Large-scale structure-informed multiple sequence alignment of proteins with SIMSApiper

Summary SIMSApiper is a Nextflow pipeline that creates reliable, structure-informed MSAs of thousands of protein sequences faster than standard structure-based alignment methods. Structural information can be provided by the user or collected by the pipeline from online resources. Parallelization wi...

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Veröffentlicht in:Bioinformatics (Oxford, England) Jg. 40; H. 5
Hauptverfasser: Crauwels, Charlotte, Heidig, Sophie-Luise, Díaz, Adrián, Vranken, Wim F
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Oxford University Press 02.05.2024
Oxford Publishing Limited (England)
Schlagworte:
Algorithms
Alignment
Amino Acid Sequence
Applications Note
Availability
Computational Biology - methods
Conserved sequence
Databases, Protein
Information processing
Internet resources
Nucleotide sequence
Protein structure
Proteins
Proteins - chemistry
Secondary structure
Sequence Alignment - methods
Sequence Analysis, Protein - methods
Sequences
Software
ISSN:1367-4811, 1367-4803, 1367-4811
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Beschreibung
Zusammenfassung:Summary SIMSApiper is a Nextflow pipeline that creates reliable, structure-informed MSAs of thousands of protein sequences faster than standard structure-based alignment methods. Structural information can be provided by the user or collected by the pipeline from online resources. Parallelization with sequence identity-based subsets can be activated to significantly speed up the alignment process. Finally, the number of gaps in the final alignment can be reduced by leveraging the position of conserved secondary structure elements. Availability and implementation The pipeline is implemented using Nextflow, Python3, and Bash. It is publicly available on github.com/Bio2Byte/simsapiper.
Bibliographie:SourceType-Scholarly Journals-1
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Charlotte Crauwels and Sophie-Luise Heidig Equal contribution.
ISSN:1367-4811
1367-4803
1367-4811
DOI:10.1093/bioinformatics/btae276