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Akshay, Akshay; Besic, Mustafa; Kuhn, Annette; Burkhard, Fiona C; Bigger-Allen, Alex; Adam, Rosalyn M; Monastyrskaya, Katia; Hashemi Gheinani, Ali (2024). Machine Learning-Based Classification of Transcriptome Signatures of Non-Ulcerative Bladder Pain Syndrome. International journal of molecular sciences, 25(3) MDPI 10.3390/ijms25031568
Akshay, Akshay; Katoch, Mitali; Shekarchizadeh, Navid; Abedi, Masoud; Sharma, Ankush; Burkhard, Fiona C; Adam, Rosalyn M; Monastyrskaya, Katia; Hashemi Gheinani, Ali (2024). Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. GigaScience, 13, pp. 1-9. Oxford University Press 10.1093/gigascience/giad111
von Siebenthal, Michelle; Akshay, Akshay; Besic, Mustafa; Schneider, Marc P; Hashemi Gheinani, Ali; Burkhard, Fiona C; Monastyrskaya, Katia (2023). Molecular Characterization of Non-Neurogenic and Neurogenic Lower Urinary Tract Dysfunction (LUTD) in SCI-Induced and Partial Bladder Outlet Obstruction Mouse Models. International journal of molecular sciences, 24(3) MDPI 10.3390/ijms24032451
Akshay, Akshay; Katoch, Mitali; Abedi, Masoud; Shekarchizadeh, Navid; Besic, Mustafa; Burkhard, Fiona C; Bigger-Allen, Alex; Adam, Rosalyn M; Monastyrskaya, Katia; Hashemi Gheinani, Ali (2022). SpheroScan: a user-friendly deep learning tool for spheroid image analysis. GigaScience, 12 Oxford University Press 10.1093/gigascience/giad082
Akshay, Akshay; Abedi, Masoud; Shekarchizadeh, Navid; Burkhard, Fiona C; Katoch, Mitali; Bigger-Allen, Alex; Adam, Rosalyn M; Monastyrskaya, Katia; Hashemi Gheinani, Ali (2022). MLcps: machine learning cumulative performance score for classification problems. GigaScience, 12 Oxford University Press 10.1093/gigascience/giad108
Hashemi Gheinani, Ali; Vögeli, Mike; Baumgartner, Ulrich; Vassella, Erik; Draeger, Annette; Burkhard, Fiona C.; Monastyrskaya-Stäuber, Katia (2018). Improved isolation strategies to increase the yield and purity of human urinary exosomes for biomarker discovery. Scientific Reports, 8(1), p. 3945. Nature Publishing Group 10.1038/s41598-018-22142-x
