Even before the perception or interaction with pathogens, plants rely on constitutively
guardian molecules, often specific to tissue or stage, with further expression after contact …

Highlights•Review of current methods in fungal plant pathogenicity effector protein
prediction.•Recent advances have been made in structural and machine learning-based …

Knottins, or inhibitor cystine knots (ICKs), are ultra-stable miniproteins with multiple
applications in drug design and medical imaging. These widespread and functionally …

Abstract SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019
and is a coronavirus which is zoonotic in origin. As it spread around the world there has …

Over 120 FDA-approved antibody-based therapeutics are used to treat a variety of diseases.
However, many candidates could fail because of unfavorable physicochemical properties …

The complexity of searching algorithms in classical computing is a classic problem and a
research area. Quantum computers and quantum algorithms can efficiently compute some …

Predictive models for prognosis of small sample advanced schistosomiasis patients have
not been well studied. We aimed to construct prognostic predictive models of small sample …

Motivation Classification by supervised machine learning greatly facilitates the annotation of
protein characteristics from their primary sequence. However, the feature generation step in …

Traditional medicinal plants are rich reservoirs of antimicrobial agents, including
antimicrobial peptides (AMPs). Advances in genomic sequencing, in silico AMP predictions …

As antibiotic-resistant bacterial pathogens become an ever-increasing concern,
antimicrobial peptides (AMPs) have grown increasingly attractive as alternatives. Potentially …