COMPUTATIONAL & DATA SCIENCE PREPRINT REPOSITORY

Computational & Data Science Preprint Repository

ABOUT PUBLICATIONS

ABOUT

The Data Science Group was established in 2019 and focuses on a) methodological research questions related to data science and algorithmic artificial intelligence, b) foundational questions regarding the best achievable performance limits in various tasks of data modeling, analysis and inference, and c) interdisciplinary research questions from a wide variety of research domains, including Social Sciences, Geo-Sciences, Bioinformatics and Biomedical Engineering, Environmental and Transportation Engineering, among others. Current activity areas include frequentist and Bayesian spatio-temporal modelling, the development of information-theoretic tools, high-dimensional and functional data analysis, time-series forecasting and online predictive and anomaly detection algorithms. Researchers from the Data Science Group participate in the Statistical Learning Lab, which fosters multidisciplinary collaborations, develops software products, research publications and patents and contributes to the education and training of students and young researchers.

This page is under construction.

PUBLICATIONS

2023
- Tzirakis K, Kamarianakis Y, Kontopodis N, Ioannou CV. Classification of Blood Rheological Models through an Idealized Symmetrical Bifurcation. Symmetry. 2023; 15(3):630
- Mazaris,AD, Dimitriadis, C, Papazekou, M, Schofield, G, Doxa, A, Chatzimentor, A, Turkozan, O, Katsanevakis S, Lioliou A, Abalo-Morla S, Aksissou M, Arcangeli A, Attard V, Atttiri H, Hili EI,Atzori F, Belda EJ, Nakhla LB, Berbash AA, Bjorndal KA, Broderick AC, Camiñas JA, Candan O, Cardona I, Cetkovic I, Dakik N, Andrea de Lucia G, Dimitrakopoulos PS, Diryaq S, Favilli C, Fortuna, CM, Fuller WJ, Gallon S, Hamza A, Jribi I, Ben Ismail M, Kamarianakis, Y, Kaska Y Korro K, Koutsoubas D, Lauriano G, Lazar B, March D, Marco A, Minotou C, Monsinjon JR, Naguib NM, Palialexis A, Piroli V, Karaa Sami K, Sönmez B, Sourbès L, Sözbilen, D, Vandeperre, F, Vignes, P, Xanthakis, M, Köpsel, V, Peck, MA, Priorities for Mediterranean marine turtle conservation and management in the face of climate change, Journal of Environmental Management, Volume 339, 2023, 117805
- Tzirakis, K., Kamarianakis, Y., Kontopodis, N., Ioannou, C.V. The Effect of Blood Rheology and Inlet Boundary Conditions on Realistic Abdominal Aortic Aneurysms under Pulsatile Flow Conditions (2023) Bioengineering, 10 (2), art. no. 272.
- Georgoulis, E.H., Loulakis, M., Tsiourvas, A. Discrete gradient flow approximations of high dimensional evolution partial differential equations via deep neural networks (2023) Communications in Nonlinear Science and Numerical Simulation, 117, art. no. 106893.
- Ntroumpogiannis, A., Giannoulis, M., Myrtakis, N., Christophides, V., Simon, E., Tsamardinos, I. A meta-level analysis of online anomaly detectors (2023) VLDB Journal.
2022
- Doxa, A., Kamarianakis, Y., Mazaris, A.D. Spatial heterogeneity and temporal stability characterize future climatic refugia in Mediterranean Europe (2022) Global Change Biology, 28 (7), pp. 2413-2424.
- Birrell, J., Katsoulakis, M.A., Pantazis, Y. Optimizing Variational Representations of Divergences and Accelerating Their Statistical Estimation (2022) IEEE Transactions on Information Theory, 68 (7), pp. 4553-4572.
- Tsourtis, A., Papoutsoglou, G., Pantazis, Y. GAN-Based Training of Semi-Interpretable Generators for Biological Data Interpolation and Augmentation (2022) Applied Sciences (Switzerland), 12 (11), art. no. 5434, .
