Bataillon, T., Ettema, T. J. G., Jochum, L. M., Schreiber, L., Chen, X., Lever, M. A., Polz, M. F., Jørgensen, B. B., Schramm, A. & Kjeldsen, K. U. (2017). Microbial community assembly and evolution in subseafloor sediment. Proceedings of the National Academy of Sciences (PNAS), 114(11), 2940-2945. https://doi.org/10.1073/pnas.1614190114

Starnawska, A., Bukowski, L., Chernomorchenko, A., Elfving, B., Müller, H. K., van den Oord, E., Aberg, K., Guintivano, J., Grove, J., Mors, O., Børglum, A. D., Nielsen, A. L., Qvist, P. & Staunstrup, N. H. (2021). DNA methylation of the KLK8 gene in depression symptomatology. Clinical Epigenetics, 13(1), Article 200. https://doi.org/10.1186/s13148-021-01184-5

Stahl, E. A., Breen, G., Forstner, A. J., McQuillin, A., Ripke, S., Trubetskoy, V., Mattheisen, M., Wang, Y., Coleman, J. R. I., Gaspar, H. A., de Leeuw, C. A., Steinberg, S., Pavlides, J. M. W., Trzaskowski, M., Byrne, E. M., Pers, T. H., Holmans, P. A., Richards, A. L., Abbott, L. ... eQTLGen Consortium (2019). Genome-wide association study identifies 30 loci associated with bipolar disorder. Nature Genetics, 51(5), 793-803. https://doi.org/10.1038/s41588-019-0397-8

Speed, D. & Balding, D. J. (2019). SumHer better estimates the SNP heritability of complex traits from summary statistics. Nature Genetics, 51(2), 277-284. https://doi.org/10.1038/s41588-018-0279-5

Speed, D., Hemani, G., Speed, M. S., Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium & Børglum, A. D. (2019). Investigating the causal relationship between neuroticism and depression via Mendelian Randomization. Acta Psychiatrica Scandinavica, 139(4), 395-397. https://doi.org/10.1111/acps.13009

Speed, M., Balding, D. J. & Hobolth, A. (2019). A general framework for moment-based analysis of genetic data. Journal of Mathematical Biology, 78(6), 1727-1769. https://doi.org/10.1007/s00285-018-01325-0

Speed, M. S., Jefsen, O. H., Børglum, A. D., Speed, D. & Østergaard, S. D. (2019). Investigating the association between body fat and depression via Mendelian randomization. Translational Psychiatry, 9(1), Article 184. https://doi.org/10.1038/s41398-019-0516-4

Speed, D., Holmes, J. & Balding, D. J. (2020). Evaluating and improving heritability models using summary statistics. Nature Genetics, 52(4), 458-462. https://doi.org/10.1038/s41588-020-0600-y

Sørensen, F. J., Andersen, C. L. & Wiuf, C. (2007).  SNPTools: A software tool for visualization and analysis of microarray data. Bioinformatics, 23(12), 1550-52. https://doi.org/10.1093/bioinformatics/btm122