Prof. Dr. Timothy Mathes Beissinger

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  • 2022 | Journal Article | Research Paper
    ​ ​Genomic prediction models for traits differing in heritability for soybean, rice, and maize​
    Kaler, A. S.; Purcell, L. C.; Beissinger, T.   & Gillman, J. D.​ (2022) 
    BMC Plant Biology, 22(1) art. 87​.​ DOI: https://doi.org/10.1186/s12870-022-03479-y 
    ​Details  DOI 
  • 2022 | Journal Article
    ​ ​Die Digitalisierung der Pneumologie und die Rolle der Fachgesellschaften​
    Wollsching-Strobel, M.; Butt, U.; Majorski, D. S.; Beissinger, T. ; Stachwitz, P.; Hagen, J. & Kroppen, D. et al.​ (2022) 
    Pneumologie, 76(08) pp. 560​-567​.​ DOI: https://doi.org/10.1055/a-1866-2507 
    ​Details  DOI 
  • 2022 | Journal Article | 
    ​ ​Restrictions and their reporting in systematic reviews of effectiveness: an observational study​
    Helbach, J.; Pieper, D.; Beissinger, T. ; Rombey, T.; Zeeb, H.; Allers, K. & Hoffmann, F.​ (2022) 
    BMC Medical Research Methodology, 22(1).​ DOI: https://doi.org/10.1186/s12874-022-01710-w 
    ​Details  DOI 
  • 2022 | Journal Article | 
    ​ ​Imputation of low‐density marker chip data in plant breeding: Evaluation of methods based on sugar beet​
    Niehoff, T.; Pook, T.; Gholami, M. & Beissinger, T. ​ (2022) 
    The Plant Genome,.​ DOI: https://doi.org/10.1002/tpg2.20257 
    ​Details  DOI 
  • 2022 | Journal Article | 
    ​ ​learnMET: an R package to apply machine learning methods for genomic prediction using multi-environment trial data​
    Westhues, C. C.; Simianer, H.   & Beissinger, T. M. ​ (2022) 
    G3 Genes|Genomes|Genetics, art. jkac226​.​ DOI: https://doi.org/10.1093/g3journal/jkac226 
    ​Details  DOI 
  • 2021 | Journal Article
    ​ ​Genomic prediction using training population design in interspecific soybean populations​
    Beche, E.; Gillman, J. D.; Song, Q.; Nelson, R.; Beissinger, T. ; Decker, J. & Shannon, G. et al.​ (2021) 
    Molecular Breeding, 41(2).​ DOI: https://doi.org/10.1007/s11032-021-01203-6 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Nested association mapping of important agronomic traits in three interspecific soybean populations​
    Beche, E.; Gillman, J. D.; Song, Q.; Nelson, R.; Beissinger, T. ; Decker, J. & Shannon, G. et al.​ (2020) 
    Theoretical and Applied Genetics, 133(3) pp. 1039​-1054​.​ DOI: https://doi.org/10.1007/s00122-019-03529-4 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Genomic Prediction Informed by Biological Processes Expands Our Understanding of the Genetic Architecture Underlying Free Amino Acid Traits in Dry Arabidopsis Seeds​
    Turner-Hissong, S. D.; Bird, K. A.; Lipka, A. E.; King, E. G.; Beissinger, T. M.   & Angelovici, R.​ (2020) 
    G3: Genes, Genomes, Genetics, 10(11) pp. 4227​-4239​.​ DOI: https://doi.org/10.1534/g3.120.401240 
    ​Details  DOI 
  • 2020 | Journal Article | 
    ​ ​Comparing Different Statistical Models and Multiple Testing Corrections for Association Mapping in Soybean and Maize​
    Kaler, A. S.; Gillman, J. D.; Beissinger, T.   & Purcell, L. C.​ (2020) 
    Frontiers in Plant Science, 10.​ DOI: https://doi.org/10.3389/fpls.2019.01794 
    ​Details  DOI 
  • 2020 | Journal Article
    ​ ​Evolutionary insights into plant breeding​
    Turner-Hissong, S. D; Mabry, M. E; Beissinger, T. M ; Ross-Ibarra, J. & Pires, J C.​ (2020) 
    Current Opinion in Plant Biology, 54 pp. 93​-100​.​ DOI: https://doi.org/10.1016/j.pbi.2020.03.003 
    ​Details  DOI 
  • 2019 | Journal Article | 
    ​ ​Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs​
    Gyawali, A.; Shrestha, V.; Guill, K. E.; Flint-Garcia, S. & Beissinger, T. M. ​ (2019) 
    BMC Plant Biology, 19(1).​ DOI: https://doi.org/10.1186/s12870-019-2000-y 
    ​Details  DOI 
  • 2019 | Journal Article | 
    ​ ​An R Framework for the Partitioning of Linkage Disequilibrium between and Within Populations​
    Petrowski, P. F.; King, E. G. & Beissinger, T. M. ​ (2019) 
    Journal of Open Research Software, 7 art. 15​.​ DOI: https://doi.org/10.5334/jors.250 
    ​Details  DOI 
  • 2019 | Journal Article | 
    ​ ​Integrated Genome-Scale Analysis Identifies Novel Genes and Networks Underlying Senescence in Maize​
    Sekhon, R. S.; Saski, C.; Kumar, R.; Flinn, B. S.; Luo, F.; Beissinger, T. M.   & Ackerman, A. J. et al.​ (2019) 
    The Plant Cell, 31(9) pp. 1968​-1989​.​ DOI: https://doi.org/10.1105/tpc.18.00930 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​A Simple Test Identifies Selection on Complex Traits​
    Beissinger, T. ; Kruppa, J.; Cavero, D.; Ha, N.-T.; Erbe, M. & Simianer, H. ​ (2018) 
    Genetics, 209(1) pp. 321​-333​.​ DOI: https://doi.org/10.1534/genetics.118.300857 
    ​Details  DOI 
  • 2016 | Journal Article | 
    ​ ​Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens​
    Beissinger, T. M. ; Gholami, M.; Erbe, M.; Weigend, S.; Weigend, A.; de Leon, N. & Gianola, D. S. et al.​ (2016) 
    Heredity, 116(2) pp. 158​-166​.​ DOI: https://doi.org/10.1038/hdy.2015.81 
    ​Details  DOI  PMID  PMC  WoS 

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