Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-3883
Title: Statistical approaches to detecting and analyzing tandem repeats in genomic sequences
Authors : Anisimova, Maria
Pečerska, Jūlija
Schaper, Elke
Published in : Frontiers in Bioengineering and Biotechnology
Volume(Issue) : 3
Issue : 31
Publisher / Ed. Institution : Frontiers Research Foundation
Issue Date: 2015
License (according to publishing contract) : CC BY 4.0: Namensnennung 4.0 International
Type of review: Peer review (Publication)
Language : English
Subjects : Molecular evolution; Protein domain; Sequence profile model; Tandem repeat annotation; Tandem repeat
Subject (DDC) : 004: Computer science
572: Biochemistry
Abstract: Tandem repeats (TRs) are frequently observed in genomes across all domains of life. Evidence suggests that some TRs are crucial for proteins with fundamental biological functions and can be associated with virulence, resistance, and infectious/neurodegenerative diseases. Genome-scale systematic studies of TRs have the potential to unveil core mechanisms governing TR evolution and TR roles in shaping genomes. However, TR-related studies are often non-trivial due to heterogeneous and sometimes fast evolving TR regions. In this review, we discuss these intricacies and their consequences. We present our recent contributions to computational and statistical approaches for TR significance testing, sequence profile-based TR annotation, TR-aware sequence alignment, phylogenetic analyses of TR unit number and order, and TR benchmarks. Importantly, all these methods explicitly rely on the evolutionary definition of a tandem repeat as a sequence of adjacent repeat units stemming from a common ancestor. The discussed work has a focus on protein TRs, yet is generally applicable to nucleic acid TRs, sharing similar features.
Departement: Life Sciences und Facility Management
Organisational Unit: Institute of Applied Simulation (IAS)
Publication type: Article in scientific Journal
DOI : 10.3389/fbioe.2015.00031
10.21256/zhaw-3883
ISSN: 2296-4185
URI: https://digitalcollection.zhaw.ch/handle/11475/8262
Appears in Collections:Publikationen Life Sciences und Facility Management

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