Εφαρμογές μηχανικής μάθησης στην γονιδιωματική
Applications of machine learning in genomics
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Keywords
Machine learning ; Genomics ; Γονιδιωματική ; Μηχανική μάθηση ; Endometrial cancerAbstract
In the rapidly evolving field of genomics, the rate at which data are growing has reached unprecedented speeds, marking a new era for computational biology. This explosive increase in genomic data, fueled by advances in DNA sequencing technologies, offers vast possibilities for understanding the complexity of life from uncovering the genetic causes of various diseases to the application of personalized treatments. However, the massive influx of these data brings to the surface major challenges in terms of storage, analysis and interpretation, requiring innovative solutions that leverage the latest developments in machine learning and data science. This thesis explores the critical role of applying machine learning techniques in the field of genomics by addressing the complexities and volume of data that traditional analysis cannot efficiently process. Through a comprehensive study of various elements and concepts associated with genomics and machine learning, as well as through the examination of applications found in the literature and the development of a customized application on real genomic data, this thesis aims to contribute to the formation of a comprehensive picture of the importance of machine learning in the exploration and exploitation of genomic data, paving the way for further scientific discoveries.
Postgraduate Studies Programme
Εφαρμοσμένη ΣτατιστικήDepartment
Σχολή Χρηματοοικονομικής και Στατιστικής. Τμήμα Στατιστικής και Ασφαλιστικής ΕπιστήμηςNumber of pages
153Language
GreekCollections
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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα