Geschmack ist vorhersagbar: Mit FlavorMiner. FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…
Seit Februar 2021 bietet Wolfgang Brandt, ehemaliger Leiter der Arbeitsgruppe Computerchemie am IPB, sein Citizen Science-Projekt zur Pilzbestimmung an. Dafür hat er in regelmäßigen Abständen öffentliche Vorträge zur Vielfalt…
Herres-Pawlis, S.; Bach, F.; Bruno, I. J.; Chalk, S. J.; Jung, N.; Liermann, J. C.; McEwen, L. R.; Neumann, S.; Steinbeck, C.; Razum, M.; Koepler, O.;Minimum information standards in chemistry: A call for better research data management practicesAngew. Chem. Int. Ed.61e202203038(2022)DOI: 10.1002/anie.202203038
Research data management (RDM) is needed to assist experimental advances and data collection in the chemical sciences. Many funders require RDM because experiments are often paid for by taxpayers and the resulting data should be deposited sustainably for posterity. However, paper notebooks are still common in laboratories and research data is often stored in proprietary and/or dead-end file formats without experimental context. Data must mature beyond a mere supplement to a research paper. Electronic lab note-books (ELN) and laboratory information managementsystems (LIMS) allow researchers to manage data better and they simplify research and publication. Thus, an agreement is needed on minimum information standards for data handling to support structured approaches to data reporting. As digitalization becomes part of curricular teaching, future generations of digital native chemists will embrace RDM and ELN as an organic part of their research.
Publikation
Peters, K.; Gorzolka, K.; Bruelheide, H.; Neumann, S.;Seasonal variation of secondary metabolites in nine different bryophytesEcol. Evol.89105-9117(2018)DOI: 10.1002/ece3.4361
Bryophytes occur in almost all land ecosystems and contribute to global biogeochemical cycles, ecosystem functioning, and influence vegetation dynamics. As growth and biochemistry of bryophytes are strongly dependent on the season, we analyzed metabolic variation across seasons with regard to ecological characteristics and phylogeny. Using bioinformatics methods, we present an integrative and reproducible approach to connect ecology with biochemistry. Nine different bryophyte species were collected in three composite samples in four seasons. Untargeted liquid chromatography coupled with mass spectrometry (LC/MS) was performed to obtain metabolite profiles. Redundancy analysis, Pearson's correlation, Shannon diversity, and hierarchical clustering were used to determine relationships among species, seasons, ecological characteristics, and hierarchical clustering. Metabolite profiles of Marchantia polymorpha and Fissidens taxifolius which are species with ruderal life strategy (R‐selected) showed low seasonal variability, while the profiles of the pleurocarpous mosses and Grimmia pulvinata which have characteristics of a competitive strategy (C‐selected) were more variable. Polytrichum strictum and Plagiomnium undulatum had intermediary life strategies. Our study revealed strong species‐specific differences in metabolite profiles between the seasons. Life strategies, growth forms, and indicator values for light and soil were among the most important ecological predictors. We demonstrate that untargeted Eco‐Metabolomics provide useful biochemical insight that improves our understanding of fundamental ecological strategies.