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Identifier |
000452749 |
Title |
Prediction and assessment of fusion proteins |
Author
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Μπαλτσαβιά, Ισμήνη
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Thesis advisor
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Ηλιόπουλος, Ιωάννης
Τοπάλης, Παντελής
Προμπονάς, Βασίλης
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Abstract |
Protein protein interactions support and orchestrate biological processes, thus playing a
crucial role in biological systems maintenance. Deviations from the proper functioning can impact
the homeostasis of an organism in different ways. Prediction of protein protein interactions through
experimental methods have proven to be a powerful strategy in a small scale, yet characterized by
lack in precision due to the presence of a high rate of false positive results deriving from the
experimental design. In the big data era where whole genome sequencing data are to be analyzed
such strategies become time and money-consuming. Computational methods can overcome these
challenges. Prediction of protein protein interactions can emerge from genome and protein
sequences. The presence of fusion proteins is a phenomenon which can ascertain that two or more
proteins interact. In this case the separate proteins from one organism are found as one fused
protein in another organism. These fusion events suggest the functional relationship between the
component proteins of a fused protein, thus supporting their interaction. The scope of this study is
to explore the potential to discover protein protein interactions in prokaryotic and eukaryotic
genomes, utilizing two algorithms (DifFuse and CompositeSearch) that detect fusion proteins from
sequence similarity searches. In addition, Information regarding the amino acid composition of the
region between the component proteins in the fused protein, called linker, are reported. Linkers
could serve as a tool for the prediction of fused proteins and thus protein protein interactions,
locating protein regions with a certain amino acid composition, akin to the composition of linker
regions.
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Language |
English |
Subject |
Linkers |
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Protein sequence similarity |
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Ομοιότητα πρωτεϊνών |
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Πρωτεϊνικές αλληλεπιδράσεις |
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Συνθέτες |
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Συντηγμένες πρωτεϊνες |
Issue date |
2022-12-07 |
Collection
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School/Department--School of Medicine--Department of Medicine--Post-graduate theses
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Type of Work--Post-graduate theses
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Permanent Link |
https://elocus.lib.uoc.gr//dlib/5/e/5/metadata-dlib-1671441264-176199-23862.tkl
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Views |
332 |
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