- Karagiannaki, I., Gourlia, K., Lagani, V., Pantazis, Y., Tsamardinos, I. Learning biologically-interpretable latent representations for gene expression data: Pathway Activity Score Learning Algorithm (2022) Machine Learning, .
- Pantazis, Y., Paul, D., Fasoulakis, M., Stylianou, Y., Katsoulakis, M.A. Cumulant GAN (2022) IEEE Transactions on Neural Networks and Learning Systems, .
- Birrell, J., Dupuis, P., Katsoulakis, M.A., Pantazis, Y., Rey-Bellet, L. (f,Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics (2022) Journal of Machine Learning Research, 23, .
- Kominis, I.K., Loulakis, M. Quantum advantage in biometric authentication with single photons (2022) Journal of Applied Physics, 131 (8), art. no. 084401.
- Tsamardinos, I. Don't lose samples to estimation (2022) Patterns, 3 (12), art. no. 100612, .
- Bowler, S., Papoutsoglou, G., Karanikas, A., Tsamardinos, I., Corley, M.J., Ndhlovu, L.C. A machine learning approach utilizing DNA methylation as an accurate classifier of COVID-19 disease severity (2022) Scientific Reports, 12 (1), art. no. 17480, .
- Tsamardinos, I., Charonyktakis, P., Papoutsoglou, G., Borboudakis, G., Lakiotaki, K., Zenklusen, J.C., Juhl, H., Chatzaki, E., Lagani, V. Just Add Data: automated predictive modeling for knowledge discovery and feature selection (2022) npj Precision Oncology, 6 (1), art. no. 38, .
- Marshall, J.L., Peshkin, B.N., Yoshino, T., Vowinckel, J., Danielsen, H.E., Melino, G., Tsamardinos, I., Haudenschild, C., Kerr, D.J., Sampaio, C., Rha, S., FitzGerald, K.T., Holland, E.C., Gallagher, D., Garcia-Foncillas, J., Juhl, H. The Essentials of Multiomics (2022) Oncologist, 27 (4), pp. 272-284.
- Karaglani, M., Panagopoulou, M., Baltsavia, I., Apalaki, P., Theodosiou, T., Iliopoulos, I., Tsamardinos, I., Chatzaki, E. Tissue‐Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach (2022) International Journal of Molecular Sciences, 23 (6), art. no. 2959, .
- Karaglani, M., Panagopoulou, M., Cheimonidi, C., Tsamardinos, I., Maltezos, E., Papanas, N., Papazoglou, D., Mastorakos, G., Chatzaki, E. Liquid Biopsy in Type 2 Diabetes Mellitus Management: Building Specific Biosignatures via Machine Learning (2022) Journal of Clinical Medicine, 11 (4), art. no. 1045, .
- Biza, K., Tsamardinos, I., Triantafillou, S. Out-of-Sample Tuning for Causal Discovery (2022) IEEE Transactions on Neural Networks and Learning Systems, pp. 1-11.
- Plakandaras, V., Gogas, P., Papadimitriou, T., Tsamardinos, I. Credit Card Fraud Detection with Automated Machine Learning Systems (2022) Applied Artificial Intelligence, 36 (1), art. no. 2086354, .
- Karagiannaki, I., Gourlia, K., Lagani, V., Pantazis, Y., Tsamardinos, I. Learning biologically-interpretable latent representations for gene expression data: Pathway Activity Score Learning Algorithm (2022) Machine Learning, .
- Tsagris, M., Papadovasilakis, Z., Lakiotaki, K., Tsamardinos, I. The γ-OMP Algorithm for Feature Selection With Application to Gene Expression Data (2022) IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19 (2), pp. 1214-1224.
2021
- Tsourtis, A., Papoutsoglou, G., Pantazis, Y. Efficient discrimination between biological populations via neural-based estimation of RÉnyi divergence (2021) UNCECOMP Proceedings, 2021-June, .
- Paul, D., Mukherjee, S., Pantazis, Y., Stylianou, Y. A universal multi-speaker multi-style text-to-speech via disentangled representation learning based on Rényi divergence minimization (2021) Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 5, pp. 3541-3545.
