List of publications

List of publications

Publications in peer-reviewed journals

  1. Iso-Touru, T., Panitz, F., Fischer, D. et al. (2024): Genes and pathways revealed by whole transcriptome analysis of milk derived bovine mammary epithelial cells after Escherichia coli challenge. Vet Res 55, 13.
    https://doi.org/10.1186/s13567-024-01269-y
  2. Calboli, F.C.F., Iso-Touru, T., Bitz, O., Fischer, D., Nousiainen, A., et al. (2023): Genomic selection for survival under naturally occuring Saprolegnia oomycete infection in farmed European whitefish Coregonus lavaretus. Journal of Animal Science 101: 1-16. 
    https://doi.org/10.1093/jas/skad333
  3. Tapio, M., Fischer, D., Mäntysaari, P., Tapio, I. (2023): Rumen Microbiota Predicts Feed Efficiency of Primiparous Nordic Red Dairy Cows. Microorganisms 11 (5), 1116.
    https://doi.org/10.3390/microorganisms11051116
  4. Shanthi, K.B., Fischer, D., Sharma, A., Kiviniemi, A., Kaakinen, M., Vainio, S.J., et al. (2023): Human Adult Astrocyte Extracellular Vesicle Transcriptomics Study Identifies Specific RNAs Which Are Preferentially Secreted as EV Luminal Cargo. Genes 14 (4), 853.
    https://doi.org/10.3390/genes14040853
  5. Fischer, D., Nordhausen, K., Yi, M. (2023): An Analysis of David E. Tyler’s Publication and Coauthor Network. Robust and Multivariate Statistical Methods: Festschrift in Honor of David E. Tyler. Pages 3-21, Springer International Publishing.
    https://doi.org/10.1007/978-3-031-22687-8_1
  6. Bart, G., Fischer, D., Samoylenko, A., Zhyvolozhnyi, A., Stehantsev, P. et al (2021): Characterization of nucleic acids from extracellular vesicle-enriched human sweat. BMC genomics 22, 1-29.
    https://doi.org/10.1186/s12864-021-07733-9
  7. Fischer, D., Nordhausen, K., Oja, H. (2020): On linear dimension reduction based on diagonalization of scatter matrices for bioinformatics downstream analyses. Heliyon, 6(12), e05732.
    https://doi.org/10.1016/j.heliyon.2020.e05732
  8. Fischer, D., Mosler, K., Nordhausen, K., Möttönen, J., Pokotylo, O., and Vogel, D. (2020): Computing the Oja Median in R: The Package OjaNP. Journal of Statistical Software, 92(8), pp. 1-36.
    http://dx.doi.org/10.18637/jss.v092.i08
  9. Fischer, D., Berro, A., Nordhausen, K., Ruiz-Gazen, A. (2019): REPPLab: Detecting Groups and Outliers Using Exploratory Projection Pursuit. Communications in Statistics – Simulation and Computation.
    https://doi.org/10.1080/03610918.2019.1626880.
  10. Dillard, K., Hytönen, M.K., Fischer, D., Tanhuanpää, K., Lehti, M., Sironen, A., Anttila, M. (2018): A splice site variant in INPP5E causes diffuse cystic renal dysplasia and hepatic fibrosis in dogs. PLoS ONE 13(9): e0204073.
    https://doi.org/10.1371/journal.pone.0204073.
  11. Iso-Touru, T., Pesonen, M., Fischer, D., Huuskonen, A., Sironen, A. (2018): The effect of CAPN1 and CAST gene variations on meat quality traits in Finnish Aberdeen Angus and Nordic Red Cattle populations. Agricultural and Food Science, 27(4), 227–231.
    https://doi.org/10.23986/afsci.75125.
  12. Tuiskula-Haavisto, M., Honkatukia, M., Dunn, I.C., Bain, M.M., De Koning, D.J., Preisinger, R., Schmutz, M., Arango, J., Fischer, D., Vilkki, J. (2018): Validated QTL for egg shell quality in experimental and commercial laying hens. Animal Genetics.
    https://doi.org/10.1111/age.12671.
  13. Fischer, D. (2017): The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci. Computer Methods and Programs in Biomedicine, 151, 171–177.
    https://doi.org/10.1016/j.cmpb.2017.08.012
  14. Tapio,I., Fischer,D., Blasco,L., Tapio,M., Wallace,R.J., Bayat,A.R., Ventto,L., Kahala,M., Negussie,E., Shingfield,K.J., Vilkki,J. (2017): Taxon abundance, diversity, co-occurrence and network analysis of the ruminal microbiota in response to dietary changes in dairy cows. PLoS ONE 12(7): e0180260.
    https://doi.org/10.1371/journal.pone.0180260.
  15. Fischer, D., Honkatukia,M., Tuiskula-Haavisto,M., Nordhausen,K., Cavero,D., Preisinger,R., Vilkki,J. (2017): Subgroup Detection in Genotype Data using Invariant Coordinate Selection. BMC Bioinformatics, 18(173), 1–9.
    https://doi.org/10.1186/s12859-017-1589-9.
  16. Da Ros, M., Lehtiniemi, T., Olotu, O., Fischer, D., Zhang, F.-P., Vihinen, H., Jokitalo, E., Sironen, A., Toppari, J., Kotaja, N. (2017): FYCO1 and autophagy control the integrity of the haploid male germ cell-specific RNP granules. Autophagy, 13(2), 302–321. 
    https://doi.org/10.1080/15548627.2016.1261319
  17. Spiliopoulos, S., Hergesell, V., Fischer, D., Koerfer, R., Tenderich, G. (2016):Applicability of Cardiogoniometry as a non- invasive Screening Tool for the Detection of Graft Vasculopathy in Heart Transplant Recipients. Interactive CardioVascular and Thoracic Surgery.
    https://doi.org/10.1093/icvts/ivw237.
  18. Nurminen, R., Rantapero, T., Chong, W.S., Fischer, D., Lehtonen, R., Tammela, T.L.J., Nykter, M., Visakorpi, T., Wahlfors, T., Schleutker, J. (2016): Expressional profiling of prostate cancer risk SNPs at 11q13.5 identifies DGAT2 as a new target gene. Genes, Chromosomes and Cancer, 55(8), 661-673.
    https://doi.org/10.1002/gcc.22368.
  19. Tapio,I., Shingfield,K.J., McKain,N., Bonin,A., Bayat,A., Fischer,D., Vilkki,J., Taberlet,P., Snelling,T.J., Wallace, R.J. (2016): Oral Samples as Non-Invasive Proxies for Assessing the Composition of the Rumen Microbial Community. PLoS ONE 11(3): e0151220.
    https://doi.org/10.1371/journal.pone.0151220.
  20. Fischer, D., Nordhausen, K. and Taskinen, S. (2015): Publication and Coauthorship Networks of Hannu Oja. Modern Nonparametric, Robust and Multivariate Methods – Festschrift in Honour of Hannu Oja. pp.7-31. Springer, Heidelberg
    https://doi.org/10.1007/978-3-319-22404-6.
  21. Bruford, M.W., Ginja, C., Hoffmann, I., Joost, S., Orozco-terWengel, P. et al. (2015): Prospects and Challenges for the Conservation of Farm Animal Genomic Resources, 2015-2025. Frontiers in Genetics 6(314).
    https://doi.org/10.3389/fgene.2015.00314
  22. Fischer, D., Laiho, A., Gyenesei, A., Sironen, A. (2015): Identification of reproduction related gene mutations using RNAseq in the Large White pig population. G3: Genes, Genomes, Genetics. July 1, 2015 vol. 5 no. 7 1351-1360.
    https://doi.org/10.1534/g3.115.018382.
  23. Fischer, D., Oja, H. (2015): Mann-Whitney Type Tests for Microarray Experiments: The R Package gMWT. Journal of Statistical Software, 65(9).
    https://doi.org/10.18637/jss.v065.i09.
  24. Fischer, D., Wahlfors, T., Mattila, H., Oja, H., Tammela, T.L.J, Schleutker, J. (2015): MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families. PLoS ONE 10(5): e0127427.
    https://doi.org/10.1371/journal.pone.0127427.
  25. Laitinen, V.H., Rantapero, T., Fischer, D., Vuorinen, E.M. , Tammela, T.L.J., Wahlfors, T., PRACTICAL Consortium, Schleutker, J. (2014): Fine-mapping the 2q37 and 17q11.2-q22 Loci for Novel Genes and Sequence Variants Associated with a Genetic Predisposition to Prostate Cancer. International Journal of Cancer, 136(10), 2316-2327.
    https://doi.org/10.1002/ijc.29276.
  26. Sironen, A., Fischer, D., Laiho, A., Gyenesei, A., Vilkki, J. (2014): A recent L1 insertion within SPEF2 gene is associated with changes in PRLR expression in sow reproductive organs. Animal Genetics, 45(4), 500-507.
    https://doi.org/10.1111/age.12153.
  27. Fischer, D., Oja, H., Schleutker, J., Sen, P.K. and Wahlfors, T. (2014): Generalized Mann-Whitney Type Tests for Microarray Experiments. Scandinavian Journal of Statistics, 41(3), 672-692.
    https://doi.org/10.1111/sjos.12055.
  28. Siltanen, S., Fischer, D., Rantapero, T., Laitinen, V., Mpindi, J.P., Kallioniemi, O., Wahlfors, T., Schleutker, J. (2013): ARLTS1 and Prostate Cancer Risk – Analysis of Expression and Regulation. PLoS ONE 8(8): e72040.
    https://doi.org/10.1371/journal.pone.0072040.

