Abstract by Kristi Bresciano
Motif Discovery in Antimicrobial Peptides
Antibiotic research is an area of ever increasing importance, especially with bacteria rapidly evolving to become more resistant to current antibiotics. Peptides, or small sequences of DNA, have a variety of properties, some of which being toxic to bacteria. Discovering the motifs, or patterns, in these toxic peptides would allow for the development of new antibiotics. We performed multiple analyses on randomly generated peptides and their observed effects on bacteria. We used heuristic algorithms and deep learning to search for motifs in peptides exhibiting toxic behavior and compared the results of each analysis. Although each approach had its own strengths and weaknesses, there were similar motifs between all methods.