Stranneheim H Wedell A. Exome and genome sequencing: a revolution for the discovery and diagnosis of monogenic disorders. J Intern Med. (2016) 279:3–15. 10.1111/joim.1239926250718
Doctoral Studies as Part of an Innovative Training Network (ITN) (2023). Available online at: https://open-research-europe.ec.europa.eu/articles/1-34 (accessed December 1, 2023).
Doonan F Taylor L Branduardi P Morrissey JP. Innovative training networks: overview of the Marie Skłodowska-curie PhD training model. FEMS Microbiol Lett. (2018) 365:fny207. 10.1093/femsle/fny20730239741
marie-sklodowska-curie-actions.ec.europa.eu (2023). Available online at: https://marie-sklodowska-curie-actions.ec.europa.eu/ (accessed December 1, 2023).
cordis.europa.eu (2023). Available online at: https://cordis.europa.eu/programme/id/H2020_MSCA-ITN-2019 (accessed December 1, 2023).
Translational SYStemics. Personalised Medicine at the Interface of Translational Research and Systems Medicine. (2023). Available online at: https://cordis.europa.eu/project/id/860895 (accessed December 1, 2023).
Morris SA Alsaidi AT Verbyla A Cruz A Macfarlane C Bauer J et al. Cost effectiveness of pharmacogenetic testing for drugs with clinical pharmacogenetics implementation consortium (CPIC) guidelines: a systematic review. Clin Pharmacol Ther. (2022) 112:1318–28. 10.1002/cpt.275436149409
Bienfait K Chhibber A Marshall JC Armstrong M Cox C Shaw PM et al. Current challenges and opportunities for pharmacogenomics: perspective of the Industry Pharmacogenomics Working Group (I-PWG). Hum Genet. (2022) 141:1165–73. 10.1007/s00439-021-02282-334081195
Najjary S Kros JM Stricker BH Ruiter R Shuai Y Kraaij R et al. Association of blood cell-based inflammatory markers with gut microbiota and cancer incidence in the Rotterdam study. Cancer Med. (2023). 10.21203/rs.3.rs-3110898/v138366800
Walakira A Rozman D Režen T Mraz M Moškon M. Guided extraction of genome-scale metabolic models for the integration and analysis of omics data. Comput Struct Biotechnol J. (2021) 19:3521–30. 10.1016/j.csbj.2021.06.00934194675
Walakira A Skubic C Nadižar N Rozman D Režen T Mraz M et al. Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma. Comput Biol Med. (2023) 159:106957. 10.1016/j.compbiomed.2023.10695737116239
Melograna F Li Z Galazzo G van Best N Mommers M Penders J et al. Edge and modular significance assessment in individual-specific networks. Sci Rep. (2023) 13:7868. 10.1038/s41598-023-34759-837188794
van Hilten A Melograna F Fan B Niessen WJ van Steen K Roshchupkin GV. Detecting genetic interactions with visible neural networks. bioRxiv. (2024) p. 2024-02. 10.1101/2024.02.27.582086
Li Z Melograna F Hoskens H Duroux D Marazita ML Walsh S et al. netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity. Front Genet. (2023) 14:1286800. 10.3389/fgene.2023.128680038125750
Andreoli L Peeters H Van Steen K Dierickx K. Taking the risk. A systematic review of ethical reasons and moral arguments in the clinical use of polygenic risk scores. American J Med Genet A. (2024) 2024:e63584. 10.1002/ajmg.a.6358438450933
Yousefi B Melograna F Galazzo G van Best N Mommers M Penders J et al. Capturing the dynamics of microbial interactions through individual-specific networks. Front Microbiol. (2023) 14:1170391. 10.3389/fmicb.2023.117039137256048
Yousefi B Firoozbakht F Melograna F Schwikowski B Van Steen K. PLEX.I: a tool to discover features in multiplex networks that reflect clinical variation. Front Genet. (2023) 14:1274637. 10.3389/fgene.2023.127463737928248
Yousefi B Schwikowski B. Consensus clustering for robust bioinformatics analysis. bioRxiv. (2024). p. 2024-03. 10.1101/2024.03.21.586064
Mihajlović K Ceddia G Malod-Dognin N Novak G Kyriakis D Skupin A et al. Multi-omics integration of scRNA-Seq time series data predicts new intervention points for Parkinson's disease. bioRxiv. (2023). p. 2023-12. 10.1101/2023.12.12.57055438744869
