Tandem repeat proteins form a distinct class of structures of great relevance due to their connection to neurodegenerative diseases and their functions in human health. Starting from RAPHAEL, a solenoid detection tool, a new method is devised.The principal aim of this work is the upgrade of RAPHAEL to achieve a deeper level of classification of tandem repeats. RAPHAEL2.0 demonstrates to obtain good performances in detection and prediction of different classes of repeats.

Automatic classification of repeat proteins with RAPHAEL

Tiberti, Gabriele
2014/2015

Abstract

Tandem repeat proteins form a distinct class of structures of great relevance due to their connection to neurodegenerative diseases and their functions in human health. Starting from RAPHAEL, a solenoid detection tool, a new method is devised.The principal aim of this work is the upgrade of RAPHAEL to achieve a deeper level of classification of tandem repeats. RAPHAEL2.0 demonstrates to obtain good performances in detection and prediction of different classes of repeats.
2014-10-14
bioinformatica, repeat proteins, machine learning
File in questo prodotto:
File Dimensione Formato  
Gabriele_Tiberti_Tesi.pdf

accesso aperto

Dimensione 3.37 MB
Formato Adobe PDF
3.37 MB Adobe PDF Visualizza/Apri

The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/18719