Description: Background: Maize is a major crop plant, grown for human and animal nutrition, as well as a renewable resource forbioenergy. When looking at the problems of limited fossil fuels, the growth of the world's population or theworld's climate change, it is important to find ways to increase the yield and biomass of maize and to studyhow it reacts to specific abiotic and biotic stress situations. Within the OPTIMAS systems biology projectmaize plants were grown under a large set of controlled stress conditions, phenotypically characterised andplant material was harvested to analyse the effect of specific environmental conditions or developmentalstages. Transcriptomic, metabolomic, ionomic and proteomic parameters were measured from the same plantmaterial allowing the comparison of results across different omics domains. A data warehouse wasDescriptionThe OPTIMAS Data Warehouse (OPTIMAS-DW) is a comprehensive data collection for maize and integratesdata from different data domains such as transcriptomics, metabolomics, ionomics, proteomics andphenomics. Within the OPTIMAS project, a 44K oligo chip was designed and annotated to describe thefunctions of the selected unigenes. Several treatment- and plant growth stage experiments were performed andmeasured data were filled into data templates and imported into the data warehouse by a Java based importtool. A web interface allows users to browse through all stored experiment data in OPTIMAS-DW includingall data domains. Furthermore, the user can filter the data to extract information of particular interest. All datacan be exported into different file formats for further data analysis and visualisation. The data analysisintegrates data from different data domains and enables the user to find answers to different systems biologyquestions. Finally, maize specific pathway information is provided. Conclusions: With OPTIMAS-DW a data warehouse for maize was established, which is able to handle different datadomains, comprises several analysis results that will support researchers within their work and supportssystems biological research in particular. The system is available athttp://www.optimas-bioenergy.org/optimas_dw.

Description: 〈ns4:p〉The German Network for Bioinformatics Infrastructure (de.NBI) is a national and academic infrastructure funded by the German Federal Ministry of Education and Research (BMBF). The de.NBI provides (i) service, (ii) training, and (iii) cloud computing to users in life sciences research and biomedicine in Germany and Europe and (iv) fosters the cooperation of the German bioinformatics community with international network structures. The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR infrastructure. The de.NBI / ELIXIR-DE training platform, also known as special interest group 3 (SIG 3) ‘Training & Education’, coordinates the bioinformatics training of de.NBI and the German ELIXIR node. The network provides a high-quality, coherent, timely, and impactful training program across its eight service centers. Life scientists learn how to handle and analyze biological big data more effectively by applying tools, standards and compute services provided by de.NBI. Since 2015, more than 300 training courses were carried out with about 6,000 participants and these courses received recommendation rates of almost 90% (status as of July 2020). In addition to face-to-face training courses, online training was introduced on the de.NBI website in 2016 and guidelines for the preparation of e-learning material were established in 2018. In 2016, ELIXIR-DE joined the ELIXIR training platform. Here, the de.NBI / ELIXIR-DE training platform collaborates with ELIXIR in training activities, advertising training courses via TeSS and discussions on the exchange of data for training events essential for quality assessment on both the technical and administrative levels. The de.NBI training program trained thousands of scientists from Germany and beyond in many different areas of bioinformatics.〈/ns4:p〉