Abstract
Bioinformatics plays a critical role in the advancement of peptidomics by providing powerful tools for data analysis, interpretation and integration. Peptidomics is concerned with the study of peptides, short chains of amino acids with diverse biological functions. This area includes peptide identification and characterization, database construction, de novo sequencing, functional annotation, omics data integration and systems biology. Artificial intelligence techniques, such as machine learning and natural language processing, aid in the interpretation of peptide sequence data and the generation of biological insights. By using bioinformatics approaches, peptidomics researchers can accelerate peptide discovery, understand their functions and gain insights into complex molecular interactions.
Financial disclosure
The authors thank the Portuguese Foundation for Science and Technology (FCT), European Union, QREN, FEDER and COMPETE for funding Unidade de Investigação Cardiovascular (UIDB/00051/2020 and UIDP/00051/2020), iBiMED (UID/04501/2020, POCI-01-0145-FEDER-007628) and LAQV/REQUIMTE (UIDB/50006/2020) research units.
Competing interests disclosure
The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Writing disclosure
No writing assistance was utilized in the production of this manuscript.