Daniela Digles

T: +43-1-4277-55007
daniela.digles@univie.ac.at

ORCID iD

Currently on maternity leave.

Postdoc

Daniela Digles is senior lecturer at the Department of Pharmaceutical Sciences, University of Vienna. She completed her PhD studies with a DOC-fFORTE-fellowship of the Austrian Academy of Sciences at the University of Vienna, in the Pharmacoinformatics Research Group of Prof. Gerhard Ecker.

In 2012 she started her Post-doc within the Open PHACTS project (IMI), and later on within the Open PHACTS Foundation, where she was testing the developed system, creating KNIME workflows to access the data to answer research questions, as well as user support. Next, she was involved in the FAIRness for Life Science Data in Austria project as well as the RESOLUTE project (IMI). Furthermore, she is a community curator of WikiPathways.

Her main research interests are the usage and quality control of open data (especially for solute carrier proteins), classification schemes, and the application of KNIME to connect data resources.

Publications

Digles, D, Ingles-Prieto, A, Dvorak, V, Mocking, TAM, Goldmann, U, Garofoli, A, Homan, EJ, Di Silvio, A, Azzollini, L, Sassone, F, Fogazza, M, Bärenz, F, Pommereau, A, Zuschlag, Y, Ooms, JF, Tranberg-Jensen, J, Hansen, JS, Stanka, J, Sijben, HJ, Batoulis, H, Bender, E, Martini, R, IJzerman, AP, Sauer, DB, Heitman, LH, Manolova, V, Reinhardt, J, Ehrmann, A, Leippe, P, Ecker, GF, Huber, KVM, Licher, T, Scarabottolo, L, Wiedmer, T & Superti-Furga, G 2024, 'Advancing drug discovery through assay development: a survey of tool compounds within the human solute carrier superfamily', Frontiers in Pharmacology, vol. 15, 1401599. https://doi.org/10.3389/fphar.2024.1401599

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Granulo, N, Sosnin, S , Digles, D & Ecker, GF 2024, 'The macrocycle inhibitor landscape of SLC‐transporter', Molecular Informatics, vol. 43, no. 5, e202300287. https://doi.org/10.1002/minf.202300287

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Huang, J, Osthushenrich, T, MacNamara, A, Mälarstig, A, Brocchetti, S, Bradberry, S, Scarabottolo, L, Ferrada, E, Sosnin, S , Digles, D, Superti-Furga, G & Ecker, GF 2024, 'ProteoMutaMetrics: machine learning approaches for solute carrier family 6 mutation pathogenicity prediction', Rsc advances, vol. 14, no. 19, 00748, pp. 13083-13094. https://doi.org/10.1039/d4ra00748d

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Agrawal, A, Balcı, H, Hanspers, K, Coort, SL, Martens, M, Slenter, DN, Ehrhart, F, Digles, D, Waagmeester, A, Wassink, I, Abbassi-Daloii, T, Lopes, EN, Iyer, A, Acosta, JM, Willighagen, LG, Nishida, K, Riutta, A, Basaric, H, Evelo, CT, Willighagen, EL, Kutmon, M & Pico, AR 2024, 'WikiPathways 2024: next generation pathway database', Nucleic Acids Research, vol. 52, no. D1, pp. D679-D689. https://doi.org/10.1093/nar/gkad960

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Hanspers, K, Kutmon, M, Coort, SL, Digles, D, Dupuis, LJ, Ehrhart, F, Hu, F, Lopes, EN, Martens, M, Pham, N, Shin, W, Slenter, DN, Waagmeester, A, Willighagen, EL, Winckers, LA, Evelo, CT & Pico, AR 2021, 'Ten simple rules for creating reusable pathway models for computational analysis and visualization', PLoS Computational Biology, vol. 17, no. 8, e1009226. https://doi.org/10.1371/journal.pcbi.1009226

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Activities

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