A survey of k-mer methods and applications in bioinformatics

Camille Moeckel, Manvita Mareboina, Maxwell A. Konnaris, Candace S.Y. Chan, Ioannis Mouratidis, Austin Montgomery, Nikol Chantzi, Georgios A. Pavlopoulos, Ilias Georgakopoulos-Soares

Research output: Contribution to journalReview articlepeer-review

23 Scopus citations

Abstract

The rapid progression of genomics and proteomics has been driven by the advent of advanced sequencing technologies, large, diverse, and readily available omics datasets, and the evolution of computational data processing capabilities. The vast amount of data generated by these advancements necessitates efficient algorithms to extract meaningful information. K-mers serve as a valuable tool when working with large sequencing datasets, offering several advantages in computational speed and memory efficiency and carrying the potential for intrinsic biological functionality. This review provides an overview of the methods, applications, and significance of k-mers in genomic and proteomic data analyses, as well as the utility of absent sequences, including nullomers and nullpeptides, in disease detection, vaccine development, therapeutics, and forensic science. Therefore, the review highlights the pivotal role of k-mers in addressing current genomic and proteomic problems and underscores their potential for future breakthroughs in research.

Original languageEnglish (US)
Pages (from-to)2289-2303
Number of pages15
JournalComputational and Structural Biotechnology Journal
Volume23
DOIs
StatePublished - Dec 2024

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'A survey of k-mer methods and applications in bioinformatics'. Together they form a unique fingerprint.

Cite this