Abstract Fungi, and particularly fungal pathogens, are having an increasing impact on human health and economy. At the same time, modern high-throughput technologies offer insights deep into the molecular level and thus mechanisms, giving scientists new opportunities to identify fungal biomarkers and essential components for survival and virulence. This wealth of data, however, is most often only analyzed in the context of a specific scientific question, while many more projects may benefit from a multifaceted view on e.g. fungal gene expression under various conditions. The prime challenge is the limited access to readily pre-processed data and circumventing technological biases introduced by different sequencing platforms and software tools across different projects. We here present FungiNetDB, a web platform comprising 139 fungal pathogenicity datasets and statistical analysis of more than 2000 different pairwise gene expression comparisons. FungiNetDB thus resembles a most comprehensive fungal transcriptomics resource, which can be explored without any programming knowledge, allows highly customizable filtering and cross-project comparisons and download of all offered data tables and visualizations.
Schäuble et al. (Mon,) studied this question.