1. Flexible single-cell RNAseq data analysis pipelines using MLscAN

2. Machine Learning-Assisted Unbiased miRNA Enrichment Analysis

3. Chemical text and association rule mining to facilitate the study of metabolic processes in hyperthermophilic microorganisms.

4. Benchmarking Activation Functions of Deep Neural Networks for Protein Secondary Structure Prediction Using the Stuttgart Neural Network Simulator

5. Cryogenic Electron Microscopy protein structure modelling

6. MLscAN A flexible tool for single-cell data analysis pipelines and model selection using unsupervised machine learning methods

7. Understanding the viral phylogenetic distribution and biodiversity at a protein family level.

8. Data Exploration and Retrieval for Hematological Markers Networks

9. Sentence Classification with Hierarchical Neural Networks for Rhetorical Sections Extraction

10. Recognition of Emotions from Facial Photos using Deep Neural Networks

11. Indexing N-Gram Graphs with Metric Access Methods

12. Genome wide distribution of H2Bub and its effect in transcription upon genotoxic stress induction

13. Comparison of machine learning methods for predicting disease progression in Duchenne Muscular Dystrophy

14. Using deep learning and natural language processing to predict protein-membrane interactions of peripheral membrane proteins

15. GREC: Multi-domain Speech Recognition for the Greek Language

16. Abundance and regulatory roles of tRNA-derived fragments: a computational exploration using Next- Generation Sequencing data

17. Cis-acting long non-coding RNAs regulate the global epigenomic and transcriptional profiles in Myelodysplastic Syndromes (MDS) and Acute Myeloid Leukemia (AML)

18. RMSD Estimation Algorithm (REA): A Neural Network Predicting Unnatural Structural Deviation in RNA Structures

19. Single cell analysis of immune compartments to predict cancer immunotherapy response and adverse autoimmune events

20. Leveraging the Matrix Profile for Real-Time Atrial Fibrillation Detection