MASH: an interactive program for multiple alignment and consensus sequence construction for biological sequences

1991 ◽  
Vol 7 (2) ◽  
pp. 195-202
Author(s):  
C. Chappey ◽  
A. Danckaert ◽  
P. Dessen ◽  
S. Hazout
Keyword(s):  
Consensus Sequence ◽  
Multiple Alignment ◽  
Interactive Program ◽  
Biological Sequences

scholarly journals Hardness Results on Local Multiple Alignment of Biological Sequences

2007 ◽  
Vol 3 ◽  
pp. 174-182 ◽  
Author(s):  
Tatsuya Akutsu ◽  
Hiroki Arimura ◽  
Shinichi Shimozono
Keyword(s):  
Multiple Alignment ◽  
Biological Sequences

scholarly journals PURC v2.0: a program for improved sequence inference for polyploid phylogenetics and other manifestations of the multiple-copy problem

2021 ◽  
Author(s):  
Peter W Schafran ◽  
Fay-Wei W Li ◽  
Carl Rothfels
Keyword(s):  
Traditional Approach ◽  
Consensus Sequence ◽  
Operational Taxonomic Unit ◽  
Phylogenetic Inference ◽  
Biological Sequences ◽  
Multiple Copy ◽  
Sequencing Data ◽  
Sequencing Errors ◽  
Manual Curation ◽  
Similarity Thresholds

Inferring the true biological sequences from amplicon mixtures remains a difficult bioinformatic problem. The traditional approach is to cluster sequencing reads by similarity thresholds and treat the consensus sequence of each cluster as an "operational taxonomic unit" (OTU). Recently, this approach has been improved upon by model-based methods that correct PCR and sequencing errors in order to infer "amplicon sequence variants" (ASVs). To date, ASV approaches have been used primarily in metagenomics, but they are also useful for identifying allelic or paralogous variants and for determining homeologs in polyploid organisms. To facilitate the usage of ASV methods among polyploidy researchers, we incorporated ASV inference alongside OTU clustering in PURC v2.0, a major update to PURC (Pipeline for Untangling Reticulate Complexes). In addition to preserving original PURC functions, PURC v2.0 allows users to process PacBio CCS/HiFi reads through DADA2 to generate and annotate ASVs for multiplexed data, with outputs including separate alignments for each locus ready for phylogenetic inference. In addition, PURC v2.0 features faster demultiplexing than the original version and has been updated to be compatible with Python 3. In this chapter we present results indicating that PURC v2.0 (using the ASV approach) is more likely to infer the correct biological sequences in comparison to the earlier OTU-based PURC, and describe how to prepare sequencing data, run PURC v2.0 under several different modes, and interpret the output. We expect that PURC v2.0 will provide biologists with a method for generating multi-locus "moderate data" datasets that are large enough to be phylogenetically informative and small enough for manual curation.

lamassemble: Multiple Alignment and Consensus Sequence of Long Reads

2020 ◽  
pp. 135-145
Author(s):  
Martin C. Frith ◽  
Satomi Mitsuhashi ◽  
Kazutaka Katoh
Keyword(s):  
Consensus Sequence ◽  
Multiple Alignment ◽  
Long Reads

Fast and Sound Two-Step Algorithms for Multiple Alignment of Nucleic Sequences

1997 ◽  
Vol 06 (02) ◽  
pp. 179-192 ◽  
Author(s):  
Said Abdeddaim
Keyword(s):  
High Efficiency ◽  
Multiple Alignment ◽  
Efficient Algorithms ◽  
Biological Sequences

We report here on our work on multiple alignment of biological sequences. The observation of actual alignments has lead us to formulate heuristics from which we have derived new and efficient algorithms. These two algorithms are very fast and give reasonably good results. They work in two steps: blocks are found in the sequences, and then the sequences are aligned between the blocks. Strong and sound hypotheses made at every step, as well as a new representation of blocks, yield high efficiency of the resulting algorithms.

A Heuristic Method Based on Multi-Objective Optimization Concept for Solving RNA Multiple Alignment

2017 ◽  
Vol 10 (5) ◽  
pp. 371
Author(s):  
Arakil Chentoufi ◽  
Abdelhakim El Fatmi ◽  
Molay Ali Bekri ◽  
Said Benhlima ◽  
Mohamed Sabbane
Keyword(s):  
Heuristic Method ◽  
Multiple Alignment ◽  
Multi Objective Optimization ◽  
Multi Objective

Tejo 1– An Interactive Program for the Division of Estuaries into Homogeneous Areas

1987 ◽  
Vol 19 (9) ◽  
pp. 43-51 ◽  
Author(s):  
A. S. Câmara ◽  
M. Cardoso da Silva ◽  
L. Ramos ◽  
J. Gomes Ferreira
Keyword(s):  
Water Quality ◽  
Computer Program ◽  
Heuristic Algorithm ◽  
Management Model ◽  
Interactive Program ◽  
Basin Management ◽  
Interactive Computer Program ◽  
Lake Basins

The division of an estuary into homogeneous areas from both hydrodynamic and ecological standpoints is essential to any estuarine basin management model. This paper presents an approach based on a heuristic algorithm to achieve such a division. The methodology implemented through an interactive computer program named Tejo 1 applies morphological, water quality and management criteria in order to achieve the disaggregation. The approach is equally applicable to river or lake basins, with only minor adaptations. An application of Tejo 1 to the Tejo estuary is included for illustrative purposes, which resulted in the final division of the estuary into 11 homogeneous areas.

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