Manuscripts accepted for publication

Submitted Manuscripts

  1. Fischer, D., Tapio, M., Bitz, O., Iso-Touru, T., Kause, A., Tapio, I. (XXX): Fine-Tuning GBS Data with Comparison of Reference and Mock Genome Approaches for Advancing Genomic Selection in Less Studied Farmed Species.

Manuscripts in peer-reviewed conference proceedings

  1. Iso-Touru, T., Fischer, D., Kyläniemi, M., Tabell, J., Virta, A., Vilkki, J. (2022): Genomewide transcriptome profiling of milk derived primary bovine mammary epithelial cells after pathogen challenge. Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP), 2830-2833.
    https://doi.org/10.3920/978-90-8686-940-4_686
  2. Gredler-Grandl, B., Raymond, B., Schopen, G.C.B., Chitneedi, P.K., Cai, Z., Manzanilla-Pech, C.I.V., et al. (2022): Accuracy of genomic prediction of dry matter intake in Dutch Holsteins using sequence variants from meta-analyses. Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP). 1181-1184.
    https://doi.org/10.3920/978-90-8686-940-4_280

Other publications

  1. Fischer, D. (2024)  An Introduction to R and Python for Data Analysis: A Side-by-Side Approach Taylor R. Brown Chapman and Hall/CRC, 2023, 246 pages (hardback $99.95, ebook $74.96) ISBN 978-10322032-56. International Statistical Review,  92:  132–134. https://doi.org/10.1111/insr.12568.
  2. Fischer, D.: Performing QTL and eQTL Analyses with the R-Package GenomicTools. eQTL Analysis: Methods and Protocols, p. 15-38. Springer US.
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