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https://doi.org/10.21256/zhaw-3883| Publication type: | Article in scientific journal |
| Type of review: | Peer review (publication) |
| Title: | Statistical approaches to detecting and analyzing tandem repeats in genomic sequences |
| Authors: | Anisimova, Maria Pečerska, Jūlija Schaper, Elke |
| DOI: | 10.3389/fbioe.2015.00031 10.21256/zhaw-3883 |
| Published in: | Frontiers in Bioengineering and Biotechnology |
| Volume(Issue): | 3 |
| Issue: | 31 |
| Issue Date: | 2015 |
| Publisher / Ed. Institution: | Frontiers Research Foundation |
| ISSN: | 2296-4185 |
| 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. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/8262 |
| Fulltext version: | Published version |
| License (according to publishing contract): | CC BY 4.0: Attribution 4.0 International |
| Departement: | Life Sciences and Facility Management |
| Organisational Unit: | Institute of Computational Life Sciences (ICLS) |
| Appears in collections: | Publikationen Life Sciences und Facility Management |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| fbioe-03-00031.pdf | 718.84 kB | Adobe PDF |  View/Open |
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Anisimova, M., Pečerska, J., & Schaper, E. (2015). Statistical approaches to detecting and analyzing tandem repeats in genomic sequences. Frontiers in Bioengineering and Biotechnology, 3(31). https://doi.org/10.3389/fbioe.2015.00031
Anisimova, M., Pečerska, J. and Schaper, E. (2015) ‘Statistical approaches to detecting and analyzing tandem repeats in genomic sequences’, Frontiers in Bioengineering and Biotechnology, 3(31). Available at: https://doi.org/10.3389/fbioe.2015.00031.
M. Anisimova, J. Pečerska, and E. Schaper, “Statistical approaches to detecting and analyzing tandem repeats in genomic sequences,” Frontiers in Bioengineering and Biotechnology, vol. 3, no. 31, 2015, doi: 10.3389/fbioe.2015.00031.
ANISIMOVA, Maria, Jūlija PEČERSKA und Elke SCHAPER, 2015. Statistical approaches to detecting and analyzing tandem repeats in genomic sequences. Frontiers in Bioengineering and Biotechnology. 2015. Bd. 3, Nr. 31. DOI 10.3389/fbioe.2015.00031
Anisimova, Maria, Jūlija Pečerska, and Elke Schaper. 2015. “Statistical Approaches to Detecting and Analyzing Tandem Repeats in Genomic Sequences.” Frontiers in Bioengineering and Biotechnology 3 (31). https://doi.org/10.3389/fbioe.2015.00031.
Anisimova, Maria, et al. “Statistical Approaches to Detecting and Analyzing Tandem Repeats in Genomic Sequences.” Frontiers in Bioengineering and Biotechnology, vol. 3, no. 31, 2015, https://doi.org/10.3389/fbioe.2015.00031.
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