Matej Oresic profile picture
Matej
Oresic
Professor, Turku Bioscience Centre
InFLAMES Flagship
Ph.D.

Contact

+358 29 450 3798
+358 46 923 3395
Tykistökatu 6
20520
Turku

Areas of expertise

Systems biology
bioinformatics
metabolomics
lipidomics
biophysics
systems medicine
computational biology

Biography

Professor Matej Orešič holds a PhD in biophysics from Cornell University. He is Professor of Medical Sciences with Specialization in Systems Medicine at School of Medical Sciences (Örebro University, Sweden), Group Leader in Systems Medicine at the Turku Bioscience Centre (University of Turku, Finland), and Guest Professor at the Oil Crops Research Institute Chinese Academy of Agricultural Sciences (Wuhan, PR China). His main research areas are metabolomics applications in biomedical research and integrative bioinformatics. He is particularly interested in the identification of disease vulnerabilities associated with different metabolic phenotypes and the underlying mechanisms linking these vulnerabilities with the development of specific disorders or their co-morbidities, with specific focus on obesity and diabetes and their co-morbidities. Dr. Orešič has also initiated the popular MZmine open source project, leading to popular software for metabolomics data processing. Previosuly, Dr. Orešič was principal investigator at Steno Diabetes Center (Gentofte, Denmark), research professor at VTT Technical Research Centre of Finland (Espoo, Finland), head of computational biology and modeling at Beyond Genomics, Inc. (Waltham/MA) and bioinformatician at LION Bioscience Research in Cambridge/MA. In 2016, Dr. Oresic received the Lifetime Honorary Fellow award from the Metabolomics Society.

Research

Our main research area is systems medicine, particularly metabolomics applications in biomedical research and related integrative bioinformatics. Specifically, we am particularly interested in the identification of disease vulnerabilities associated with different metabolic phenotypes and the underlying mechanisms linking these vulnerabilities with the development of specific disorders or their co-morbidities. Such in depth understanding of the metabolic phenotypes in health and disease is crucial if one is to implement personalized medicine. Dr. Orešič initiated the popular MZmine open source project, leading to popular software for metabolomics data processing. Main ongoing projects: Strategic Research Agreement, Juvenile Diabetes Research Foundation (9/2016-9/2018): Metabolomic and Proteomic markers staging progression to type 1 diabetes in autoantibody positive children – PI Strategic Research Agreement, Juvenile Diabetes Research Foundation (9/2016-9/2018): Mother-infant interactions in relation to potential biomarkers of beta-cell autoimmunity and type 1 diabetes – PI Academy of Finland Centre of Excellence in Molecular Systems Immunology and Physiology Research (2012-2017) - PI Strategic Research Agreement, Juvenile Diabetes Research Foundation (Integrative multi-omic study of early progression to type 1 diabetes; 2014-2017) - PI pHealth Programme, multi-PI collaborative project, Academy of Finland (Personalised medicine to predict and prevent Type 1 Diabetes; 9/2015-8/2019) – Co-PI EU H2020 EPoS (Elucidating Pathways of Steatohepatitis) - Workpackage leader EU FP7 METSY (Integrated neuroimaging and metabolic platform for characterisation of early psychosis and prediction of patient outcomes) - Coordinator

Publications

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MS-based lipidomics of human blood plasma: a community-initiated position paper to develop accepted guidelines (2018)

Journal of Lipid Research
Bo Burla, Makoto Arita, Masanori Arita, Anne K. Bendt, Amaury Cazenave-Gassiot, Edward A. Dennis, Kim Ekroos, Xianlin Han, Kazutaka Ikeda, Gerhard Liebisch, Michelle K. Lin, Tze Ping Loh, Peter J. Meikle, Matej Orešič, Oswald Quehenberger, Andrej Shevchenko, Federico Torta, Michael J. O. Wakelam, Craig E. Wheelock, Markus R. Wenk
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

A computational framework to integrate high-throughput ‘-omics’ datasets for the identification of potential mechanistic links (2018)

Nature Protocols
Helle Krogh Pedersen, Sofia K. Forslund, Valborg Gudmundsdottir, Anders Østergaard Petersen, Falk Hildebrand, Tuulia Hyötyläinen, Trine Nielsen, Torben Hansen, Peer Bork, S. Dusko Ehrlich, Søren Brunak, Matej Oresic, Oluf Pedersen, Henrik Bjørn Nielsen
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma (2017)

Journal of Lipid Research
John A. Bowden, Alan Heckert, Candice Z. Ulmer, Christina M. Jones, Jeremy P. Koelmel, Laila Abdullah, Linda Ahonen, Yazen Alnouti, Aaron Armando, John M. Asara, Takeshi Bamba, John R. Barr, Jonas Bergquist, Christoph H. Borchers-, Joost Brandsma, Susanne B. Breitkopf, Tomas Cajka, Amaury Cazenave-Gassiot, Antonio Checa, Michelle A Cinel, Romain A. Colas, Serge Cremers, Edward A. Dennis, James E. Evans, Alexander Fauland, Oliver Fiehn, Michael S. Gardner, Timothy J. Garrett, Katherine H. Gotlinger, Jun Han, Yingying Huang, Aveline Huipeng Neo, Tuulia Hyötyläinen, Yoshihiro Izumi, Hongfeng Jiang, Houli Jiang, Jiang Jiang, Maureen Kachman, Reiko Kiyonami, Kristaps Klavins, Christian Klose, Harald C. Köfeler, Johan Kolmert, Therese Koal, Grielof Koster, Zsuzsanna Kuklenyik, Irwin J. Kurland, Michael Leadley, Karen Lin, Krishna Rao Maddipati, Danielle McDougall, Peter J. Meikle, Natalie A Mellett, Cian Monnin, M. Arthur Moseley, Renu Nandakumar, Matej Oresic, Rainey Patterson, David Peake, Jason S. Pierce, Martin Post, Anthony D. Postle, Rebecca Pugh, Yunping Qiu, Oswald Quehenberger, Parsram Ramrup, Jon Rees, Barbara Rembiesa, Denis Reynaud, Mary R. Roth, Susanne Sales, Kai Schuhmann, Michal Laniado Schwartzman, Charles N. Serhan, Andrej Shevchenko, Stephen E. Somerville, Lisa St. John-Williams, Michal A. Surma, Hiroaki Takeda, Rhishikesh Thakare, J. Will Thompson, Federico Torta, Alexander Triebl, Martin Trötzmüller, S. J. Kumari Ubhayasekera, Dajana Vuckovic, Jacquelyn M. Weir, Ruth Welti, Markus R. Wenk, Craig E. Wheelock, Libin Yao, Min Yuan, Xueqing Heather Zhao, Senlin Zhou
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))