RESEARCH
PUBLICATIONS
2015
Discovering and Exploiting Entailment Relationships in Multi-Label Learning
Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos
ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2015 (KDD)
Bayesian Network Learning with Discrete Case-Control Data
Giorgos Borboudakis, Ioannis Tsamardinos
Uncertainty in Artificial Intelligence (UAI), 2015
MiRduplexSVM: A High-Performing MiRNA-Duplex Prediction and Evaluation Methodology
Nestoras Karathanasis, Ioannis Tsamardinos, Panayiota Poirazi
PLoS ONE 10(5): e0126151. doi:10.1371/journal.pone.0126151
Realization of a service for the long-term risk assessment of diabetes-related complications
Vincenzo Lagani, Franco Chiarugi, Dimitris Manousos, Vivek Verma, Jo Fursse, Kostas Marias, Ioannis Tsamardinos
Journal of Diabetes and its Complications 29(5), p. 691-698, 2015
Probabilistic Computational Causal Discovery for Systems Biology
Vincenzo Lagani, Sofia Triantafillou, Gordon Ball, Jesper Tegner, Ioannis Tsamardinos
Uncertainty in Biology, A computational Modeling Approach, Springer 2015, (Eds) Liesbet Geris, David Gomez-Cabrero
Development and validation of risk assessment models for diabetes-related complications based on the DCCT/EDIC data
Vincenzo Lagani, Franco Chiarugi, Shona Thomson, Jo Fursse, Edin Lakasing, Russell W. Jones, Ioannis Tsamardinos
Journal of Diabetes and Its Complications 2015 May-Jun;29(4):479-87. doi: 10.1016/j.jdiacomp.2015.03.001
Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets
Sofia Triantafillou, Ioannis Tsamardinos
16(Nov):2147−2205, 2015 Journal of Machine Learning Research
Performance-Estimation Properties of Cross-Validation-Based Protocols with Simultaneous Hyper-Parameter Optimization
Ioannis Tsamardinos, Amin Rakhshani, and Vincenzo Lagani
Int. J. Artif. Intell. Tools 24, 1540023 (2015)
T-Recs: Stable selection of Dynamically Formed Groups of Features with Application to Prediction of Clinical Outcomes
Grace T. Huang, Ioannis Tsamardinos, Vineet Raghu, Naftali Kaminski, Panayiotis V. Benos
Pacific Symposium on Biocomputing (PSB) 2015
2014
Hidden treasures in “ancient” microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue
Kerkentzes Konstantinos, Lagani Vincenzo, Tsamardinos Ioannis, Vyberg Mogens, Oluf D. Røe
Frontiers in Oncology 4, 2014, doi: 10.3389/fonc.2014.00251
Learning Neighborhoods of High Confidence in Constraint-Based Causal Discovery
Sofia Triantafillou, Ioannis Tsamardinos, and Anna Roumpelaki
Seventh European Workshop on Probabilistic Graphical Models (PGM), 2014
Don't use a cannon to kill the ... miRNA mosquito
Nestoras Karathanasis; Ioannis Tsamardinos; Panayiota Poirazi
Bioinformatics 2014; doi: 10.1093/bioinformatics/btu100
Performance-Estimation Properties of Cross-Validation-Based Protocols with Simultaneous Hyper-Parameter Optimization
Ioannis Tsamardinos, Amin Rakhshani, Vincenzo Lagani
8th Hellenic Conference on Artificial Intelligence (SETN) 2014
2013
DNA Damage Triggers a Chronic Autoinflammatory Response, Leading to Fat Depletion in NER Progeria
Ismene Karakasilioti, Irene Kamileri, Georgia Chatzinikolaou, Theodoros Kosteas, Eleni Vergadi, Andria Rasile Robinson, Ioannis Tsamardinos, Tania A. Rozgaja, Sandra Siakouli, Christos Tsatsanis, Laura J. Niedernhofer, and George A. Garinis
Cell Metabolism 18(3), Sep. 2013, 403-415
A bioinformatics approach for investigating the determinants of Drosha processing
Nestoras Karathanasis, Angelos Armen, Ioannis Tsamardinos and Panayiota Poirazi
13th IEEE International Conference on Bioinformatics and Bioengineering (IEEE BIBE 2013)
Scoring and Searching over Bayesian Networks with Informative, Causal and Associative Priors
Giorgos Borboudakis, Ioannis Tsamardinos
Uncertainty in Artificial Intelligence (UAI) 2013
Biomarker signature identification in “omics” data with multi-class outcome
Vincenzo Lagani, George Kortas, Ioannis Tsamardinos
Computational and Structural Biotechnology Journal 6, jun. 2013
A vision and strategy for the VPH: 2012 update
Hunter P, Chapman T, Coveney PV, de Bono B, Diaz V, Fenner J, Frangi AF, Harris P, Hose R, Kohl P, Lawford P, McCormack K, Mendes M, Omholt S, Quarteroni A, Shublaq N, Ska°r J, Stroetmann K, Tegner J, Thomas SR, Tollis I, Tsamardinos I, van Beek JHGM, Viceconti M.
