Explore the words cloud of the DynaOmics project. It provides you a very rough idea of what is the project "DynaOmics" about.
The following table provides information about the project.
Coordinator |
TURUN YLIOPISTO
Organization address contact info |
Coordinator Country | Finland [FI] |
Project website | https://elolab.utu.fi |
Total cost | 1˙499˙869 € |
EC max contribution | 1˙499˙869 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2015-STG |
Funding Scheme | ERC-STG |
Starting year | 2016 |
Duration (year-month-day) | from 2016-06-01 to 2021-05-31 |
Take a look of project's partnership.
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1 | TURUN YLIOPISTO | FI (Turku) | coordinator | 1˙499˙869.00 |
Longitudinal omics data hold great promise to improve biomarker detection and enable dynamic individualized predictions. Recent technological advances have made proteomics an increasingly attractive option but clinical longitudinal proteomic datasets are still rare and computational tools for their analysis underdeveloped. The objective of this proposal is to create a roadmap to detect clinically feasible protein markers using longitudinal data and effective computational tools. A biomedical focus is on early detection of Type 1 diabetes (T1D). Specific objectives are:
1) Novel biomarker detector using longitudinal data. DynaOmics introduces novel types of multi-level dynamic markers that are undetectable in conventional single-time cross-sectional studies (e.g. within-individual changes in abundance or associations), develops optimization methods for their robust and reproducible detection within and across individuals, and validates their utility in well-defined samples. 2) Individualized disease risk prediction dynamically. DynaOmics develops dynamic individualized predictive models using the multi-level longitudinal proteome features and novel statistical and machine learning methods that have previously not been used in this context, including joint models of longitudinal and time-to-event data, and one-class classification type techniques. 3) Dynamic prediction of T1D. DynaOmics builds a predictive model of dynamic T1D risk to assist early detection of the disease, which is crucial for developing future therapeutic and preventive strategies. T1D typically involves a relatively long symptom-free period before clinical diagnosis but current tools to predict early T1D risk have restricted power.
The objectives involve innovative and unconventional approaches and address major unmet challenges in the field, having high potential to open new avenues for diagnosis and treatment of complex diseases and fundamentally novel insights towards precision medicine.
year | authors and title | journal | last update |
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2019 |
Subhash K. Tripathi, Tommi Välikangas, Ankitha Shetty, Mohd Moin Khan, Robert Moulder, Santosh D. Bhosale, Elina Komsi, Verna Salo, Rafael Sales De Albuquerque, Omid Rasool, Sanjeev Galande, Laura L. Elo, Riitta Lahesmaa Quantitative Proteomics Reveals the Dynamic Protein Landscape during Initiation of Human Th17 Cell Polarization published pages: 334-355, ISSN: 2589-0042, DOI: 10.1016/j.isci.2018.12.020 |
iScience 11 | 2020-04-23 |
2017 |
Tomi Suomi, Fatemeh Seyednasrollah, Maria K. Jaakkola, Thomas Faux, Laura L. Elo ROTS: An R package for reproducibility-optimized statistical testing published pages: e1005562, ISSN: 1553-7358, DOI: 10.1371/journal.pcbi.1005562 |
PLOS Computational Biology 13/5 | 2020-04-23 |
2017 |
Fatemeh Seyednasrollah, Johanna Mäkelä, Niina Pitkänen, Markus Juonala, Nina Hutri-Kähönen, Terho Lehtimäki, Jorma Viikari, Tanika Kelly, Changwei Li, Lydia Bazzano, Laura L. Elo, Olli T. Raitakari Prediction of Adulthood Obesity Using Genetic and Childhood Clinical Risk Factors in the Cardiovascular Risk in Young Finns StudyCLINICAL PERSPECTIVE published pages: e001554, ISSN: 1942-3268, DOI: 10.1161/CIRCGENETICS.116.001554 |
Circulation: Cardiovascular Genetics 10/3 | 2020-04-23 |
2018 |
Niina Lietzen, Le T. T. An, Maria K. Jaakkola, Henna Kallionpää, Sami Oikarinen, Juha Mykkänen, Mikael Knip, Riitta Veijola, Jorma Ilonen, Jorma Toppari, Heikki Hyöty, Riitta Lahesmaa, Laura L. Elo Enterovirus-associated changes in blood transcriptomic profiles of children with genetic susceptibility to type 1 diabetes published pages: 381-388, ISSN: 0012-186X, DOI: 10.1007/s00125-017-4460-7 |
Diabetologia 61/2 | 2020-04-23 |
2018 |
Ubaid Ullah, Syed Bilal Ahmad Andrabi, Subhash Kumar Tripathi, Obaiah Dirasantha, Kartiek Kanduri, Sini Rautio, Catharina C. Gross, Sari Lehtimäki, Kanchan Bala, Johanna Tuomisto, Urvashi Bhatia, Deepankar Chakroborty, Laura L. Elo, Harri Lähdesmäki, Heinz Wiendl, Omid Rasool, Riitta Lahesmaa Transcriptional Repressor HIC1 Contributes to Suppressive Function of Human Induced Regulatory T Cells published pages: 2094-2106, ISSN: 2211-1247, DOI: 10.1016/j.celrep.2018.01.070 |
Cell Reports 22/8 | 2020-04-23 |
2017 |
Tomi Suomi, Laura L. Elo Enhanced differential expression statistics for data-independent acquisition proteomics published pages: , ISSN: 2045-2322, DOI: 10.1038/s41598-017-05949-y |
Scientific Reports 7/1 | 2020-04-23 |
2018 |
Maria K. Jaakkola, Aidan J. McGlinchey, Riku Klén, Laura L. Elo PASI: A novel pathway method to identify delicate group effects published pages: e0199991, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0199991 |
PLOS ONE 13/7 | 2020-04-23 |
2017 |
Tommi Välikangas, Tomi Suomi, Laura L. Elo A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation published pages: , ISSN: 1467-5463, DOI: 10.1093/bib/bbx054 |
Briefings in Bioinformatics | 2020-04-23 |
2017 |
Sohrab Saraei, Tomi Suomi, Otto Kauko, Laura L Elo Phosphonormalizer: an R package for normalization of MS-based label-free phosphoproteomics published pages: , ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btx573 |
Bioinformatics | 2020-04-23 |
2018 |
Tommi Välikangas, Tomi Suomi, Laura L. Elo A systematic evaluation of normalization methods in quantitative label-free proteomics published pages: bbw095, ISSN: 1467-5463, DOI: 10.1093/bib/bbw095 |
Briefings in Bioinformatics | 2020-04-23 |
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The information about "DYNAOMICS" are provided by the European Opendata Portal: CORDIS opendata.