This dissertation investigates innovative data mining methodologies in the biomedical field, placing special emphasis on the identification and analysis of microRNAs as potential biomarkers for various diseases, devoting specific attention to COVID-19 in the hospitalized elderly population. Through the use of Ingenuity Pathway Analysis, the research examines in detail the complex biological processes and molecular mechanisms influenced by microRNAs, exploring their regulation and potential roles in disease development and response to treatments. The present study not only enriches our understanding of the functions and control of miRNAs in the biomedical context, but also highlights how state-of-the-art bioinformatics tools can facilitate in silico research, opening new horizons for biomarker identification and elucidation of complex biological phenomena. The thesis highlights the importance of combining sophisticated data mining techniques with molecular biology to increase the predictive accuracy of potential biomarkers.
Questa tesi studia metodologie innovative di data mining in campo biomedico, ponendo particolare enfasi sull'identificazione e l'analisi dei microRNA come potenziali biomarcatori di varie malattie, dedicando un'attenzione specifica al COVID-19 nella popolazione anziana ospedalizzata. Attraverso l'uso di Ingenuity Pathway Analysis, la ricerca esamina in dettaglio i complessi processi biologici e i meccanismi molecolari influenzati dai microRNA, esplorando la loro regolazione e i potenziali ruoli nello sviluppo delle malattie e nella risposta ai trattamenti. Il presente studio non solo arricchisce la nostra comprensione delle funzioni e del controllo dei miRNA nel contesto biomedico, ma evidenzia anche come gli strumenti bioinformatici all'avanguardia possano facilitare la ricerca in silico, aprendo nuovi orizzonti per l'identificazione di biomarcatori e la delucidazione di fenomeni biologici complessi. La tesi evidenzia l'importanza di combinare sofisticate tecniche di data mining con la biologia molecolare per aumentare l'accuratezza predittiva di potenziali biomarcatori.
Data-Mining Innovative Approaches in biomedical fields / Marra, Massimo. - (2024).
Data-Mining Innovative Approaches in biomedical fields
MARRA, MASSIMO
2024-01-01
Abstract
This dissertation investigates innovative data mining methodologies in the biomedical field, placing special emphasis on the identification and analysis of microRNAs as potential biomarkers for various diseases, devoting specific attention to COVID-19 in the hospitalized elderly population. Through the use of Ingenuity Pathway Analysis, the research examines in detail the complex biological processes and molecular mechanisms influenced by microRNAs, exploring their regulation and potential roles in disease development and response to treatments. The present study not only enriches our understanding of the functions and control of miRNAs in the biomedical context, but also highlights how state-of-the-art bioinformatics tools can facilitate in silico research, opening new horizons for biomarker identification and elucidation of complex biological phenomena. The thesis highlights the importance of combining sophisticated data mining techniques with molecular biology to increase the predictive accuracy of potential biomarkers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.