| Applications of machine learning in human microbiome studies: a review on feature selection, biomarker identification, disease prediction and treatment LJM Zambrano, K Karaduzovic-Hadziabdic, T Loncar-Turukalo, ... Frontiers in Microbiology 12, 313, 2021 | 274 | 2021 |
| Just Add Data: automated predictive modeling for knowledge discovery and feature selection I Tsamardinos, P Charonyktakis, G Papoutsoglou, G Borboudakis, ... NPJ precision oncology 6 (1), 38, 2022 | 78 | 2022 |
| In vivo molecular imaging of cervical neoplasia using acetic acid as biomarker C Balas, G Papoutsoglou, A Potirakis IEEE Journal of Selected Topics in Quantum Electronics 14 (1), 29-42, 2008 | 51 | 2008 |
| Machine learning approaches in microbiome research: challenges and best practices G Papoutsoglou, S Tarazona, MB Lopes, T Klammsteiner, E Ibrahimi, ... Frontiers in Microbiology 14, 1261889, 2023 | 37 | 2023 |
| Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets G Papoutsoglou, M Karaglani, V Lagani, N Thomson, OD Røe, ... Scientific Reports 11 (1), 15107, 2021 | 26 | 2021 |
| Challenges in the Multivariate Analysis of Mass Cytometry Data: The Effect of Randomization G Papoutsoglou, V Lagani, A Schmidt, K Tsirlis, DG Cabrero, J Tegnér, ... Cytometry Part A 95 (11), 1178-1190, 2019 | 16 | 2019 |
| Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action D D’Elia, J Truu, L Lahti, M Berland, G Papoutsoglou, M Ceci, A Zomer, ... Frontiers in Microbiology 14, 1257002, 2023 | 14 | 2023 |
| A machine learning approach utilizing DNA methylation as an accurate classifier of COVID-19 disease severity S Bowler, G Papoutsoglou, A Karanikas, I Tsamardinos, MJ Corley, ... Scientific Reports 12 (1), 17480, 2022 | 14 | 2022 |
| Applications of machine learning in human microbiome studies: a review on feature selection, biomarker identification, disease prediction and treatment. Front Microbiol 12: 634511 LJ Marcos-Zambrano, K Karaduzovic-Hadziabdic, T Loncar Turukalo, ... | 14 | 2021 |
| Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation I Ferreirós-Vidal, T Carroll, T Zhang, V Lagani, RN Ramirez, ... PLoS biology 17 (4), e2006506, 2019 | 9 | 2019 |
| SCENERY: a web application for (causal) network reconstruction from cytometry data G Papoutsoglou, G Athineou, V Lagani, I Xanthopoulos, A Schmidt, ... Nucleic acids research 45 (W1), W270-W275, 2017 | 8 | 2017 |
| Dynamic contrast enhanced optical imaging of cervix, in vivo: A paradigm for mapping neoplasia-related parameters G Papoutsoglou, TM Giakoumakis, C Balas 2013 35th Annual International Conference of the IEEE Engineering in …, 2013 | 7 | 2013 |
| Estimation of neoplasia-related biological parameters through modeling and sensitivity analysis of optical molecular imaging data GS Papoutsoglou, C Balas IEEE Transactions on Biomedical Engineering 60 (5), 1241-1249, 2012 | 7 | 2012 |
| Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets. Sci Rep 11 (1): 15107 G Papoutsoglou, M Karaglani, V Lagani, N Thomson, OD Røe, ... | 5 | 2021 |
| GAN-Based Training of Semi-Interpretable Generators for Biological Data Interpolation and Augmentation A Tsourtis, G Papoutsoglou, Y Pantazis Applied Sciences 12 (11), 5434, 2022 | 3 | 2022 |
| Learning Pathway Dynamics from Single‐Cell Proteomic Data: A Comparative Study KM Verrou, I Tsamardinos, G Papoutsoglou Cytometry Part A 97 (3), 241-252, 2020 | 2 | 2020 |
| In silico modeling and global optimization of dynamic bio-optical processes for probing, in vivo, biological features of neoplasia G Papoutsoglou, M Stamatiadou, C Balas 2012 International Conference on Biomedical Engineering and Biotechnology …, 2012 | 2 | 2012 |
| Modelling of epithelial transport phenomena related with the acetowhitening optical characteristics: Potential for the in-vivo diagnosis of Cervical Neoplasia G Papoutsoglou, A Tsapras, WP Scouter, C Balas Technical University of Crete, 2007 | 2 | 2007 |
| MACHINE LEARNING ANALYSIS of DNA METHYLATION in COVID-19 DISEASE S Bowler, G Papoutsoglou, A Karanikas, I Tsamardinos, MJ Corley, ... Topics in Antiviral Medicine, 75-76, 2022 | | 2022 |
| mensxmachina/CyTOF-Randomization: Challenges in the multivariate analysis of mass cytometry data: the effect of randomization. G Papoutsoglou, V Lagani, A Schmidt, K Tsirlis, D Gomez-Cabrero, ... Github, 2019 | | 2019 |
