Databases - AG Diederichs

From our different research projects, we provide comprehensive and easy-to-use databases to facilitate research and access to our research data for the scientific community. Please share your thoughts - and cite the respective original publications if you use any of our databases.

Databases on RNA - Protein Complexes

R-DeeP
R-DeeP provides the proteome-wide screening results for RNA-dependent protein complexes based on our paper in Molecular Cell 2019.

RBP2GO
RBP2GO provides a comprehensive database of RNA-binding or RNA-dependent proteins from all available proteome-wide studies in 13 different species. It includes the annotation of their functions as well as interaction partners - and allows also reverse searches for RNA-binding proteins with specific molecular functions, biological processes, cellular compartments or a known link to cancer. RBP2GO is published in Nucleic Acids Reseach 2021.

circ2GO
This database visualizes the circular RNA expression data derived from our comprehensive transcriptome profiling of human lung cancer cell lines using rRNA-depleted RNA published in Cancers 2020. In addition, it offers search opportunities for circRNAs linked to molecular mechanisms, biological processes or cellular components via gene onotology or for circRNA - microRNA pairs as published in Cancers 2020.

Databases on non-canonical Mutations in Cancer

SynMICdb
SynMICdb provides a comprehensive database on synonymous mutations in human cancer including their frequency, signature-normalized frequency and related tumor entities as well as orthogonal data like evolutionary conservation and impact on secondary RNA structure leading to the SynMICdb score to predict the likelihood of a functional impact of a given synonymous mutation. SynMICdb is based on our publication in Nature Communications 2019.

NonStopdb
NonStopdb is the first database devoted to nonstop mutations - a.k.a. stop-loss mutations and comprising nonstop extension and readthrough mutations - which extend a protein at its C-terminus. It is based on our research on nonstop mutations in human cancer and has been published in Nature Cell Biology 2020.

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