Analysis of Bioinformatic algorithms for MSA
- Autores
- Díaz, Adrián; Minetti, Gabriela F.
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Aligning three or more biological sequences, such as DNA, RNA, or protein, is known as multiple sequence alignment (MSA). MSA is crucial in identifying important information about the sequences, including function, evolution, and structure. It serves as the first step in analyzing phylogenetic, protein, and genomic data. However, as sequence scale increases and the demand for alignment accuracy grows, MSA faces new challenges. Therefore, developing an efficient and precise tool for MSA and comparing its performance with existing ones has become a research hotspot in Bioinformatics. In this magister thesis, we propose a metaheuristic algorithm to solve MSA and a methodology to compare the performance of algorithms for aligning multiple sequences.
Red de Universidades con Carreras en Informática - Materia
-
Ciencias Informáticas
Multiple sequence alignment
Bioinformatics
Simulated Annealing
Metaheuristics - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/164877
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Analysis of Bioinformatic algorithms for MSADíaz, AdriánMinetti, Gabriela F.Ciencias InformáticasMultiple sequence alignmentBioinformaticsSimulated AnnealingMetaheuristicsAligning three or more biological sequences, such as DNA, RNA, or protein, is known as multiple sequence alignment (MSA). MSA is crucial in identifying important information about the sequences, including function, evolution, and structure. It serves as the first step in analyzing phylogenetic, protein, and genomic data. However, as sequence scale increases and the demand for alignment accuracy grows, MSA faces new challenges. Therefore, developing an efficient and precise tool for MSA and comparing its performance with existing ones has become a research hotspot in Bioinformatics. In this magister thesis, we propose a metaheuristic algorithm to solve MSA and a methodology to compare the performance of algorithms for aligning multiple sequences.Red de Universidades con Carreras en Informática2023-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf81-86http://sedici.unlp.edu.ar/handle/10915/164877enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-9285-51-0info:eu-repo/semantics/reference/url/https://sedici.unlp.edu.ar/handle/10915/163107info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:43:41Zoai:sedici.unlp.edu.ar:10915/164877Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:43:42.036SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Analysis of Bioinformatic algorithms for MSA |
| title |
Analysis of Bioinformatic algorithms for MSA |
| spellingShingle |
Analysis of Bioinformatic algorithms for MSA Díaz, Adrián Ciencias Informáticas Multiple sequence alignment Bioinformatics Simulated Annealing Metaheuristics |
| title_short |
Analysis of Bioinformatic algorithms for MSA |
| title_full |
Analysis of Bioinformatic algorithms for MSA |
| title_fullStr |
Analysis of Bioinformatic algorithms for MSA |
| title_full_unstemmed |
Analysis of Bioinformatic algorithms for MSA |
| title_sort |
Analysis of Bioinformatic algorithms for MSA |
| dc.creator.none.fl_str_mv |
Díaz, Adrián Minetti, Gabriela F. |
| author |
Díaz, Adrián |
| author_facet |
Díaz, Adrián Minetti, Gabriela F. |
| author_role |
author |
| author2 |
Minetti, Gabriela F. |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Multiple sequence alignment Bioinformatics Simulated Annealing Metaheuristics |
| topic |
Ciencias Informáticas Multiple sequence alignment Bioinformatics Simulated Annealing Metaheuristics |
| dc.description.none.fl_txt_mv |
Aligning three or more biological sequences, such as DNA, RNA, or protein, is known as multiple sequence alignment (MSA). MSA is crucial in identifying important information about the sequences, including function, evolution, and structure. It serves as the first step in analyzing phylogenetic, protein, and genomic data. However, as sequence scale increases and the demand for alignment accuracy grows, MSA faces new challenges. Therefore, developing an efficient and precise tool for MSA and comparing its performance with existing ones has become a research hotspot in Bioinformatics. In this magister thesis, we propose a metaheuristic algorithm to solve MSA and a methodology to compare the performance of algorithms for aligning multiple sequences. Red de Universidades con Carreras en Informática |
| description |
Aligning three or more biological sequences, such as DNA, RNA, or protein, is known as multiple sequence alignment (MSA). MSA is crucial in identifying important information about the sequences, including function, evolution, and structure. It serves as the first step in analyzing phylogenetic, protein, and genomic data. However, as sequence scale increases and the demand for alignment accuracy grows, MSA faces new challenges. Therefore, developing an efficient and precise tool for MSA and comparing its performance with existing ones has become a research hotspot in Bioinformatics. In this magister thesis, we propose a metaheuristic algorithm to solve MSA and a methodology to compare the performance of algorithms for aligning multiple sequences. |
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2023 |
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2023-10 |
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