MSc Thesis Presentation by Asimenia Giagli
MSc Thesis Presentation by Asimenia Giagli titled: “A Reproducible Pipeline for Prioritizing Antibody-Accessible Cell-Surface Targets from Single-Cell Transcriptomic Data”
Abstract:
Cell-surface proteins are promising candidates for antibody-based therapies, but their prioritization from transcriptomic data requires more than differential expression alone. This thesis developed a reproducible computational workflow to identify biologically plausible, antibody-accessible surface proteins from single-cell RNA-sequencing data. The workflow was implemented as a modular Nextflow pipeline integrating single-cell preprocessing, cell-type annotation, donor-level pseudobulk differential expression, UniProt protein mapping, transmembrane-topology prediction, GTEx-based normal-tissue filtering, and external validation. It was evaluated using a human cutaneous squamous cell carcinoma dataset containing tumour and matched normal skin samples. Differential expression was performed within annotated cell populations to retain cellular context. Tumour-upregulated genes were mapped to human membrane proteins, filtered for predicted single-pass Type I or Type II topology with sufficient extracellular domains, and screened for low expression in selected vital tissues using GTEx. This progressively reduced the candidate space to a smaller set of cell-type-specific proteins. Validation included comparison with antibody-related IEDB antigens, therapeutic-target annotations, and extracellular-domain BepiPred predictions. The final candidates represent computational priorities rather than validated therapeutic targets and require experimental confirmation of protein expression, surface localization, antibody binding, functional relevance, and normal-tissue safety. Overall, the framework provides a transparent approach for narrowing transcriptomic data toward experimentally testable cell-surface therapeutic candidates.
Date/Time: 16/10/2026 – 13:30 PM
Examination Committee:
Theodore Dalamagas, Research Director, ATHENA Research Center
Dimitrios Stravopodis, Associate Professor, Department of Biology, National and Kapodistrian University of Athens
Eleni Christodoulou, Scientific Associate, ATHENA Research Center
Teams link: https://teams.microsoft.com/meet/362275300616504?p=SX5AkcQxcBxmfu4aOl
UPDATED – PROGRAM FALL SEMESTER 2026-27
Lessons begin on Monday, 5 October (The Python bootcamp will be held the previous week (28/9 – 2/10)
MSc thesis presentation of Vasiliki Koumarela, October 5
Title: “Electricity Price Forecasting with Attention-Based Neural Network Architectures”
Abstract:
In recent years, electricity markets have undergone significant changes, driven by the introduction of auction-based power trading mechanisms, ambitious greenhouse-gas emis-
sion targets, and the increasing penetration of Renewable Energy Sources (RES), which together make electricity price forecasting a highly volatile, multifactorial problem. These developments have heightened the importance of quantifying forecast uncertainty and have motivated growing interest in probabilistic forecasting, particularly with deep learning models. This thesis contributes to probabilistic electricity price forecasting by applying and evaluating modern attention-based architectures, namely the Transformer, the Temporal Fusion Transformer (TFT), PatchTST, and the foundation model Chronos-2, adapted to produce quantile forecasts. The models are first evaluated on the GEFCom2014 dataset under the same experimental setting as the original competition, on which, to the best of our knowledge, such deep learning architectures have not previously been applied; their results are compared against both classical statistical and neural benchmarks, as well as the competition-winning solutions. To assess robustness under more realistic and demanding conditions the same framework is then applied to recent Greek electricity market data, which exhibit high volatility, missing values, and negative prices. The forecasting task is to predict the next 24 hours from a historical observation window together with available exogenous features, with performance evaluated using the pinball loss alongside reliability and sharpness metrics. The results show that the proposed models consistently outperform the classical benchmarks on GEFCom2014, in some cases matching or exceeding the competition-winning solutions. On the more complex Greek data the models remain effective, though with some degradation attributable to the increased difficulty of the series, indicating room for further improvement. Overall, Chronos-2 achieves the strongest performance, followed closely by the Transformer.
Date-Time: 5/10/2026 – 16:00 PM
Examination Committee:
Associate Professor Aggelos Pikrakis, University of Piraeus
Dr. Vassilis Katsouros, Director, ILSP/Athena Research Center
Dr. Kosmas Kritsis, ILSP/Athena Research Center
Msc Thesis Presentation
Monday, October 5 · 16:00pm – 17:00pm
Time zone: Europe/Athens
Webex joining info
Video call link: https://unipi.webex.com/meet/webex-host2
Invitation to the Workshop “From Systems to Trust: Data Management in the AI Era” | 15 September 2026
The European project DataGEMS and DareLab of the Athena Research Center cordially invite you to the workshop:
From Systems to Trust: Data Management in the AI Era
The workshop is dedicated to current trends and challenges in data management in the era of Artificial Intelligence. It will take place on Tuesday, September 15, 2026, from 10:00 AM to 3:30 PM, at the History Museum of the University of Athens.
