Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://doi.org/10.21256/zhaw-22764| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | TRAL 2.0 : tandem repeat detection with circular profile hidden Markov models and evolutionary aligner |
| Autor/-in: | Delucchi, Matteo Näf, Paulina Bliven, Spencer Anisimova, Maria |
| et. al: | No |
| DOI: | 10.3389/fbinf.2021.691865 10.21256/zhaw-22764 |
| Erschienen in: | Frontiers in Bioinformatics |
| Band(Heft): | 1 |
| Heft: | 691865 |
| Erscheinungsdatum: | 25-Jun-2021 |
| Verlag / Hrsg. Institution: | Frontiers Research Foundation |
| ISSN: | 2673-7647 |
| Sprache: | Englisch |
| Schlagwörter: | Bioinformatics; Profile hidden markov models; Computational biology; Genome annotation; Protein sequence analysis; Tandem repeats |
| Fachgebiet (DDC): | 004: Informatik 572: Biochemie |
| Zusammenfassung: | The Tandem Repeat Annotation Library (TRAL) focuses on analyzing tandem repeat units in genomic sequences. TRAL can integrate and harmonize tandem repeat annotations from a large number of external tools, and provides a statistical model for evaluating and filtering the detected repeats. TRAL version 2.0 includes new features such as a module for identifying repeats from circular profile hidden Markov models, a new repeat alignment method based on the progressive Poisson Indel Process, an improved installation procedure and a docker container. TRAL is an open-source Python 3 library and is available, together with documentation and tutorials viavital-it.ch/software/tral. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/22764 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | Life Sciences und Facility Management |
| Organisationseinheit: | Institut für Computational Life Sciences (ICLS) |
| Publiziert im Rahmen des ZHAW-Projekts: | REFRACT – Repeat protein Function, Refinement, Annotation and Classification of Topologies Trans-omic approach to colorectal cancer: an integrative computational and clinical perspective Frequentist estimation of the evolutionary history of sequences with substitutions and indels |
| Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2021_Delucchi-etal_Tandem-repeat-detection.pdf | 2.15 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Delucchi, M., Näf, P., Bliven, S., & Anisimova, M. (2021). TRAL 2.0 : tandem repeat detection with circular profile hidden Markov models and evolutionary aligner. Frontiers in Bioinformatics, 1(691865). https://doi.org/10.3389/fbinf.2021.691865
Delucchi, M. et al. (2021) ‘TRAL 2.0 : tandem repeat detection with circular profile hidden Markov models and evolutionary aligner’, Frontiers in Bioinformatics, 1(691865). Available at: https://doi.org/10.3389/fbinf.2021.691865.
M. Delucchi, P. Näf, S. Bliven, and M. Anisimova, “TRAL 2.0 : tandem repeat detection with circular profile hidden Markov models and evolutionary aligner,” Frontiers in Bioinformatics, vol. 1, no. 691865, Jun. 2021, doi: 10.3389/fbinf.2021.691865.
DELUCCHI, Matteo, Paulina NÄF, Spencer BLIVEN und Maria ANISIMOVA, 2021. TRAL 2.0 : tandem repeat detection with circular profile hidden Markov models and evolutionary aligner. Frontiers in Bioinformatics. 25 Juni 2021. Bd. 1, Nr. 691865. DOI 10.3389/fbinf.2021.691865
Delucchi, Matteo, Paulina Näf, Spencer Bliven, and Maria Anisimova. 2021. “TRAL 2.0 : Tandem Repeat Detection with Circular Profile Hidden Markov Models and Evolutionary Aligner.” Frontiers in Bioinformatics 1 (691865). https://doi.org/10.3389/fbinf.2021.691865.
Delucchi, Matteo, et al. “TRAL 2.0 : Tandem Repeat Detection with Circular Profile Hidden Markov Models and Evolutionary Aligner.” Frontiers in Bioinformatics, vol. 1, no. 691865, June 2021, https://doi.org/10.3389/fbinf.2021.691865.
Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.