Εξειδίκευση τύπου :	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	Challenges in identifying large germline structural variants for clinical use by long read sequencing: Mini review
Δημιουργός/Συγγραφέας:	Jenko Bizjan, Barbara [EL] Κατσίλα, Θεοδώρα[EN] Katsila, Theodora Tesovnik, Tine Šket, Robert Debeljak, Maruša Matsoukas, Minos Timotheos Kovač, Jernej
Εκδότης:	Elsevier
Ημερομηνία:	2020
Γλώσσα:	Αγγλικά
ISSN:	2001-0370
DOI:	10.1016/j.csbj.2019.11.008
Άλλο:	32099591
Περίληψη:	Genomic structural variations, previously considered rare events, are widely recognized as a major source of inter-individual variability and hence, a major hurdle in optimum patient stratification and disease management. Herein, we focus on large complex germline structural variations and present challenges towards target treatment via the synergy of state-of-the-art approaches and information technology tools. A complex structural variation detection remains challenging, as there is no gold standard for identifying such genomic variations with long reads, especially when the chromosomal rearrangement in question is a few Mb in length. A clinical case with a large complex chromosomal rearrangement serves as a paradigm. We feel that functional validation and data interpretation are of outmost importance for information growth to be translated into knowledge growth and hence, new working practices are highlighted.
Τίτλος πηγής δημοσίευσης:	Computational and structural biotechnology journal
Τόμος/Κεφάλαιο:	18
Σελίδες:	83-92
Θεματική Κατηγορία:	[EL] Γενετική[EN] Genetics [EL] Ιατρική[EN] Medicine [EL] Βιοτεχνολογία[EN] Biotechnology [EL] Βιοπληροφορική[EN] Bioinformatics [EL] Δομική Βιολογία[EN] Structural Biology
Λέξεις-Κλειδιά:	Human genetics Long reads sequencing Structural variations Theranostics
Κάτοχος πνευματικών δικαιωμάτων:	© 2019 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
Ηλεκτρονική διεύθυνση στον εκδότη (link):	https://www.sciencedirect.com/science/article/pii/S2001037019303678?via%3Dihub
Ηλεκτρονική διεύθυνση περιοδικού (link) :	https://www.sciencedirect.com/journal/computational-and-structural-biotechnology-journal
Εμφανίζεται στις συλλογές:	Ινστιτούτο Χημικής Βιολογίας - Επιστημονικό έργο