SpliVert: A Protein Multiple Sequence Alignment Refinement Method Based on Splitting-Splicing Vertically

Developments in Algorithms for Sequence Alignment: A Review

The continuous development of sequencing technologies has enabled researchers to obtain large amounts of biological sequence data, and this has resulted in increasing demands for software that can perform sequence alignment fast and accurately. A number of algorithms and tools for sequence alignment have been designed to meet the various needs of biologists. Here, the ideas that prevail in the research of sequence alignment and some quality estimation methods for multiple sequence alignment tools are summarized.

A survey on the algorithm and development of multiple sequence alignment

Multiple sequence alignment (MSA) is an essential cornerstone in bioinformatics, which can reveal the potential information in biological sequences, such as function, evolution and structure. MSA is widely used in many bioinformatics scenarios, such as phylogenetic analysis, protein analysis and genomic analysis. However, MSA faces new challenges with the gradual increase in sequence scale and the increasing demand for alignment accuracy. Therefore, developing an efficient and accurate strategy for MSA has become one of the research hotspots in bioinformatics. In this work, we mainly summarize the algorithms for MSA and its applications in bioinformatics. To provide a structured and clear perspective, we systematically introduce MSA's knowledge, including background, database, metric and benchmark. Besides, we list the most common applications of MSA in the field of bioinformatics, including database searching, phylogenetic analysis, genomic analysis, metagenomic analysis and protein analysis. Furthermore, we categorize and analyze classical and state-of-the-art algorithms, divided into progressive alignment, iterative algorithm, heuristics, machine learning and divide-and-conquer. Moreover, we also discuss the challenges and opportunities of MSA in bioinformatics. Our work provides a comprehensive survey of MSA applications and their relevant algorithms. It could bring valuable insights for researchers to contribute their knowledge to MSA and relevant studies.

Metaheuristics for multiple sequence alignment: A systematic review

The Multiple Sequence Alignment (MSA) is a key task in bioinformatics, because it is used in different important biological analysis, such as function and structure prediction of unknown proteins. There are several approaches to perform MSA and the use of metaheuristics stands out because of the search ability of these methods, which generally leads to good results in a reasonable amount of time. This paper presents a Systematic Literature Review (SLR) on metaheuristics for MSA, compiling relevant works published between 2014 and 2019. The results of our SLR show the constant interest in this subject, due to the several recent publications that use different metaheuristics to obtain more accurate alignments. Moreover, the final results of our SLR show a multi-objective and hybrid approaches trends, which generally leads these methods to achieve even better results. Thus, we show in this work how the use of metaheuristics to perform MSA still remains an important and promising open research field.

Efficient Multiple Sequences Alignment Algorithm Generation via Components Assembly Under PAR Framework

As a key algorithm in bioinformatics, sequence alignment algorithm is widely used in sequence similarity analysis and genome sequence database search. Existing research focuses mainly on the specific steps of the algorithm or is for specific problems, lack of high-level abstract domain algorithm framework. Multiple sequence alignment algorithms are more complex, redundant, and difficult to understand, and it is not easy for users to select the appropriate algorithm; some computing errors may occur. Based on our constructed pairwise sequence alignment algorithm component library and the convenient software platform PAR, a few expansion domain components are developed for multiple sequence alignment application domain, and specific multiple sequence alignment algorithm can be designed, and its corresponding program, i.e., C++/Java/Python program, can be generated efficiently and thus enables the improvement of the development efficiency of complex algorithms, as well as accuracy of sequence alignment calculation. A star alignment algorithm is designed and generated to demonstrate the development process.

Research on Components Assembly Platform of Biological Sequences Alignment Algorithm

After years of development, the complexity of the biological sequence alignment algorithm is gradually increasing, and the lack of high abstract level domain research leads to the complexity of its algorithm development and improvement. By applying the idea of software components to the design and development of algorithms, the development efficiency and reliability of biological sequence alignment algorithms can be effectively improved. The component assembly platform applies related assembly technology, which simplifies the operation difficulty of component assembly and facilitates the maintenance and optimization of the algorithm. At the same time, a friendly visual interface is used to intuitively complete the assembly of algorithm components, and an executable sequence alignment algorithm program is obtained, which can directly carry out alignment computing.