- Papoutsoglou, G., Karaglani, M., Lagani, V., Thomson, N., Røe, O.D., Tsamardinos, I., Chatzaki, E. Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets (2021) Scientific Reports, 11 (1), art. no. 15107, .
- Borboudakis, G., Tsamardinos, I. Extending greedy feature selection algorithms to multiple solutions (2021) Data Mining and Knowledge Discovery, 35 (4), pp. 1393-1434.
- Rounis, K., Makrakis, D., Papadaki, C., Monastirioti, A., Vamvakas, L., Kalbakis, K., Gourlia, K., Xanthopoulos, I., Tsamardinos, I., Mavroudis, D., Agelaki, S. Prediction of outcome in patients with non-small cell lung cancer treated with second line PD-1/PDL-1 inhibitors based on clinical parameters: Results from a prospective, single institution study (2021) PLoS ONE, 16 (6 June), art. no. e0252537, .
- Nissen, L.R., Tsamardinos, I., Eskelund, K., Gradus, J.L., Andersen, S.B., Karstoft, K.-I. Forecasting military mental health in a complete sample of Danish military personnel deployed between 1992-2013 (2021) Journal of Affective Disorders, 288, pp. 167-174.
- Myrtakis, N., Tsamardinos, I., Christophides, V. PROTEUS: Predictive explanation of anomalies (2021) Proceedings - International Conference on Data Engineering, 2021-April, art. no. 9458931, pp. 1967-1972.
- Panagopoulou, M., Karaglani, M., Manolopoulos, V.G., Iliopoulos, I., Tsamardinos, I., Chatzaki, E. Deciphering the methylation landscape in breast cancer: Diagnostic and prognostic biosignatures through automated machine learning (2021) Cancers, 13 (7), art. no. 1677, . Planell, N., Lagani, V.,
- Sebastian-Leon, P., van der Kloet, F., Ewing, E., Karathanasis, N., Urdangarin, A., Arozarena, I., Jagodic, M., Tsamardinos, I., Tarazona, S., Conesa, A., Tegner, J., Gomez-Cabrero, D. STATegra: Multi-Omics Data Integration – A Conceptual Scheme With a Bioinformatics Pipeline (2021) Frontiers in Genetics, 12, art. no. 620453, .
- Marcos-Zambrano, L.J., Karaduzovic-Hadziabdic, K., Loncar Turukalo, T., Przymus, P., Trajkovik, V., Aasmets, O., Berland, M., Gruca, A., Hasic, J., Hron, K., Klammsteiner, T., Kolev, M., Lahti, L., Lopes, M.B., Moreno, V., Naskinova, I., Org, E., Paciência, I., Papoutsoglou, G., Shigdel, R., Stres, B., Vilne, B., Yousef, M., Zdravevski, E., Tsamardinos, I., Carrillo de Santa Pau, E., Claesson, M.J., Moreno-Indias, I., Truu, J., ML4Microbiome Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment (2021) Frontiers in Microbiology, 12, art. no. 634511, .
- Papadogiorgaki, M., Venianaki, M., Charonyktakis, P., Antonakakis, M., Tsamardinos, I., Zervakis, M.E., Sakkalis, V. Heart Rate Classification Using ECG Signal Processing and Machine Learning Methods (2021) BIBE 2021 - 21st IEEE International Conference on BioInformatics and BioEngineering, Proceedings, .
- Agrapetidou, A., Charonyktakis, P., Gogas, P., Papadimitriou, T., Tsamardinos, I. An AutoML application to forecasting bank failures (2021) Applied Economics Letters, 28 (1), pp. 5-9.
2020
- Pantazis, Y., Tselas, C., Lakiotaki, K., Lagani, V., Tsamardinos, I. Latent Feature Representations for Human Gene Expression Data Improve Phenotypic Predictions (2020) Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020, art. no. 9313286, pp. 2505-2512.
