Antiprotozoal peptide prediction using machine learning with effective feature selection techniques.

Background: Protozoal pathogens pose a considerable threat, leading to notable mortality rates and the ongoing challenge of developing resistance to drugs. This situation underscores the urgent need for alternative therapeutic approaches. Antimicrobial peptides stand out as promising candidates for drug development.

iIL13Pred: improved prediction of IL-13 inducing peptides using popular machine learning classifiers.

Background: Inflammatory mediators play havoc in several diseases including the novel Coronavirus disease 2019 (COVID-19) and generally correlate with the severity of the disease. Interleukin-13 (IL-13), is a pleiotropic cytokine that is known to be associated with airway inflammation in asthma and reactive airway diseases, in neoplastic and autoimmune diseases. Interestingly, the recent association of IL-13 with COVID-19 severity has sparked interest in this cytokine.