Publications

• Ibrahimi, E., Miri, F., Porreca, A. et al. Mixed Modeling of the Effect of Pharmaceutical Pollution on the Metamorphosis of Amphibians from Incomplete Trajectory Data. Inland Water Biol (2025). https://doi.org/10.1134/S1995082924600704 

• Falco, F. et al. (2024). Ecotoxicity Assessment of Emerging Contaminants (EC) in Fish: Effects, Trends, and Challenges. In: The Handbook of Environmental Chemistry. Springer, Berlin, Heidelberg. https://doi.org/10.1007/698_2024_1190  

• Santana, E., Ibrahimi, E., Ntalianis, E., Cauwenberghs, N., & Kuznetsova, T. (2024). Integrating Metabolomics Domain Knowledge with Explainable Machine Learning in Atherosclerotic Cardiovascular Disease Classification. International Journal of Molecular Sciences, 25(23), 12905. https://doi.org/10.3390/ijms252312905   

• Porreca, A., Ibrahimi, E., Maturo, F., Marcos Zambrano, L. J., Meto, M., & Lopes, M. B. (2024). Robust prediction of colorectal cancer via gut microbiome 16S rRNA sequencing data. Journal of Medical Microbiology, 73(10), 001903. https://doi.org/10.1099/jmm.0.001903 

• Noga, F., Hoti, E., Ibrahimi, E., Toma, D., & Malaj, L. (2024). Perceptions and experiences of community pharmacists with off-label prescribing in the pediatric population. International Journal of Pharmacy Practice, 32(5), 355-362. https://doi.org/10.1093/ijpp/riae031 

• Aliko, V., Vasjari, L., Ibrahimi, E., Impellitteri, F., Karaj, A., Gjonaj, G., ... & Istifli, E. S. (2024). “From shadows to shores”-quantitative analysis of CuO nanoparticle-induced apoptosis and DNA damage in fish erythrocytes: A multimodal approach combining experimental, image-based quantification, docking and molecular dynamics. Science of the Total Environment, 906, 167698. https://doi.org/10.1016/j.scitotenv.2023.167698  

• Ibrahimi, E*., Lopes, M. B., Dhamo, X., Simeon, A., Shigdel, R., Hron, K., Stres, B., Berland, M., & Judith, L. (2023). Overview of data preprocessing for machine learning applications in human microbiome research. Frontiers in Microbiology, 14, 1250909. https://doi.org/10.3389/fmicb.2023.1250909 

• Berberi, S., Ibrahimi, E*. & Bego, F. Modeling the Dynamics of Avian Populations in Europe (1980–2019) through Generalized Additive Mixed Models. Biol Bull Russ Acad Sci 50 (Suppl 4), S686–S693 (2023). https://doi.org/10.1134/S1062359023603762  

• Ibrahimi, E*., Miri, F., Koçiaj, I. (2024). An assessment of the integration of ICTs into teaching processes by science teachers: The case of Albania. Journal of Technology and Science Education, [S.l.], v. 14, n. 2, p. 405-417. https://doi.org/10.3926/jotse.2319 

• Papoutsoglou, G., Tarazona, S., Lopes, M. B., Klammsteiner, T., Ibrahimi, E., Eckenberger, J., Novielli, P., Tonda, A., Simeon, A., Shigdel, R., Béreux, S., Vitali, G., Tangaro, S., Lahti, L., Temko, A., Claesson, M. J., & Berland, M. (2023). Machine learning approaches in microbiome research: Challenges and best practices. Frontiers in Microbiology, 14, 1261889. https://doi.org/10.3389/fmicb.2023.1261889 

• Aliko, V., Vasjari, L., Ibrahimi, E., Impellitteri, F., Karaj, A., Gjonaj, G., Piccione, G., Arfuso, F., Faggio, C., & Istifli, E. S. (2023). “From shadows to shores”-quantitative analysis of CuO nanoparticle-induced apoptosis and DNA damage in fish erythrocytes: A multimodal approach combining experimental, image-based quantification, docking and molecular dynamics. Science of The Total Environment, 906, 167698. https://doi.org/10.1016/j.scitotenv.2023.167698 

• Judith, L., Manuel, V., Frohme, M., Klammsteiner, T., Ibrahimi, E., Lahti, L., Dhamo, X., Simeon, A., Nechyporenko, A., Pio, G., Przymus, P., Sampri, A., Trajkovik, V., Aasmets, O., Araujo, R., Anagnostopoulos, I., Aydemir, Ö., Berland, M., Calle, M. L., . . . Truu, J. (2023). A toolbox of machine learning software to support microbiome analysis. Frontiers in Microbiology, 14, 1250806. https://doi.org/10.3389/fmicb.2023.1250806 

• D'Elia, D., Truu, J., Lahti, L., Berland, M., Papoutsoglou, G., Ceci, M., Zomer, A., Lopes, M. B., Ibrahimi, E., Gruca, A., Nechyporenko, A., Frohme, M., Klammsteiner, T., Pau, E. C., Judith, L., Hron, K., Pio, G., Simeon, A., Suharoschi, R., Temko, A., . . . Claesson, M. J. (2023). Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology, 14, 1257002. https://doi.org/10.3389/fmicb.2023.1257002 

• Meço, M., Hyska, E.D. & Ibrahimi, E. (2024) Comparative Analysis of the Morphological Features of Hypericum haplophylloides in Different Populations. Biol Bull Russ Acad Sci. 1-7. https://doi.org/10.1134/S1062359023605347  

• Xhelili, P., Ibrahimi, E*., Rruci, E., & Sheme, K. (2021). Adaptation and perception of online learning during COVID-19 pandemic by Albanian university students. International Journal on Studies in Education (IJonSE), 3(2), 103-111. https://doi.org/10.46328/ijonse.49 

• Ibrahimi, E*., Kërri, A., Kuci, A. (2018). Roli i mënyrës së jetesës në parametrat e hemostazës: Përmbledhje e Literaturës. BSHN, 29, 128-138. https://jns.edu.al/wp-content/uploads/2023/08/4_Review_Eliana_Ibrahimi_A_Kerri_A_Kuci_Perf_239e884064.pdf 

• Ibrahimi E*. Data analysis and documentation of statistics in biomedical research papers in Albania. Biostatistics Epidemiol Int J. (2018);1(1): 18-20.  https://epa.hu/03500/03509/00002/pdf/EPA03509_beij_2018_1_018-020.pdf 

• Kokojka, F., Lleshaj, A., Rrudho, I., Allgjata, F., Ibrahimi, E. (2017). Shëndeti emocional dhe motivimi tek studentët Shqiptarë. BSHN, 25, 42-50. https://jns.edu.al/wp-content/uploads/2023/08/5_F_Kokojka_et_al_rreg_a2047ba72f.pdf

• Kasmi, I., Sallabanda, S., Kasmi, G., Ibrahimi, E. (2015). Nosocomial blood stream infections in pediatric intensive care unit in Albania. JNTS, XX (2), 81-91. https://akad.gov.al/ash/pdf/periodike/JNTS-2-2015.pdf