Gustavo Nicoletti Rosa
Heuristic Algorithm for Predicting Alternatively Spliced mRNAs with Pre-Trained LLM in Cancer.
Rel. Stefano Di Carlo, Roberta Bardini, Alessandro Savino, Matteo Cereda, Lorenzo Martini. Politecnico di Torino, Master of science program in Data Science And Engineering, 2025
|
Preview |
PDF (Tesi_di_laurea)
- Thesis
Licence: Creative Commons Attribution Non-commercial No Derivatives. Download (74MB) | Preview |
Abstract
Alternative Splicing is the RNA's ability to be spliced into many different mRNA isoforms, and it is of great evolutionary importance because it allows a single gene to produce a variety of proteins. However, in cancer, the spliceosome machinery produces aberrant isoforms or changes their expression, which alters the behavior of the cell, as they interfere with biological pathways. The study of novel cancer isoforms is essential for developing therapies that can suppress their expression or exploit the new epitopes, in addition to providing a deeper understanding of the disease. The relatively new long-read sequencing technology enables a more accurate representation of the transcriptome than the older short-read.
Still, not all isoforms have been sequenced, and each cell in each state will produce different outcomes
Relators
Academic year
Publication type
Number of Pages
Course of studies
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modify record (reserved for operators) |