- Vernardos, G., Tsagkatakis, G., Pantazis, Y. Quantifying the structure of strong gravitational lens potentials with uncertainty-aware deep neural networks (2020) Monthly Notices of the Royal Astronomical Society, 499 (4), pp. 5641-5652.
- Velli, M.-C., Tsibidis, G.D., Mimidis, A., Skoulas, E., Pantazis, Y., Stratakis, E. Predictive modeling approaches in laser-based material processing (2020) Journal of Applied Physics, 128 (18), art. no. 018235, .
- Dupuis, P., Katsoulakis, M.A., Pantazis, Y., Rey-Bellet, L. Sensitivity analysis for rare events based on rényi divergence (2020) Annals of Applied Probability, 30 (4), pp. 1507-1533.
- Simantiraki, O., Cooke, M., Pantazis, Y. Effects of Spectral Tilt on Listeners' Preferences and Intelligibility (2020) ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2020-May, art. no. 9054117, pp. 6254-6258.
- Paul, D., Shifas, M.P.V., Pantazis, Y., Stylianou, Y. Enhancing speech intelligibility in text-to-speech synthesis using speaking style conversion (2020) Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2020-October, pp. 1361-1365.
- Paul, D., Pantazis, Y., Stylianou, Y. Speaker conditional WaveRNN: Towards universal neural vocoder for unseen speaker and recording conditions (2020) Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2020-October, pp. 235-239.
- Karagiannaki, I., Pantazis, Y., Chatzaki, E., Tsamardinos, I. Pathway Activity Score Learning for Dimensionality Reduction of Gene Expression Data (2020) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12323 LNAI, pp. 246-261.
- Giacomazzo, M., Kamarianakis, Y. Bayesian estimation of subset threshold autoregressions: short-term forecasting of traffic occupancy (2020) Journal of Applied Statistics, 47 (13-15), pp. 2658-2689.
- Nikoloudakis, N., Stagakis, S., Mitraka, Z., Kamarianakis, Y., Chrysoulakis, N. Spatial interpolation of urban air temperatures using satellite-derived predictors (2020) Theoretical and Applied Climatology, 141 (1-2), pp. 657-672.
- Cho, N., El Asmar, M., Underwood, S., Kamarianakis, Y. Long-Term Performance Benefits of the Design-Build Delivery Method Applied to Road Pavement Projects in the U.S. (2020) KSCE Journal of Civil Engineering, 24 (4), pp. 1049-1059.
- Cheliotis, D., Kontoyiannis, I., Loulakis, M., Toumpis, S. A simple network of nodes moving on the circle (2020) Random Structures and Algorithms, 57 (2), pp. 317-338.
- Pantazis, Y., Tselas, C., Lakiotaki, K., Lagani, V., Tsamardinos, I. Latent Feature Representations for Human Gene Expression Data Improve Phenotypic Predictions (2020) Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020, art. no. 9313286, pp. 2505-2512.
- Karaglani, M., Gourlia, K., Tsamardinos, I., Chatzaki, E. Accurate blood-based diagnostic biosignatures for alzheimer’s disease via automated machine learning
  (2020) Journal of Clinical Medicine, 9 (9), art. no. 3016, pp. 1-14.
- Karstoft, K.-I., Tsamardinos, I., Eskelund, K., Andersen, S.B., Nissen, L.R. Applicability of an automated model and parameter selection in the prediction of screening-level PTSD in Danish soldiers following deployment: Development study of transferable predictive models using automated machine learning (2020) JMIR Medical Informatics, 8 (7), art. no. e17119, .
- Chatzaki, E., Tsamardinos, I. Somatic copy number aberrations detected in circulating tumor DNA can hold diagnostic value for early detection of hepatocellular carcinoma (2020) EBioMedicine, 57, art. no. 102851, .
- Tsamardinos, I., Fanourgakis, G.S., Greasidou, E., Klontzas, E., Gkagkas, K., Froudakis, G.E. An Automated Machine Learning architecture for the accelerated prediction of Metal-Organic Frameworks performance in energy and environmental applications (2020) Microporous and Mesoporous Materials, 300, art. no. 110160, .
