Sequence analysis is the study of biological sequences, primarily DNA, RNA, and protein, to identify their features, compare them, and infer their structure, function, and evolutionary relationships. By examining the order of nucleotides or amino acids, researchers can locate genes and regulatory elements, detect mu…
Sequence analysis is the study of biological sequences, primarily DNA, RNA, and protein, to identify their features, compare them, and infer their structure, function, and evolutionary relationships. By examining the order of nucleotides or amino acids, researchers can locate genes and regulatory elements, detect mutations and variations, align sequences to reveal similarities and differences, and reconstruct the relationships among genes, proteins, and organisms. Sequence analysis relies heavily on computational tools and algorithms for tasks such as alignment, database searching, motif discovery, and phylogenetic reconstruction, and it is foundational to genomics, molecular biology, and evolutionary biology. Applications range from understanding the molecular basis of disease and identifying drug targets to tracking the evolution of pathogens and characterizing newly discovered genes. Within the scope of the International Journal of Structural Biology, this collection includes directly relevant work, including investigations of molecular evolutionary mechanisms in a heat-shock protein gene, analysis of insect protein domains, molecular analysis of a metabolic enzyme gene, evolutionary characterization of SARS-CoV-2 spike gene sequences, and identification of somatic mutations in signaling molecules. The page gathers peer-reviewed, open-access research relevant to nucleic acid and protein sequence analysis, molecular evolution, and the computational study of biological molecules.
12 peer-reviewed articles, ranked by relevance. Each links to its DOI.
The 12 articles above have been cited 23 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
A sample of recent works citing this journal's research on Sequence Analysis, linking to each citing work.