@article {Hansen2020.03.18.979971, author = {Bjoern Oest Hansen and Stefan Olsson}, title = {OmicsDB::Pathogens - A database for exploring functional networks of plant pathogens}, elocation-id = {2020.03.18.979971}, year = {2020}, doi = {10.1101/2020.03.18.979971}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Plant pathogens are a great threat to food security. To combat them we need an understanding of how they work. Integrating large-scale omics datasets such as genomes and transcriptomes has been shown to provide deeper insights into many aspects of molecular biology. For a better understanding of plant pathogens, we aim to construct a platform for accessing genomic and gene co-expression networks for a range of pathogens and reference species. Currently we have integrated genomic and transcriptomics data from 10 species (Fusarium graminearum, Ustilago maydis, Blumeria graminis, Neurospora crassa, Schizosaccharomyces pombe, Saccharomyces cerevisiae, Escherichia coli, Arabidopsis thaliana, Mus musculus and Homo sapiens).Here we introduce OmicsDB::Pathogens (http://pathogens.omicsdb.org), a publicly available web portal with an underlying database containing genomic, and transcriptomic data and analysis tools. It allows non-bioinformaticians to browse genomic data and inspect and compare biological networks across species.The information is modelled in a graph-based database, enabling flexibility for querying and future extensions. Tools such as BLAST and Cytoscape.js are available together with the option of performing GO enrichment analysis. The database also enables the user to browse information such as Orthologs, Protein domains and publications citing a given gene.Herein we describe how to use this platform for generating hypotheses for the function of a gene.Availability and Implementation Currently, Omicsdb supports networks for 10 organisms and is freely available for public use at http://pathogens.omicsdb.org}, URL = {https://www.biorxiv.org/content/early/2020/03/23/2020.03.18.979971}, eprint = {https://www.biorxiv.org/content/early/2020/03/23/2020.03.18.979971.full.pdf}, journal = {bioRxiv} }