RESEARCH
PUBLICATIONS
2019
STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse
David Gomez-Cabrero, Sonia Tarazona, Isabel Ferreirós-Vidal, Ricardo N. Ramirez, Carlos Company, Andreas Schmidt, Theo Reijmers, Veronica von Saint Paul, Francesco Marabita, Javier Rodríguez-Ubreva, Antonio Garcia-Gomez, Thomas Carroll, Lee Cooper, Ziwei Liang, Gopuraja Dharmalingam, Frans van der Kloet, Amy C. Harms, Leandro Balzano-Nogueira, Vincenzo Lagani, Ioannis Tsamardinos, Michael Lappe, Dieter Maier, Johan A. Westerhuis, Thomas Hankemeier, Axel Imhof, Esteban Ballestar, Ali Mortazavi, Matthias Merkenschlager, Jesper Tegner & Ana Conesa
Scientific Data, volume 6(256), 2019, doi:10.1038/s41597-019-0202-7
A "Reduced" HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial
BMJ Open Respiratory Research, 2019;6: e000512. doi: 10.1136/bmjresp-2019-000512
A data driven approach reveals disease similarity on a molecular level
Kleanthi Lakiotaki, George Georgakopoulos, Elias Castanas, Oluf Dimitri Røe, Giorgos Borboudakis, Ioannis Tsamardinos
npj Systems Biology and Applications, vol. 5(39), 2019, doi:10.1038/s41540-019-0117-0
Feature Selection with the R package MXM
Michalis Tsagris, Ioannis Tsamardinos
F1000Research, vol. 7, p. 1505, 2019
Challenges in the multivariate analysis of mass cytometry data: the effect of randomization.
Papoutsoglou G, Lagani V, Schmidt A, Tsirlis K, Gomez-Cabrero D, Tegner J, Tsamardinos I.
Cytom. Part A; to appear
Non-parametric combination analysis of multiple data types enables detection of novel regulatory mechanisms in T cells of multiple sclerosis patients
Sunjay Fernandes, Hiromasa Morikawa, Ewoud Ewing, Sabrina Ruhrmann, Rubin Narayan Joshi, Vincenzo Lagani, Nestoras Karanthanasis, Mohsen Khademi, Nuria Picola, Angelika Schmidt, Ioannis Tsamardinos, Tomas Olsson, Fredrik Piehl, Ingrid Kockum, Maja Jagodic, Jesper Tegner, and David Gomez-Cabrero
Scientific Reports 9, 2019
Structural basis of the sub-cellular topology landscape of Escherichia coli
Maria Loos, Reshmi Ramakrishnan, Wim Vranken, Alexandra Tsirigotaki, Evrydiki-Pandora Tsare, Valentina Zorzini, Jozefien De Geyter, Biao Yuan, Ioannis Tsamardinos, Maria I Klapa, Joost Schymkowitz, Frederic Rousseau, Spyridoula Karamanou, Tassos Economou
Frontiers in Microbiology 10, 2019, pp. 675, doi: 10.3389/fmicb.2019.01670
Scanning of genetic variants and genetic mapping of phenotypic traits in gilthead seabream through ddRAD sequencing
Dimitrios Kyriakis, Alexandros Kanterakis, Tereza Manousaki, Alexandros Tsakogiannis, Michalis Tsagris, Ioannis Tsamardinos, Leonidas Papaharisis, DImitris Chatziplis, George Potamias, Costas S Tsigenopoulos
Frontiers in Genetics, vol. 10, p. 675, 2019
Combining evidence from four immune cell types identifies DNA methylation patterns that implicate functionally distinct pathways during Multiple Sclerosis progression
Ewoud Ewing, Lara Kular, Sunjay Fernandes, Nestoras Karathanasis, Vincenzo Lagani, Sabrina Ruhrmann, Ioannis Tsamardinos, Jesper Tegner, Fredrik Piehl, David Gomez-Cabrero, Maja Jagodic
EBioMedicine 43 2019, 411-423
Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation
Isabel Ferreirós-Vidal, Thomas Carroll, Tianyi Zhang, Vincenzo Lagani, Ricardo N. Ramirez, Elizabeth Ing-Simmons, Alicia G. Gómez-Valadés, Lee Cooper, Ziwei Liang, Georgios Papoutsoglou, Gopuraja Dharmalingam, Ya Guo, Sonia Tarazona, Sunjay J. Fernandes, Peri Noori, Gilad Silberberg, Amanda G. Fisher, Ioannis Tsamardinos, Ali Mortazavi, Boris Lenhard, Ana Conesa, Jesper Tegner, Matthias Merkenschlager, David Gomez-Cabrero
PLoS Biol 17(4): e2006506
Forward Backward Selection with Early Dropping
Giorgos Borboudakis, Ioannis Tsamardinos
Journal of Machine Learning Research 20(8):1−39, 2019
A Unified Approach for Sparse Dynamical System Inference from Temporal Measurements
Yannis Pantazis, Ioannis Tsamardinos
Bioinformatics 2019, doi: 10.1093/bioinformatics/btz065
Circulating cell free DNA in Breast cancer: size profiling, levels and methylation patterns lead to prognostic and predictive classifiers
Maria Panagopoulou, Makrina Karaglani, Ioanna Balgkouranidou, Eirini Biziota, Triantafillia Koukaki, Evaggelos Karamitrousis, Evangelia Nena, Ioannis Tsamardinos, George Kolios, Evi Lianidou, Stylianos Kakolyris, Ekaterini Chatzaki
Oncogene 2019, 38(18):3387-3401. doi: 10.1038/s41388-018-0660-y.
