A Categorization of Relevant Sequence Alignment Algorithms with Respect to Data Structures

Sequence Alignment is an active research subfield of bioinformatics. Today, sequence databases are rapidly and steadily increasing. Thus, to overcome this issue, many efficient algorithms have been developed depending on various data structures. The latter have demonstrated considerable efficacy in terms of run-time and memory consumption. In this paper, we briefly outline existing methods applied to the sequence alignment problem. Then we present a qualitative categorization of some remarkable algorithms based on their data structures. Specifically, we focus on research works published in the last two decades (i.e. the period from 2000 to 2020). We describe the employed data structures and expose some important algorithms using each. Then we show potential strengths and weaknesses among all these structures. This will guide biologists to decide which program is best suited for a given purpose, and it also intends to highlight weak points that deserve attention of bioinformaticians in future research.

@article{Haji2020,
  title     = {A Categorization of Relevant Sequence Alignment Algorithms with Respect to Data Structures},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {6},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Hasna El Haji and Larbi Alaoui},
  doi       = {10.14569/IJACSA.2020.0110635},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110635}
}