Gureghian V Herbst H Kozar I Mihajlovic K Malod-Dognin N Ceddia G et al. A multi-omics integrative approach unravels novel genes and pathways associated with senescence escape after targeted therapy in NRAS mutant melanoma. Cancer Gene Ther. (2023) 30:1330–45. 10.1038/s41417-023-00640-z37420093
Li S Schmid KT de Vries DH Korshevniuk M Losert C Oelen R et al. Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data. Genome Biol. (2023) 24:80. 10.1186/s13059-023-02897-x37072791
Knauer-Arloth J Hryhorzhevska A Binder EB. Multi-omics analysis of the molecular response to glucocorticoids-insights into shared genetic risk from psychiatric to medical disorders. medRxiv. (2023). p. 2023-12. 10.1101/2023.12.05.23299430
Skokou M Karamperis K Koufaki MI Tsermpini EE Pandi MT Siamoglou S et al. Clinical implementation of preemptive pharmacogenomics in psychiatry. Ebiomedicine. (2024) 101:105004. 10.1016/j.ebiom.2024.10500938364700
Karamperis K Koromina M Papantoniou P Skokou M Kanellakis F Mitropoulos K et al. Economic evaluation in psychiatric pharmacogenomics: a systematic review. Pharmacogen J. (2021) 21:533–41. 10.1038/s41397-021-00249-134215853
Swen JJ van der Wouden CH Manson LE Abdullah-Koolmees H Blagec K Blagus T et al. A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study. Lancet. (2023) 401:347–56. 10.1016/S0140-6736(22)01841-436739136
Katz S Suijker J Hardt C Madsen MB Vries AMd Pijpe A et al. Decision support system and outcome prediction in a cohort of patients with necrotizing soft-tissue infections. Int J Med Inform. (2022) 167:104878. 10.1016/j.ijmedinf.2022.10487836194993
Katz S Martins dos Santos VA Saccenti E Roshchupkin GV. mEthAE: an explainable AutoEncoder for methylation data. bioRxiv. (2023). p. 2023-07. 10.1101/2023.07.18.549496
Li Z Katz S Martins dos Santos VA Fardo D Claes P Saccenti E et al. Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping. bioRxiv. (2024). p. 2024-02. 10.1101/2024.02.05.578873
Kočar E Katz S Pušnik Ž Bogovič P Turel G Skubic C et al. COVID-19 and cholesterol biosynthesis: toward innovative decision support systems. Iscience. (2023) 26:107799. 10.1016/j.isci.2023.10779937720097
Stenzinger A Edsjö A Ploeger C Friedman M Fröhling S Wirta V et al. Trailblazing precision medicine in Europe: a joint view by genomic medicine Sweden and the centers for personalized medicine, ZPM, in Germany. Semin Cancer Biol. (2022) 84:242–54. 10.1016/j.semcancer.2021.05.02634033893
Lévy Y. Genomic medicine 2025: France in the race for precision medicine. Lancet. (2016) 388:2872. 10.1016/S0140-6736(16)32467-927979406
Stenzinger A Moltzen EK Winkler E Molnar-Gabor F Malek N Costescu A et al. Implementation of precision medicine in healthcare—A European perspective. J Intern Med. (2023) 294:437–54. 10.1111/joim.1369837455247
Bedard PL Hyman DM Davids MS Siu LL. Small molecules, big impact: 20 years of targeted therapy in oncology. Lancet. (2020) 395:1078–88. 10.1016/S0140-6736(20)30164-132222192
Rosenquist R Fröhling S Stamatopoulos K. Precision medicine in cancer: a paradigm shift. Semin Cancer Biol. (2022) 84:1–2. 10.1016/j.semcancer.2022.05.00835597437
Notten A Es-Sadki N Ciarli T Visentin F Wang L Wintjes R et al. Evaluation Study of the European Framework Programmes for Research and Innovation for Excellent Science: Horizon 2020: Phase 1 Final Study Report. Luxembourg: Publications Office of the European Union (2023).
Yeast Cell Factories. Training Researchers to Apply Modern Post-Genomic Methods In Yeast Biotechnology–cordis. europa.eu. (2023). Available online at: https://cordis.europa.eu/project/id/606795 (accessed December 1, 2023).
Woolston C. Depression and anxiety ‘the Norm' for UK PhD students. Nature. (2021). 10.1038/d41586-021-03761-3. [Epub ahead of print].34907376