2018
A Greedy Feature Selection Algorithm for Big Data of high dimensionality
Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides
Machine Learning 108(2), pp 149-202, 2018
Towards Automatic Risk Assessment to Support Suicide Prevention
Marios Adamou, Grigoris Antoniou, Elissavet Greasidou, Vincenzo Lagani, Paulos Charonyktakis, Ioannis Tsamardinos, Michael Doyle
Crisis 2018
A Validated Clinical Risk Prediction Model for Lung Cancer in Smokers of All Ages and Exposure Types: A HUNT Study
Maria Markaki, Ioannis Tsamardinos, Arnulf Langhammer, Vincenzo Lagani, Kristian Hveem, Oluf Dimitri Røe
EBioMedicine v31, 2018
Bootstrapping the Out-of-sample Predictions for Efficient and Accurate Cross-Validation
Ioannis Tsamardinos, Elissavet Greassidou, Giorgos Borboudakis
Machine Learning Journal (2018) 107(12), pp 1895–1922
Mining Free-Text Medical Notes for Suicide Risk Assessment
Marios Adamou, Grigoris Antoniou, Elissavet Greassidou, Vincenzo Lagani, Paulos Charonyktakis, Ioannis Tsamardinos
SETN 2018
Constraint-based causal discovery with mixed data
Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, and Ioannis Tsamardinos
Journal of Data Science and Analytics, (2018)
BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology
Kleanthi Lakiotaki, Nikolaos Vorniotakis, Michail Tsagris, Georgios Georgakopoulos, and Ioannis Tsamardinos
Database, 2018, 1–14, doi: 10.1093/database/bay011
Feature selection for high-dimensional temporal data
Michail Tsagris, Vincenzo Lagani and Ioannis Tsamardinos
BMC Bioinformatics (2018) 19:17, DOI 10.1186/s12859-018-2023-7
2017
Chemically-intuited, large-scale screening of MOFs by machine learning techniques
George Froudakis, George Borboudakis, Taxiarchis Stergiannakos, Maria Frysali, Emanuel Klontzas, and Ioannis Tsamardinos
NPJ Computational Materials, (2017) 3:40, doi:10.1038/s41524-017-0045-8
Predicting Causal Relationships from Biological Data: Applying Automated Casual Discovery on Mass Cytometry Data of Human Immune Cells
Sofia Triantafillou, Vincenzo Lagani, Christina Heinze-Deml, Angelika Schmidt, Jesper Tegner, Ioannis Tsamardinos
Scientific Reports 7, (2017), doi:10.1038/s41598-017-08582-x
On Scoring Maximal Ancestral Graphs with the Max-Min Hill Climbing Algorithm
Konstantinos Tsirlis, Vincenzo Lagani, Sofia Triantafillou, Ioannis Tsamardinos
23d ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2017), (2017)
Constraint-based Causal Discovery with Mixed Data
Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos
23d ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2017), (2017)
Feature Selection with the R Package MXM: Discovering Multiple, Statistically-Equivalent, Predictive Feature Subsets
Vincenzo Lagani, Giorgos Athineou, Alessio Farcomeni, Michail Tsagris, Ioannis Tsamardinos
Journal of Statistical Software v80(7), 2017 doi: 10.18637/jss.v080.i07
MatureP: prediction of secreted proteins with exclusive information from their mature regions
Georgia Orfanoudaki, Maria Markaki, Katerina Chatzi, Ioannis Tsamardinos, and Anastassios Economou
Scientific Reports 7, 2017, doi:10.1038/s41598-017-03557-4
SCENERY: a web application for (causal) network reconstruction from cytometry data
Georgios Papoutsoglou, Giorgos Athineou, Vincenzo Lagani, Iordanis Xanthopoulos, Angelika Schmidt, Szabolcs Éliás, Jesper Tegnér, Ioannis Tsamardinos
Nucleic Acids Research 37, p. D412-D416, doi:10.1093/nar/gkx448
Prothrombotic and Endothelial Inflammatory Markers in Greek Patients with Type 2 Diabetes Compared to Non-Diabetics
Siomos K, Papadakis E, Tsamardinos I, Kerkentzes K, Koygioylis M, Trakatelli CM
Endocrinology & Metabolic Syndrome 2017, 6:1, DOI: 10.4172/2161-1017.1000259
2016
omicsNPC: applying the Non-Parametric Combination methodology to the integrative analysis of heterogeneous omics data
Nestoras Karathanasis, Ioannis Tsamardinos, Vincenzo Lagani
PLoS ONE 11(11), doi:10.1371/journal.pone.0165545
A comparative evaluation of data-merging and meta-analysis methods for reconstructing gene-gene interactions
Vincenzo Lagani, Argyro D. Karozou, David Gomez-Cabrero, Gilad Silberberg and Ioannis Tsamardinos
BMC Bioinformatics 17(5), 287-305, 2016, doi=10.1186/s12859-016-1038-1
Marginal causal consistency in constraint-based causal learning
Anna Roumpelaki, Giorgos Borbudakis, Sofia Triantafillou and Ioannis Tsamardinos
UAI 2016, Workshop Causation: Foundation to Application
Score based vs constraint based causal learning in the presence of confounders
Sofia Triantafillou and Ioannis Tsamardinos
UAI 2016 workshop Causation: Foundation to Application.
Towards Robust and Versatile Causal Discovery for Business Applications
Giorgios Borboudakis, Ioannis Tsamardinos
22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016)
SCENERY: a Web-Based Application for Network Reconstruction and Visualization of Cytometry Data
G. Athineou, G. Papoutsoglou, S. Triantafullou, I Basdekis, V. Lagani, I. Tsamardinos (2016)
10th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2016).