sysbiostor.unl.edu

Introduction

Fungal pathogens cause various diseases to hosts from plants to animals, and fungal diseases have contributed to death and disability in humans, devastated agricultural crops, and triggered global wildlife extinctions or population declines.

Despite the extensive influence of fungi on human health and life, the threats posed by emerging fungal pathogens are poorly understood. Therefore, we propose a study on fungal pathogens employing the state-of-the-art computational technology. We plan to construct a comprehensive database with all known fungal virulence factors and develop a novel algorithm to predict putative virulence factors for any given fungal pathogen. Bioinformatics algorithms have been applied and large-scale databases developed in almost every field of biological research. There exist, however, only a very limited number of fungal virulence genes databases and applicable prediction algorithms, despite the importance. The proposed project aims at bridging this gap, and creating a pivotal platform that will stimulate and facilitate further bench studies on fungal pathogens.

The database is expected to greatly stimulate and facilitate further studies in fungal pathogens; both experimental biologists and computational biologists can use the database and/or the predicted virulence factors to guide their search for new virulence factors and/or discovery of new pathogen-host interaction mechanisms in fungi.



Citation: T. Lu, B. Yao, C. Zhang. DFVF: database of fungal virulence factors. DATABASE (2012); 2012:bas032.