Seferina Mavroudi

Current Academic Year:

• Health Informatics
• Biostatistics
• Bioinformation
• Biomedical Databases

Previous Academic Years:

• Health Informatics
• Biostatistics
• Research Methodology
• Bioinformation
• Biomedical Databases

 ACADEMIC DEGREES

  ACADEMIC CAREER

PREVIOUS WORK EXPERIENCE

RESEARCH INTERESTS

• Biomedical Informatics
• Bioinformatics
• Computational Intelligence
• Machine Learning

PARTICIPATION IN SCIENTIFIC JOURNALS COMMITTEES

• PC Member, 10^th International Conference on Information, Intelligence,  Systems and Applications, IISAA 2019 , Patras 15-17 July, Greece, 2019

• PC Member of the 3rd Workshop on New Methods and Tools for Big Data (MT4BD-2016), 16-18 September 2016, Thessaloniki – Greece
• PC Member of the 3rd Workshop on Mining Humanistic Data, AIAI 2014 10th International Conference on Artificial Intelligence Applications and Innovation 19-21 September, Rhodes, Greece, 2014
• Organizing Committee of the Computational Intelligence Applications in Bioinformatics (CIAB 2013) Workshop, 14^th EANN Conference on Engineering Applications of Neural Networks 2013 (EANN 2013), Halkidiki, Greece, 13-16 September, 2013
• Organizing Committee of the Computational Intelligence Applications in Bioinformatics (CIAB 2012) Workshop, International Conference on Engineering Applications of Neural Networks 2012 (EANN 2012), London, England, 20-23 September, 2012
• Organizing Committee of the Computational Intelligence Applications in Bioinformatics (CIAB 2011) Workshop, Artificial Intelligence Applications and Innovations 2011 (EANN/AIAI 2011), Corfu Greece, September 2011
• Local Organizing Committee of the 2nd Summer School on Emerging Technologies in Biomedicine, Patras 20th June- 25th June 2004.