Interface Focus 2013 3, 20130004
GATA-1 genome-wide occupancy associates with distinct epigenetic profiles in mouse fetal liver erythropoiesis
Giorgio L Papadopoulos, Elena Karkoulia, Ioannis Tsamardinos, Catherine Porcher, Jiannis Ragoussis, Jorg Bungert and John Strouboulis
Nucleic Acids Research Journal 41(9) 2013 doi: 10.1093/nar/gkt167
A Methodological Framework for Statistical Analysis of Social Text Stream
Sophia Kleisarchaki, Dimitris Kotzinos, Ioannis Tsamardinos, and Vassilis Christophides
International Workshop on Information Search, Integration and Personalization (ISIP 2012), 2013
A systematic review of predictive risk models for diabetes complications based on large scale clinical studies
Vincenzo Lagani, Lefteris Koumakis, Franco Chiarugi, Edin Lakasing, Ioannis Tsamardinos
Journal of Diabetes and Its Complications, 2013
2012
SVM-Based miRNA:miRNA* Duplex Prediction
Nestoras Karathanasis, Angelos Armen, Ioannis Tsamardinos and Panayiota Poirazi
IEEE 12th International Conference on BioInformatics and BioEngineering (BIBE 2012)
Tools and Algorithms for Causally Interpreting Directed Edges in Maximal Ancestral Graphs
Giorgos Borboudakis, Sofia Triantafillou, Ioannis Tsamardinos
The Sixth European Workshop on Probabilistic Graphical Models, (PGM) 2012
Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral Graphs
Giorgos Borboudakis, Ioannis Tsamardinos
International Conference in Machine Learning (ICML), 2012
Chemosensitivity Prediction of Tumours Based on Expression, miRNA, and Proteomics Data
Ioannis Tsamardinos, Giorgos Borboudakis, Eleni G. Christodoulou, Oluf D. Røe
International Journal of Systems Biology and Biomedical Technologies (IJSBBT), Volume 1, Issue, 2012
Learning from a mixture of experimental data: a constrained–based approach
Vincenzo Lagani, Ioannis Tsamardinos, Sofia Triantafillou
7th Hellenic Conference on Artificial Intelligence (SETN), 2012
Towards Integrative Causal Analysis of Heterogeneous Datasets and Studies
Ioannis Tsamardinos, Sofia Triantafillou, Vincenzo Lagani
Journal of Machine Learning Research 13(Apr):1097−1157, 2012
To Feature Space and Back: Identifying Top-Weighted Features in Polynomial Support Vector Machines Models
Laura E. Brown, Ioannis Tsamardinos, Douglas P. Hardin
Intelligent Data Analysis, 16(4), 2012
2011
Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition
C. Filipaki, G. Antoniou, I. Tsamardinos
International Joint Conference on Ambient Intelligence (AMI 2011)
Risk assessment models for diabetes complications: a survey of available on line tools
L. Koumakis, F. Chiarugi, V. Lagani, I. Tsamardinos
2nd International ICST Conference on Wireless Mobile Communication and Healthcare (MobiHealth 2011), Kos Island, Greece, 5-7 October 2011
A Genome-Wide Study of the Effect of Aging on Level-2 Gene-Ontology Categories in Mice Using Mixed Models
Vincenzo Lagani, Ioannis Tsamardinos, Magda Grammatikou, George Garinis
ECML/PKDD 2011, Workshop on “Data Mining in Genomics and Proteomics”
Information-Preserving Techniques Improve Chemosensitivity Prediction of Tumours Based on Expression Profiles
Eleni G. Christodoulou, Oluf Dimitri Røe, Amos Folarin, Ioannis Tsamardinos
12th Engineering Applications of Neural Networks (EANN) / 7th Artificial Intelligence Applications and Innovations (AIAI) joint conferences, Workshop on Computational Intelligence Applications in Bioinformatics (CIAB 2011)
A constraint-based approach to incorporate prior knowledge in causal models
Giorgos Borboudakis, Sofia Triantafillou,Vincenzo Lagani, Ioannis Tsamardinos
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2011)
A Unified Framework for Estimation and Control of the False Discovery Rate in Bayesian Network Skeleton Identification
Angelos P. Armen and Ioannis Tsamardinos
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2011)
2010
MatureBayes: A probabilistic algorithm for identifying the mature miRNA within novel precursors
Katerina Gkirtzou, Ioannis Tsamardinos, Panagiotis Tsakalides, Panayiota Poirazi
PLoS ONE 5(8): e11843. doi:10.1371/journal.pone.0011843
Permutation Testing Improves Bayesian Network Learning
Ioannis Tsamardinos, Giorgos Borboudakis
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2010)
Structure-Based Variable Selection for Survival Data
Vincenzo Lagani, Ioannis Tsamardinos
Bioinformatics 2010 26(15):1887-1894; doi:10.1093/bioinformatics/btq261
A vision and strategy for the virtual physiological human in 2010 and beyond
Peter Hunter, Peter V. Coveney, Bernard de Bono, Vanessa Diaz, John Fenner, Alejandro F. Frangi, Peter Harris, Rod Hose, Peter Kohl, Pat Lawford, Keith McCormack, Miriam Mendes, Stig Omholt, Alfio Quarteroni, John Skår, Jesper Tegner, S. Randall Thomas, Ioannis Tollis, Ioannis Tsamardinos, Johannes H. G. M. van Beek and Marco Viceconti
Phil. Trans. R. Soc. A 2010 368, 2595-2614
Morphological classification of heartbeats to dominant and non-dominant in ECG signals
Franco Chiarugi, Dimitra Emmanouilidou, Ioannis Tsamardinos
Physiological Measurement 31 (2010) 611-631
Learning Causal Structure from Overlapping Variable Sets
Sofia Triantafillou, Ioannis Tsamardinos, Ioannis Tollis,
Y.W. Teh and M. Titterington (Eds.), Proceedings of The Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010, JMLR: W&CP 9, pp 860-867, 2010, Chia Laguna, Sardinia, Italy, May 13-15, 2010
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification. Part I: Algorithms and Empirical Evaluation
Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
Journal of Machine Learning Research, Special Topic on Causality 11:171−234, 2010
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification. Part II: Analysis and Extensions
Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
Journal of Machine Learning Research, Special Topic on Causality 11:235−284, 2010.