PODC is an integrated knowledge- and database providing the information of gene networks (GENs) and knowledge-based functional annotations in model plants and crops. GENs consist of gene expression networks for similar expression profiles (“co-expression profiles” in a broad sense) and regulatory networks with cis-elements and transcription factors. Knowledge-based functional annotations including cis-elements and transcription factors have been collected through natural language processing (NLP) and manual curation of the scientific literature. Users can easily construct GENs under any arbitrary combination of experimental conditions (RNA-Seq expression data) and plant species stored in PODC. With the Plant Ontology and Plant Experimental Conditions Ontology terms assigned to RNA-Seq data, which are whole data obtained from NCBI SRA, RNA-seq datasets under experimental conditions of interest are accessible by keyword searches in PODC. The GENs of two or more species can be quickly combined and easily compared by using orthologs (homologs) among species in the interactive viewer in PODC. The current version of PODC contains the information of thale cress (Arabidopsis thaliana), soybean (Glycine max), barrelclover (Medicago truncatula) , tobacco (Nicotiana tabacum), rice (Oryza sativa), spreading earthmoss (Physcomitrella patens), tomato (Solanum lycopersicum), potato (Solanum tuberosum), sorghum (Sorghum bicolor), grape (Vitis vinifera), corn (Zea mays).
* You can enter one or more keywords separated by a space(s) (e.g. AT2G22120 AT5G40720) for the AND/OR search. The list of keywords can be filled by copying and pasting a column/row from an external file (such as an Excel file).
A phrase containing a space(s) must be enclosed in single quotation marks, such as 'binding protein'.