ANNOUNCEMENTS AT GREEK / INTERNATIONAL CONFERENCES: 47

PUBLICATIONS IN  INTERNATIONAL JOURNALS: 38

SELECTED SCIENTIFIC PUBLICATIONS

Selected Publications in peer-reviewed International Journal

1. “Reducing Opioid Prescriptions by Identifying Responders on Topical Analgesic Treatment Using an Individualized Medicine and Predictive Analytics Approach”, Gudin, J., Mavroudi, S., Korfiati, A., Theofilatos, K., Dietze, D., & Hurwitz, P., Journal of Pain Research 13, 1255-1266, 2020, https://doi.org/10.2147/JPR.S246503
2. “Discovery of stroke-related blood biomarkers from gene expression network models”, Theofilatos, K., Korfiati, A., Mavroudi, S. Cowperthwaite M., Shpak, M., BMC Med Genomics 12, 118, 2019, https://doi.org/10.1186/s12920-019-0566-8
3. “An Adaptive Pipeline To Maximize Isobaric Tagging Data in Large-Scale MS-Based Proteomics”, Corthésy, J., Theofilatos, K., Mavroudi, S., Macron, C., Cominetti, O., Remlawi, M., ... & Dayon, L., Journal of Proteome Research 17 (6), 2165-2173, 2018, https://doi.org/10.1021/acs.jproteome.8b00110
4. “Prediction overlapping protein complexes from weighted protein interaction graphs by gradually expanding dense neighborhoods”, Dimitrakopoulos, C., Theofilatos, K., Pegkas, A., Likothanassis, S., & Mavroudi, S., Artificial intelligence in medicine, 71, 62-69, 2016, https://doi.org/10.1016/j.artmed.2016.05.006
5. “Quo vadis computational analysis of PPI data or why the future isn’t here yet.”, Theofilatos, K. A., Likothanassis, S., & Mavroudi, S., Frontiers in genetics, 6, 289, 2015, https://doi.org/10.3389/fgene.2015.00289
6. “Predicting Human miRNA Target Genes Using a Novel Computational Intelligent Framework”, Korfiati, A., Theofilatos, K., Kleftogiannis, D., Alexakos, C., Likothanassis, S., & Mavroudi, S., Information Sciences, 294, 576-585, 2015, http://dx.doi.org/10.1016/j.ins.2014.09.016
7. “Predicting protein complexes from weighted protein–protein interaction graphs with a novel unsupervised methodology: evolutionary enhanced Markov clustering”, Theofilatos, K., Pavlopoulou, N., Papasavvas, C., Likothanassis, S., Dimitrakopoulos, C., Georgopoulos, E., ... & Mavroudi, S., Artificial intelligence in medicine, 63 (3), 181-189., 2015, https://doi.org/10.1016/j.artmed.2014.12.012
8. “ncRNAclass: A web platform for non-coding RNA feature calculation, microRNA prediction and microRNA target prediction”, Karathanou, K., Theofilatos, K., Kleftogiannis, D., Alexakos, C., Likothanassis, S., Tsakalidis, A., & Mavroudi, S., International Journal on Artificial Intelligence Tools, 24 (01), 1540002, 2015, https://doi.org/10.1142/S0218213015400023
9. “YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features”, Kleftogiannis, D., Theofilatos, K., Likothanassis, S., & Mavroudi, S., IEEE/ACM transactions on computational biology and bioinformatics, 12 (5), 1183-1192, 2015,
   https://doi.org/10.1109/TCBB.2014.2388227
10. “EnsembleGASVR: A novel ensemble method for classifying missense Single Nucleotide Polymorphisms.”, Rapakoulia, T., Theofilatos, K., Kleftogiannis, D., Likothanasis, S., Tsakalidis, A., & Mavroudi, S., Bioinformatics, 30 (16), 2324-2333, 2014, https://doi.org/10.1093/bioinformatics/btu297
11. “A hybrid support vector fuzzy inference system for the classification of leakage current waveforms portraying discharges”, Theofilatos, K., Pylarinos, D., Likothanassis, S., Melidis, D., Siderakis, K., Thalassinakis, E., & Mavroudi, S., Electric Power Components and Systems, 42 (2), 180-189, 2014, https://doi.org/10.1080/15325008.2013.853217
12. “The Human Interactome Knowledge Base (HINT-KB): an integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique”, Theofilatos, K., Dimitrakopoulos, C., Likothanassis, S., Kleftogiannis, D., Moschopoulos, C., Alexakos, C., ... & Mavroudi, S., Artificial Intelligence Review, 42(3), 427-443, 2013, https://doi.org/10.1007/s10462-013-9409-8
13. “Where we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory role”, Kleftogiannis, D., Korfiati, A., Theofilatos, K., Likothanassis, S., Tsakalidis, A., & Mavroudi, S., Journal of biomedical informatics, 46 (3), 563-573, 2013, https://doi.org/10.1016/j.jbi.2013.02.002
14. “Computational Approaches for the Prediction of Protein-Protein Interactions: A Survey”, A Theofilatos, K., M Dimitrakopoulos, C., K Tsakalidis, A., D Likothanassis, S., T Papadimitriou, S., & P Mavroudi, S., Current Bioinformatics, 6(4), 398-414, 2011, https://doi.org/10.2174/157489311798072981
15. “Mutual Information Clustering For Efficient Mining Of Fuzzy Association Rules With Application To Gene Expression Data Analysis”, Papadimitriou, S., Mavroudi, S., & Likothanassis, S. D., International Journal on Artificial Intelligence Tools, 15 (02), 227-250, 2006, https://doi.org/10.1142/S0218213006002643
16. “Gene Expression Analysis with a Dynamically extended Self-Organized Map that exploits class information”, Mavroudi, S., Papadimitriou, S., & Bezerianos, A., Bioinformatics, 18(11), 1446-1453, 2002, https://doi.org/10.1093/bioinformatics/18.11.1446
17. "Ischemia Detection with a Self Organizing Map supplemented by Supervised Learning”, Papadimitriou, S., Mavroudi, S., Vladutu, L., & Bezerianos, A., IEEE Transactions on Neural Networks, 12(3), 503-515, 2001, https://doi.org/10.1109/72.925554

Selected Publications in Book/Book Chapters

1. “Computational intelligence: Recent advances, perspectives and open problems”, Theofilatos, K., Georgopoulos, E., Likothanassis, S., Mavroudi, S. Computational Intelligence Techniques for Trading and Investment, pp. 3-21. Taylor and Francis (Series: Advances in Experimental and Computable Economics), ISBN: 978-0-415-63680-3, 2014
2. “Πρωτεϊνική Ανάλυση”, Χ. Μοσχόπουλος, Σ. Μαυρουδή, Σ. Κοσσίδα, Βιοπληροφορική – Δυνατότητες και Προοπτικές, Κεφάλαιο 11, σελ. 173-186, Εκδόσεις: Ίδρυμα Ιατροβιολογικών Ερευνών της Ακαδημίας Αθηνών, 2008

