| Autor: |
Ricardo Moreira Borges, Fernanda Neves Costa, Fernanda Oliveira Chagas, Andrew Magno Teixeira, Jaewon Yoon, Márcio Barczyszyn Weiss, Camila Manoel Crnkovic, Alan Cesar Pilon, Bruno Carius Garrido, Luz Adriana Betancur, Abel Mateo Forero Tunjano, Leonardo Castellanos, Freddy Ramos, Monica Tallarico Pupo, Stefan Kuhn |
| Rok vydání: |
2022 |
| DOI: |
10.26434/chemrxiv-2022-5fj6v-v2 |
| Popis: |
DAFdiscovery is a pipeline designed to help users combine NMR, MS and bioactivity data in a notebook-based application to accelerate annotation and discovery of bioactive compounds. It applies Statistical Total Correlation (STOCSY) and Statistical HeteroSpectroscopy (SHY) calculation in their data using an easy-to-follow Jupyter Notebook. Different case studies are presented for benchmarking, and the resultant outputs are shown to aid natural products identification and discovery. The goal is to encourage users to acquire MS and NMR data from their samples (in replicated samples and fractions when available) and to explore their variance to highlight MS features, NMR peaks, and bioactivity that might be correlated to accelerate bioactive compound discovery or for annotation-identification studies. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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