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https://www.selleckchem.com/products/bi-2852.html The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plsearch process.The venom of Lycosoidea spiders is a complex multicomponent mixture of neurotoxic peptides (main components) and antimicrobial peptides (AMPs) as minor components. In this study, we described the high-throughput identification and analysis of AMPs from Lycosa sinensis venom (named LS-AMPs) using a combination strategy that includes the following three different analysis approaches (i) peptidomic analysis, namely reversed-phase high-performance liquid chromatography (RP-HPLC) separation plus top-down sequencing by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS); (ii) transcriptomic analysis, namely cDNA library construction plus DNA sequencing; (iii) bioinformatic analysis, namely analysis and prediction for molecular characters of LS-AMPs by the online biology databases. In total, 52 sequences of AMPs were identified from L. sinensis venom, and all AMPs can be categori

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