Selected Publications in peer-reviewed International Conferences

1. Gudin, J., Mavroudi, S., Korfiati, A., Theofilatos, K., Dietze, D., & Hurwitz, P. (2019, July). A precision medicine approach for non-opioid pain therapy using a combination of multi-objective optimization and support vector regression. In 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)(pp. 1-7). IEEE, Greece, DOI: 10.1109/IISA.2019.8900689
2. Hastings, M., Theofilatos, K., Mavroudi, S., (2018). Combining network theory and machine learning to identify a diagnostic and prognostic biosignature for Glioblastoma, In Proceedings of the 11th annual RECOMB/ISCB Conference on Regulatory & Systems Genomics conference, New York City, USA, December 2018
3. Theofilatos, K., Tatsi, K., Mavroudi, S., Georgakilas, A. (2017). Deciphering the impact of radiation therapies in molecular level using biological network based bioinformatics technique, In Proceedings of the CPRIT Innovations in Cancer Prevention and Research, Austin, USA November 2017
4. Corthésy, J., Theofilatos, K., Mavroudi, S., Cominetti, O., Remlawi, M., Ferraro, F., Núñez Galindo, A., Montoliu, I., Kussmann, M., Likothanassis, S., Dayon, L., (2016). Maximizing shotgun proteomics isobaric tagging data output using MS/MS multi-objective optimization algorithm, In Proceedings of the American Society for Mass Spectrometry on June 2016, San Antonio, USA.
5. Kontaxakis, J., Sangriotis, M., Angelopoulou, R., Plastira, K., Sgouros, N., Mavroudi, S. (2007). Automatic Analysis of TUNEL assay Microscopy Images, The 7th IEEE International Symposium on Signal Processing and Information Technology, Biomedical Signal Processing Session, pp 1172-1176, December 15-18, Cairo Egypt, 2007
6. Dragomir, A., Mavroudi, S., Bezerianos, A. (2004). Tumor classification using ensembles of support vector machines and boosting, The Workshop on Genomic Signal Processing and Statistics (GENSIPS 2004), Baltimore, Maryland, USA
7. Mavroudi, S., Dragomir, A., Papadimitriou, S., Bezerianos, A. (2003). Integrating Supervised and Unsupervised Learning in Self Organizing Maps for Gene Expression Data Analysis, ICANN/ICONIP, June 26-29, 2003, Istanbul, Turkey published in Lecture Notes in Computer Science 2714, pp. 262-270
8. Mavroudi, S., Papadimitriou, S., Bezerianos, A. (2002). Gene Expression Analysis By A Novel Dynamically Extendable Self-Organized Map Integrating Unsupervised And Supervised Learning, Poster-session, RECOMB 2002, The Sixth Annual International Conference on Research in Computational Molecular Biology, Washington, DC, April 18-21, 2002
9. Vladutu, L., Papadimitriou, S., Mavroudi, S., Bezerianos, A. (2001). Ischemia Detection using Supervised Learning for Hierarchical Neural Networks based on Kohonen -Maps, Τhe 23rd IEEE-EMBS Conference, Istanbul, 25-28 October 2001, Proceedings, 2, 1688-1691
10. Vladutu, L., Papadimitriou, S., Mavroudi, S., Bezerianos, A. (2001). Generalized RBF Networks trained with Instance Based Training for mining Symbolic Data, The 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-01), April 16-18, 2001, Hong Kong, published in Lecture Notes in Artificial Intelligence, Advances in Knowledge Discovery and Data Mining,Edts. David Cheung, Graham J. Williams, Qing Li, Springer-Verlang, pp. 587-594
11. Papadimitriou, S., Bezerianos, A., Vladutu, L., Mavroudi, S. (2000). Detection of ischemic episodes with a combination of supervised and unsupervised learning, the Int. Conference On Computational Intelligence, Slovakia, ISCI 2000, 29 August – 1 September 2000 published in "The State of the Art in Computational Intelligence",Physica-Verlag, SPRINGER, 2000,P. Sincak, J. Vascak, V. Kvasnicka, R. Mesiar,Eds.

Selected Publications in peer-reviewed Hellenic Conferences

1. Pappa I., Nikou S., Korfiati A., Theofilatos K., Mavroudi S., Bravou V. Deciphering the importance of focal adhesion proteins in lung adenocarcinoma with bioinformatics tools. 70th National Conference of the Hellenic Society of Biochemistry and Molecular Biology, 29th November – 1st December 2019. Athens, Greece.
2. Korfiati, D., Kleftogiannis, K. Theofilatos, S. Likothanassis, A. Tsakalidis, S. Mavroudi, “Predicting Human miRNA Target Genes Using a Novel Evolutionary Methodology”, Artificial Intelligence: Theories, Models and Applications, 8th Hellenic Conference on AI, SETN 2012 Lamia, Greece, May 2012. (Best Student Award) Lecture Notes in Computer Science, Springer Verlag, 2012, Volume 7297/2012, 291-298, DOI:10.1007/978-3-642-30448-4_37