Translational SYStemics: Personalised Medicine at the Interface of Translational Research and Systems Medicine

Informations projet

TranSYS

N° de convention de subvention: 860895

DOI 10.3030/860895

Projet clôturé

Date de signature de la CE 19 Août 2019

Date de début 1 Septembre 2019

Date de fin 30 Juin 2024

Financé au titre de

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coût total € 3 916 285,67

Contribution de l’UE € 3 916 285,67

Coordonné par

KATHOLIEKE UNIVERSITEIT LEUVEN
Belgium

Livrables

Other (2)

TranSYS School 1

Lead overlooking Body Training Council Natasa Przulj Details Annex 1 Part B Table 22b

Doctoral Schools

ESRs enrolled in doctoral school programmes regulated by M12

Websites, patent fillings, videos etc. (2)

TranSYS intranet and extranet / SharePoint in place

Website for data sharing internal CO external PU Sharepoint for easy filling of reports and sharing documents within WGs within TranSYS Boards within TranSYS at large

TranSYS recruitment pages online with ESR vacancies posted (recruitment process+gender plan)

Publications

Peer reviewed articles (7)

Economic evaluation in psychiatric pharmacogenomics: a systematic review

Auteurs: Kariofyllis Karamperis, Maria Koromina, Panagiotis Papantoniou, Maria Skokou, Filippos Kanellakis, Konstantinos Mitropoulos, Athanassios Vozikis, Daniel J. Müller, George P. Patrinos, Christina Mitropoulou
Publié dans: The Pharmacogenomics Journal, Numéro 21/4, 2021, Page(s) 533-541, ISSN 1470-269X
Éditeur: Nature Publishing Group
DOI: 10.1038/s41397-021-00249-1

Guided extraction of genome-scale metabolic models for the integration and analysis of omics data

Auteurs: Andrew Walakira, Damjana Rozman, Tadeja Režen, Miha Mraz, Miha Moškon
Publié dans: Computational and Structural Biotechnology Journal, Numéro 19, 2021, Page(s) 3521-3530, ISSN 2001-0370
Éditeur: Elsevier
DOI: 10.1016/j.csbj.2021.06.009

Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics

Auteurs: Maria Koromina, Stefania Koutsilieri, George P. Patrinos
Publié dans: Human Genomics, Numéro 14/1, 2020, ISSN 1479-7364
Éditeur: Springer Nature
DOI: 10.1186/s40246-019-0254-y

Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma

Auteurs: Andrew Walakira, Cene Skubic, Nejc Nadižar, Damjana Rozman, Tadeja Režen, Miha Mraz, Miha Moškon,
Publié dans: Computers in Biology and Medicine, 2023, ISSN 0010-4825
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.compbiomed.2023.106957

The AIMe registry for artificial intelligence in biomedical research.

Auteurs: Julian Matschinske; Julian Matschinske; Nicolas Alcaraz; Arriel Benis; Martin Golebiewski; Dominik G. Grimm; Dominik G. Grimm; Lukas Heumos; Tim Kacprowski; Tim Kacprowski; Tim Kacprowski; Olga Lazareva; Markus List; Zakaria Louadi; Zakaria Louadi; Josch Konstantin Pauling; Nico Pfeifer; Richard Röttger; Veit Schwämmle; Gregor Sturm; Alberto Traverso; Kristel Van Steen; Kristel Van Steen; Martie
Publié dans: VOLUME=18;ISSUE=10;STARTPAGE=1128;ENDPAGE=1131;ISSN=1548-7091;TITLE=Nature Methods, Numéro 2, 2021, ISSN 1548-7091
Éditeur: Nature Publishing Group
DOI: 10.1038/s41592-021-01241-0

Detecting gene–gene interactions from GWAS using diffusion kernel principal components

Auteurs: Andrew Walakira; Junior Ocira; Diane Duroux; Ramouna Fouladi; Miha Moškon; Damjana Rozman; Kristel Van Steen
Publié dans: BMC Bioinformatics 23, Numéro 1, 2022, Page(s) Article number: 57 (2022), ISSN 1471-2105
Éditeur: BioMed Central
DOI: 10.1186/s12859-022-04580-7

An overview of machine learning methods for monotherapy drug response prediction

Auteurs: Farzaneh Firoozbakht, Behnam Yousefi, Benno Schwikowski
Publié dans: Briefings in Bioinformatics, 2021, ISSN 1467-5463
Éditeur: Oxford University Press
DOI: 10.1093/bib/bbab408