- Verrou, K.-M., Tsamardinos, I., Papoutsoglou, G. Learning Pathway Dynamics from Single-Cell Proteomic Data: A Comparative Study (2020) Cytometry Part A, 97 (3), pp. 241-252.
- Malliaraki, N., Lakiotaki, K., Vamvoukaki, R., Notas, G., Tsamardinos, I., Kampa, M., Castanas, E. Translating vitamin D transcriptomics to clinical evidence: Analysis of data in asthma and chronic obstructive pulmonary disease, followed by clinical data meta-analysis (2020) Journal of Steroid Biochemistry and Molecular Biology, 197, art. no. 105505, .
- Karagiannaki, I., Pantazis, Y., Chatzaki, E., Tsamardinos, I. Pathway Activity Score Learning for Dimensionality Reduction of Gene Expression Data (2020) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12323 LNAI, pp. 246-261.
- Xanthopoulos, I., Tsamardinos, I., Christophides, V., Simon, E., Salinger, A. Putting the human back in the AutoML loop (2020) CEUR Workshop Proceedings, 2578.
2019
- Gomez-Cabrero, D., Tarazona, S., Ferreirós-Vidal, I., Ramirez, R.N., Company, C., Schmidt, A., Reijmers, T., Paul, V.S., Marabita, F., Rodríguez-Ubreva, J., Garcia-Gomez, A., Carroll, T., Cooper, L., Liang, Z., Dharmalingam, G., van der Kloet, F., Harms, A.C., Balzano-Nogueira, L., Lagani, V., Tsamardinos, I., Lappe, M., Maier, D., Westerhuis, J.A., Hankemeier, T., Imhof, A., Ballestar, E., Mortazavi, A., Merkenschlager, M., Tegner, J., Conesa, A. STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse (2019) Scientific Data, 6 (1), art. no. 256, .
- Lakiotaki, K., Georgakopoulos, G., Castanas, E., Røe, O.D., Borboudakis, G., Tsamardinos, I. A data driven approach reveals disease similarity on a molecular level (2019) npj Systems Biology and Applications, 5 (1), art. no. 39, .
- Fernandes, S.J., Morikawa, H., Ewing, E., Ruhrmann, S., Joshi, R.N., Lagani, V., Karathanasis, N., Khademi, M., Planell, N., Schmidt, A., Tsamardinos, I., Olsson, T., Piehl, F., Kockum, I., Jagodic, M., Tegnér, J., Gomez-Cabrero, D. Non-parametric combination analysis of multiple data types enables detection of novel regulatory mechanisms in T cells of multiple sclerosis patients (2019) Scientific Reports, 9 (1), art. no. 11996, .
- Røe, O.D., Markaki, M., Tsamardinos, I., Lagani, V., Nguyen, O.T.D., Pedersen, J.H., Saghir, Z., Ashraf, H.G. 'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial (2019) BMJ Open Respiratory Research, 6 (1), art. no. e000512, .
- Papoutsoglou, G., Lagani, V., Schmidt, A., Tsirlis, K., Cabrero, D.-G., Tegnér, J., Tsamardinos, I. Challenges in the Multivariate Analysis of Mass Cytometry Data: The Effect of Randomization (2019) Cytometry Part A, 95 (11), pp. 1178-1190.
- Pantazis, Y., Tsamardinos, I. A unified approach for sparse dynamical system inference from temporal measurements (2019) Bioinformatics, 35 (18), pp. 3387-3396.
- Loos, M.S., Ramakrishnan, R., Vranken, W., Tsirigotaki, A., Tsare, E.-P., Zorzini, V., De Geyter, J., Yuan, B., Tsamardinos, I., Klappa, M., Schymkowitz, J., Rousseau, F., Karamanou, S., Economou, A. Structural basis of the subcellular topology landscape of Escherichia coli (2019) Frontiers in Microbiology, 10, art. no. 1670, pp. 1-22.
