@article{55fd43be83c54743b4c209e0b7ed046e,
title = "Network medicine for disease module identification and drug repurposing with the NeDRex platform",
abstract = "Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs and faster drug development timelines. However, the data necessary for the identification of disease modules, i.e. pathways and sub-networks describing the mechanisms of complex diseases which contain potential drug targets, are scattered across independent databases. Moreover, existing studies are limited to predictions for specific diseases or non-translational algorithmic approaches. There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. We close this gap with NeDRex, an integrative and interactive platform for network-based drug repurposing and disease module discovery. NeDRex integrates ten different data sources covering genes, drugs, drug targets, disease annotations, and their relationships. NeDRex allows for constructing heterogeneous biological networks, mining them for disease modules, prioritizing drugs targeting disease mechanisms, and statistical validation. We demonstrate the utility of NeDRex in five specific use-cases.There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. Here, the authors close this gap with NeDRex, an integrative and interactive platform.",
keywords = "ACTIVATED RECEPTOR, ALZHEIMERS-DISEASE, COGNITIVE IMPAIRMENT, EXPRESSION, GENE, GROWTH-FACTOR, HUNTINGTONS-DISEASE, OVARIAN-CANCER, RESISTANCE, TISSUE, PROTEIN",
author = "S. Sadegh and J. Skelton and E. Anastasi and J. Bernett and D.B. Blumenthal and G. Galindez and M. Salgado-Albarran and O. Lazareva and K. Flanagan and S. Cockell and C. Nogales and A.I. Casas and H.H.H.W. Schmidt and J. Baumbach and A. Wipat and T. Kacprowski",
note = "Funding Information: S.S., J.S., E.A., K.F., S.C., H.H.H.W.S., J.Ba., A.W., and T.K. are grateful for financial support from REPO-TRIAL. REPO-TRIAL has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 777111. This publication reflects only the authors{\textquoteright} view and the European Commission is not responsible for any use that may be made of the information it contains. J.Ba. and T.K. are grateful for financial support from BMBF grant Sys_CARE (no. 01ZX1908A) of the Federal German Ministry of Research and Education. J.Ba. was partially funded by his VILLUM Young Investigator Grant no. 13154. Contribution by J.Be. is funded by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (grant 01ZX1910D). M.S.-A. is grateful for a Ph.D. fellowship funding from CONACYT (CVU659273) and the German Academic Exchange Service, DAAD (ref. 91693321). Contribution by O.L. is funded by the Bavarian State Ministry of Science and the Arts as part of the Bavarian Research Institute for Digital Transformation. A.I.C. is currently financially supported by the DFG Walter Benjamin Program (ref. DFG CA 2642/1-1). Figures 1 and 2 are created with BioRender.com. Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = nov,
day = "25",
doi = "10.1038/s41467-021-27138-2",
language = "English",
volume = "12",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",
}