A time warping approach to multiple sequence alignment
| Autor: | Catherine Matias, Ana Arribas-Gil |
|---|---|
| Přispěvatelé: | Departamento de Estadistica, Universidad Carlos III de Madrid [Madrid] (UC3M), Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Statistics and Probability FOS: Computer and information sciences Warping Dynamic time warping Computer science Context (language use) Statistics - Applications Quantitative Biology - Quantitative Methods 03 medical and health sciences Synchronization (computer science) Genetics Computer Simulation Applications (stat.AP) Image warping Molecular Biology Quantitative Methods (q-bio.QM) Alignment [STAT.AP]Statistics [stat]/Applications [stat.AP] Multiple sequence alignment Base Sequence Functional data analysis Quantitative Biology::Genomics [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] Computational Mathematics Quantitative Biology::Quantitative Methods 030104 developmental biology FOS: Biological sciences Path (graph theory) Pairwise comparison Algorithm Sequence Alignment Algorithms Software |
| Zdroj: | Statistical Applications in Genetics and Molecular Biology Statistical Applications in Genetics and Molecular Biology, 2017, 16 (2), pp.133-144. ⟨10.1515/sagmb-2016-0043⟩ Statistical Applications in Genetics and Molecular Biology, De Gruyter, 2017, 16 (2), pp.133-144. ⟨10.1515/sagmb-2016-0043⟩ |
| ISSN: | 1544-6115 |
| DOI: | 10.1515/sagmb-2016-0043⟩ |
| Popis: | We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context of functional data analysis. Starting from pairwise alignments of all the sequences (viewed as paths in a certain space), we construct a median path that represents the MSA we are looking for. We establish a proof of concept that our method could be an interesting ingredient to include into refined MSA techniques. We present a simple synthetic experiment as well as the study of a benchmark dataset, together with comparisons with 2 widely used MSA softwares. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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