Hey! I am Damianos, Bioinformatics Scientist at Platomics GmbH.
I hold a doctorate degree in Computer Science from the Faculty of Electrical Engineering and Computer Science, Gottfried Wilhelm Leibniz University. The theme of my PhD research was to apply machine learning and expert-based methods to classify distinct data types (textual streams, protein sequences and human genomic variants). I have conducted my research under the supervision of Prof. Dr. techn. Dipl.-Ing. Wolfgang Nejdl since January 2017.
My experience and interests lie in: applying machine learning and discrete algorithms for bioinformatics. If you share the same passion for such research topics, please let's follow let's connect through social media or email me at melidis att l3s.uni-hannover.de.
Industry
- Research Assistant (Internship) position in the bioinformatics team of Molecular Diagnostics, Genomics and Bioinformatics, supervised by Dr. Christian Ahrens (2014-2015).
- Bioinformatics Scientist position in the research sub-team of bioinformatics department of Platomics GmbH. Main projects: HLA/ABO Typing, ACMG Classification, CNV Calling, Assay Development (Jan. 2022-Present).
Education
- Diploma (5-year studies) in Computer Science at Computer Engineering and Informatics Department,University of Patras (2006-2011).
- Master of Science in Computational Biology and Bioinformatics at Swiss Federal Institute of Technology Zurich - University of Zurich (2012-2014).
- Scientific assistant and PhD candidate in computer science at Gottfried Wilhelm Leibniz University, supervised by Prof. Dr. Wolfgang Nejdl (2017- March of 2023).
Selected research
- Doctorate thesis:
- Classifying distinct data types: textual streams, protein sequences and genomic variants, Damianos P. Melidis, Gottfried Wilhelm Leibniz University, 2023.
- Thesis defense (without appendix), Damianos P. Melidis, Gottfried Wilhelm Leibniz University, 22.03.2023.
- Pattern recognition:
- Unlocking the Black Box of Support Vector Machine based on Classification in Biological Datasets, D. Melidis, K. Theofilatos, A. Tsakalidis, S. Likothanassis, S. Papadimitriou and S. Mavroudi, HSCBB-2011.
- A Hybrid Support Vector Fuzzy Inference System for the Classification of Leakage Current Waveforms Portraying Discharges, K. Theofilatos, D. Pylarinos, S. Likothanassis and D. Melidis, K. Siderakis, E. Thalassinakis, S. Mavroudi Electric Power Components and Systems, 42:2, 180-189.
- Bioinformatics:
- Reference-guided de novo assembly: improved genome of a non-model plant species, H. E.L. Lischer, D. Melidis, M. Hatakeyama and K. Shimizu, European Society for Evolutionary Biology, 2015 (Poster).
- Comparative genomics of completely sequenced Lactobacillus helveticus genomes provides insights into strain-specific genes and resolves metagenomics data down to the strain level, M. Schmid, J. Muri, D. Melidis, A. R. Varadarajan, V. Somerville, A. Wicki, A. Moser, M. Bourqui, C. Wenzel, E. Eugster-Meier, J. E. Frey, S. Irmler, C. H. Ahrens, Front. Microbiol., 2018.
- Capturing Protein Domain Structure and Function Using Self-Supervision on Domain Architectures, D. P. Melidis, W. Nejdl, Algorithms, 2021.
- ViruSurf: an integrated database to investigate viral sequences, A. Canakoglu, P. Pinoli, A. Bernasconi, T. Alfonsi, D. P. Melidis, S. Ceri, NAR, 2020.
- GenOtoScope: Towards automating ACMG classification of variants associated with congenital hearing loss, D. P. Melidis *, C. Landgraf *, G. Schmidt, A. Schöner-Heinisch, S. von Hardenberg, A. Lesinski-Schiedat, W. Nejdl , B. Auber (*: equal 1st author contribution), PLoS Comput Biol, 2022.
- Data stream mining:
- Learning under feature drifts in textual streams, D. P. Melidis, M. Spiliopoulou, E. Ntoutsi, CIKM 2018, Turin Italy.
About
I was born and raised in sunny Athens, Greece. Through these years, I have also lived in Switzerland, Germany and Austria where I got to know good friends! \o/
Some nice pieces of literature: