Opendata, web and dolomites

DynaOmics SIGNED

From longitudinal proteomics to dynamic individualized diagnostics

Total Cost €


EC-Contrib. €






 DynaOmics project word cloud

Explore the words cloud of the DynaOmics project. It provides you a very rough idea of what is the project "DynaOmics" about.

single    fundamentally    data    detection    detect    insights    prediction    detector    biomarker    class    individual    medicine    introduces    technological    hold    attractive    machine    assist    proteomic    techniques    event    statistical    sectional    innovative    omics    free    optimization    cross    dynamically    samples    underdeveloped    conventional    protein    models    strategies    tools    builds    avenues    proteomics    diabetes    made    treatment    joint    predictive    unmet    time    datasets    restricted    learning    involve    undetectable    validates    individualized    precision    individuals    context    biomedical    predict    abundance    roadmap    reproducible    therapeutic    associations    previously    clinical    dynaomics    disease    promise    model    t1d    develops    predictions    relatively    longitudinal    rare    power    create    feasible    classification    proteome    utility    diseases    unconventional    option    symptom    computational    period    clinically    markers    diagnosis    dynamic    types    preventive    risk   

Project "DynaOmics" data sheet

The following table provides information about the project.


Organization address
city: Turku
postcode: 20014

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Finland [FI]
 Project website
 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.

# participants  country  role  EC contrib. [€] 
1    TURUN YLIOPISTO FI (Turku) coordinator 1˙499˙869.00


 Project objective

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
List of publications.
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

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "DYNAOMICS" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email ( and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "DYNAOMICS" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

inhibiTOR (2020)

Novel selective mTORC1 inhibitors

Read More  

MIMATOM (2020)

Paleomagnetism and rock-magnetism by Micro-Magnetic Tomography

Read More  

FaultScan (2019)

Passive seismic scanning of the preparation phase of damaging earthquakes

Read More