- Panagopoulou, M., Karaglani, M., Balgkouranidou, I., Biziota, E., Koukaki, T., Karamitrousis, E., Nena, E., Tsamardinos, I., Kolios, G., Lianidou, E., Kakolyris, S., Chatzaki, E. Circulating cell-free DNA in breast cancer: size profiling, levels, and methylation patterns lead to prognostic and predictive classifiers (2019) Oncogene, 38 (18), pp. 3387-3401.
- Ewing, E., Kular, L., Fernandes, S.J., Karathanasis, N., Lagani, V., Ruhrmann, S., Tsamardinos, I., Tegner, J., Piehl, F., Gomez-Cabrero, D., Jagodic, M. Combining evidence from four immune cell types identifies DNA methylation patterns that implicate functionally distinct pathways during Multiple Sclerosis progression (2019) EBioMedicine, 43, pp. 411-423.
- Tsamardinos, I., Borboudakis, G., Katsogridakis, P., Pratikakis, P., Christophides, V. A greedy feature selection algorithm for Big Data of high dimensionality (2019) Machine Learning, 108 (2), pp. 149-202.
- Tsagris, M., Tsamardinos, I. Feature selection with the R package MXM (2019) F1000Research, 7, art. no. 1505, .
- Borboudakis, G., Tsamardinos, I. Forward-backward selection with early dropping (2019) Journal of Machine Learning Research, 20, .
- Kyriakis, D., Kanterakis, A., Manousaki, T., Tsakogiannis, A., Tsagris, M., Tsamardinos, I., Papaharisis, L., Chatziplis, D., Potamias, G., Tsigenopoulos, C.S. Scanning of genetic variants and genetic mapping of phenotypic traits in gilthead seabream through ddRAD sequencing (2019) Frontiers in Genetics, 10 (JUN), art. no. 675, .
- Ferreirós-Vidal, I., Carroll, T., Zhang, T., Lagani, V., Ramirez, R.N., Ing-Simmons, E., Gómez-Valadés, A.G., Cooper, L., Liang, Z., Papoutsoglou, G., Dharmalingam, G., Guo, Y., Tarazona, S., Fernandes, S.J., Noori, P., Silberberg, G., Fisher, A.G., Tsamardinos, I., Mortazavi, A., Lenhard, B., Conesa, A., Tegner, J., Merkenschlager, M., Gomez-Cabrero, D. Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation (2019) PLoS Biology, 17 (4), art. no. e2006506, .
- Adamou, M., Antoniou, G., Greasidou, E., Lagani, V., Charonyktakis, P., Tsamardinos, I., Doyle, M. Toward Automatic Risk Assessment to Support Suicide Prevention (2019) Crisis, 40 (4), pp. 249-256.
- Borboudakis and I. Tsamardinos (2019) Forward-backward selection with early dropping. The Journal of Machine Learning Research, 20 (1), 276-314.
- D. Kyriakis, A. Kanterakis, T. Manousaki, A. Tsakogiannis, M. Tsagris, I. Tsamardinos, L. Papaharisis, D. Chatziplis, G. Potamias and C. S. Tsigenopoulos. Scanning of genetic variants and genetic mapping of phenotypic traits in Gilthead sea bream through ddRAD sequencing. Frontiers in Genetics (2019) 10:675.
- Y. Pantazis, M. Tsagris and A.T.A. Wood (2019) Gaussian Asymptotic Limits for the α-transformation in the Analysis of Compositional Data. Sankhya A, 1-20.
- Y. Pantazis and I. Tsamardinos (2019) A unified approach for sparse dynamical system inference from temporal measurements. Bioinformatics, btz065.
- M. Tsagris and I. Tsamardinos I. (2019). Feature selection with the R package MXM. F1000Research, 7:1505.
- I. Tsamardinos, G. Borboudakis, P. Katsogridakis, P. Pratikakis and V. Christophides (2019) A greedy feature selection algorithm for Big Data of high dimensionality. Machine Learning, 108 (2), 149-202.
- B. Wang, Y. Zheng, D. Fang, Y. Kamarianakis and J. Wilson (2019) Split bootstrap hierarchical modeling of antibiotics abuse in China. Statistics in Medicine, 38, 2282-2291.