The program is divided into two parts:
Part A: Research Presentations | 10:00 AM – 1:40 PM | in English
Eight presentations, organized into four thematic sessions, explore how Artificial Intelligence transforms data systems, enables natural language interaction, supports data search and linking, and highlights critical trustworthiness issues.
Part B: Open Panel Discussion | 2:30 PM – 3:30 PM | in Greek
“Artificial Intelligence at the Service of Society”
Who benefits, who takes the risk, and what does an open research infrastructure owe to the public that funds it? The panel is addressed to a broader audience and does not require having attended the first part.
Participation is free, but registration is required. The event will be held exclusively in person. You may choose to attend the first part, the second part, or both.
Registration: ai-dialogues.athenarc.gr
Πρόσκληση στην ημερίδα «From Systems to Trust: Data Management in the AI Era» | 15 Σεπτεμβρίου 2026
Το ευρωπαϊκό έργο DataGEMS και το DareLab του Ερευνητικού Κέντρου Αθηνά σας προσκαλούν στην ημερίδα:
From Systems to Trust: Data Management in the AI Era
Η ημερίδα είναι αφιερωμένη στις σύγχρονες τάσεις και προκλήσεις της διαχείρισης δεδομένων στην εποχή της Τεχνητής Νοημοσύνης και θα πραγματοποιηθεί την Τρίτη 15 Σεπτεμβρίου 2026, από τις 10:00 πμ έως τις 15:30 μμ, στο Μουσείο Ιστορίας του Πανεπιστημίου Αθηνών.
Το πρόγραμμα χωρίζεται σε δύο μέρη:
Μέρος Α΄: Ερευνητικές παρουσιάσεις | 10:00 πμ –13:40 μμ | στα αγγλικά
Οκτώ παρουσιάσεις, οργανωμένες σε τέσσερις θεματικές ενότητες, εξετάζουν πώς η Τεχνητή Νοημοσύνη μετασχηματίζει τα συστήματα δεδομένων, επιτρέπει την αλληλεπίδραση μέσω φυσικής γλώσσας, υποστηρίζει την αναζήτηση και σύνδεση δεδομένων και αναδεικνύει κρίσιμα ζητήματα αξιοπιστίας.
Μέρος Β΄: Ανοιχτή συζήτηση | 14:30 μμ –15:30 μμ | στα ελληνικά
«Η Τεχνητή Νοημοσύνη στην Υπηρεσία της Κοινωνίας»
Ποιος ωφελείται, ποιος αναλαμβάνει το ρίσκο και τι οφείλει μια ανοιχτή ερευνητική υποδομή στο κοινό που τη χρηματοδοτεί; Το πάνελ απευθύνεται σε ευρύτερο κοινό και δεν προϋποθέτει την παρακολούθηση του πρώτου μέρους.
Η συμμετοχή είναι δωρεάν, με απαραίτητη εγγραφή, και η εκδήλωση θα πραγματοποιηθεί αποκλειστικά με φυσική παρουσία. Μπορείτε να επιλέξετε να παρακολουθήσετε το πρώτο μέρος, το δεύτερο ή και τα δύο.
Εγγραφές: ai-dialogues.athenarc.gr
Hellenic Society for Computational Biology and Bioinformatics Conference, Kalamata, Greece
The Hellenic Society for Computational Biology and Bioinformatics (HSCBB) is pleased to announce the upcoming HSCBB26 Conference, which will take place in Kalamata, Greece, at the Municipal Cultural Center of Kalamata between 23-25 of October.
The conference will bring together researchers, academics, students, and professionals working at the interface of computational biology, bioinformatics, systems biology, artificial intelligence, and biomedical data science.
HSCBB26 will serve as a forum for presenting cutting-edge research, fostering scientific collaborations, and promoting interdisciplinary exchange across the rapidly evolving fields of computational life sciences. Participants will have the opportunity to attend keynote lectures, oral presentations, poster sessions, and networking activities covering a broad spectrum of topics related to computational and data-driven approaches in biology and medicine.
The conference aims to strengthen the Greek and international computational biology community by encouraging interaction among researchers from academia, research institutes, healthcare organizations, and industry.
We warmly invite researchers and students from relevant disciplines to participate in the conference and contribute to the advancement of computational biology and bioinformatics research.
More information, registration details, and updates are available at:
https://sites.google.com/view/hscbb26/home