SAliBASE: A Database of Simulated Protein Alignments

Pervez, Muhammad Tariq; Shah, Hayat Ali; Babar, Masroor Ellahi; Naveed, Nasir; Shoaib, Muhammad

doi:10.1177/1176934318821080

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…A considerable number of statistical models and methods have been developed and tested for inferring the evolutionary relationship of nucleotide and protein sequences. [16][17][18] The established models are effective in simulating evolution of real sequences, 19,20 in establishing databases of simulated protein alignments, 21 and in exploring early events in the ecological differentiation of bacterial genomes. 22 However, these methods were mostly developed for simulation of gene or protein sequences which possess high conservatism.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Chordate Intron Evolution Using Randomly Generated and Mutated Base Sequences

Wang

Zeng

et al. 2020

Evol Bioinform Online

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Introns are well known for their high variation not only in length but also in base sequence. The evolution of intron sequences has aroused broad interest in the past decades. However, very little is known about the evolutionary pattern of introns due to the lack of efficient analytical method. In this study, we designed 2 evolutionary models, that is, mutation-and-deletion (MD) and mutation-and-insertion (MI), to simulate intron evolution using randomly generated and mutated bases by referencing to the phylogenetic tree constructed using 14 chordate introns from TF4 (transcription factor–like protein 4) gene. A comparison of attributes between model-generated sequences and chordate introns showed that the MD model with proper parameter settings could generate sequences that have attributes matchable to chordate introns, whereas the MI model with any parameter settings failed in doing so. These data suggest that the surveyed chordate introns have evolved from a long ancestral sequence through gradual reduction in length. The established methodology provides an effective measure to study the evolutionary pattern of intron sequences from organisms of various taxonomic groups. (C++ scripts of MD and MI models are available upon request.)

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Section: Introductionmentioning

confidence: 99%

Simulation of Chordate Intron Evolution Using Randomly Generated and Mutated Base Sequences

Wang

Zeng

et al. 2020

Evol Bioinform Online

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“…Many databases have proliferated in recent days. The most common databases of protein which include large amount of protein sequences are Swiss-Prot, HOMFAM [20], SAliBASE [21,22], PIR, Pfam [23], and BAliBASE [24,25]. There is another database for DNA and RNA sequences such as GenBank, HOMSTRAD, PDB, and RefSeq [2].…”

Section: Widespread Datasets Of Proteinmentioning

confidence: 99%

“…Each dataset part in SAliBASE contains the corresponding alignment that is considered as a standard to evaluate MSA approaches. There are five parameters that control the database generation such as the sequence number, the rate of insertion, the rate of deletion, the length of the sequence, and indel size as in [21].…”

Section: Widespread Datasets Of Proteinmentioning

confidence: 99%

Artificial Fish Swarm for Multi Protein Sequences Alignment in Bioinformatics

Tawfeek¹,

Alanazi²,

El-Aziz³

2022

Computers, Materials &Amp; Continua

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The alignment operation between many protein sequences or DNA sequences related to the scientific bioinformatics application is very complex. There is a trade-off in the objectives in the existing techniques of Multiple Sequence Alignment (MSA). The techniques that concern with speed ignore accuracy, whereas techniques that concern with accuracy ignore speed. The term alignment means to get the similarity in different sequences with high accuracy. The more growing number of sequences leads to a very complex and complicated problem. Because of the emergence; rapid development; and dependence on gene sequencing, sequence alignment has become important in every biological relationship analysis process. Calculating the number of similar amino acids is the primary method for proving that there is a relationship between two sequences. The time is a main issue in any alignment technique. In this paper, a more effective MSA method for handling the massive multiple protein sequences alignment maintaining the highest accuracy with less time consumption is proposed. The proposed method depends on Artificial Fish Swarm (AFS) algorithm that can break down the most challenges of MSA problems. The AFS is exploited to obtain high accuracy in adequate time. ASF has been increasing popularly in various applications such as artificial intelligence, computer vision, machine learning, and dataintensive application. It basically mimics the behavior of fish trying to get the food in nature. The proposed mechanisms of AFS that is like preying, swarming, following, moving, and leaping help in increasing the accuracy and concerning the speed by decreasing execution time. The sense organs that aid the artificial fishes to collect information and vision from the environment help in concerning the accuracy. These features of the proposed AFS make the alignment operation more efficient and are suitable especially for large-scale data. The implementation and experimental results put the proposed AFS as a first choice in the queue of alignment compared to the well-known algorithms in multiple sequence alignment.

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“…Simulated sequence evolution datasets have also been used to evaluate MSA tools ( 36–39 ), providing the means to produce larger test sets, a wide range of sequence divergence characteristics, and supporting the generation of DNA-specific benchmarks. However, these previous studies focused on constrained sequences ( 36 ), protein simulations ( 37 , 38 ), or ignored the problem of working with fragmented sequences ( 36–39 ).…”

Section: Introductionmentioning

confidence: 99%

Accuracy of multiple sequence alignment methods in the reconstruction of transposable element families

Hubley

Wheeler

Smit

2022

NAR Genomics and Bioinformatics

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The construction of a high-quality multiple sequence alignment (MSA) from copies of a transposable element (TE) is a critical step in the characterization of a new TE family. Most studies of MSA accuracy have been conducted on protein or RNA sequence families, where structural features and strong signals of selection may assist with alignment. Less attention has been given to the quality of sequence alignments involving neutrally evolving DNA sequences such as those resulting from TE replication. Transposable element sequences are challenging to align due to their wide divergence ranges, fragmentation, and predominantly-neutral mutation patterns. To gain insight into the effects of these properties on MSA accuracy, we developed a simulator of TE sequence evolution, and used it to generate a benchmark with which we evaluated the MSA predictions produced by several popular aligners, along with Refiner, a method we developed in the context of our RepeatModeler software. We find that MAFFT and Refiner generally outperform other aligners for low to medium divergence simulated sequences, while Refiner is uniquely effective when tasked with aligning high-divergent and fragmented instances of a family.

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SAliBASE: A Database of Simulated Protein Alignments

Cited by 5 publications

References 11 publications

Simulation of Chordate Intron Evolution Using Randomly Generated and Mutated Base Sequences

Simulation of Chordate Intron Evolution Using Randomly Generated and Mutated Base Sequences

Artificial Fish Swarm for Multi Protein Sequences Alignment in Bioinformatics

Accuracy of multiple sequence alignment methods in the reconstruction of transposable element families

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