Within EPHOR we will develop methods and tools to characterise the working-life exposome. By applying these,
we will obtain better and more complete knowledge on the working-life exposome. Through uniquely combining
large-scale pooling of existing data (>40 cohorts; ~ 21 million people) systematically looking at many types of
exposure and diseases with the collection of new data in case studies in which we will investigate the effects
of working-life exposure on respiratory health in the general population and night shift workers.
LifeGlimmer is responsible for the bioinformatics analysis of the omics data, including the analysis of
adverse outcome pathways (AOPs) and exposome stratification. In addition, we are involved in the establishment of the data
management and analytics platform and, in particular, in the visualisation of AOPs in the envisaged Exposome Toolbox.
The INFECT consortium takes on a novel systems biology approach towards necrotizing soft tissue infection
(NSTI). NSTI is an aggressively progressing bacterial infection that usually starts from a small wound.
The diagnosis of this infection is often challenging due to clinical heterogeneity like presence of comorbidities.
The INFECT consortium takes on a novel systems biology approach by integrating clinical data with the underlying molecular data in order to
understand infection specific molecular mechanisms.
LifeGlimmer is involved as a computational partner in the consortium. We integrate interactions with
experimental omics data to pinpoint disease-specific molecular mechanisms and develop statistical methods
to reveal associations between clinical parameters (for example comorbidities, age, or BMI) and infection
types. Furthermore, we develop effective classification methods to identify patient subgroups from a
heterogeneous patient cohort aiming for a better diagnosis and ultimately treatment.
The goal of PERMIT is to establish personalised medicine in severe infectious diseases, specifically for
necrotizing soft tissue infections as well as sepsis. Focus lies on the improvement of diagnosis and therapy
predominantly based on the integration of diverse data sources and the derivation of a more precise risk assessment..
LifeGlimmer provides computational analysis of omics data as well as the establishment of decision
support system for personalised treatment of NSTI patients.
The PERAID project proposes to implement personalized medicine (PM) in severe infectious diseases,
specifically focusing on the life-threatening necrotizing soft tissue infections (NSTI) as well as the large
heterogeneous group of sepsis patients that represent a global health priority. Personalized medicine is
a neglected, albeit much desired, development in the field of acute infectious diseases. The patient
population is highly heterogeneous with different pathogens, pathogenic mechanisms, as well as varying
predisposing host factors, and importantly, a dysregulated host response to infection is directly linked
to severity and outcome of severe infections, i.e. sepsis and NSTI. Hence, tailored immunotherapy in
stratified patients holds great potential.
PERAID builds on the advances and resources created in the EU FP7-project INFECT, including the
world’s largest patient cohort on NSTI (Scandinavian patients enrolled by PERAID’s partners), biobank,
multi-omics data, and pathophysiologic models. These already available resources combined with an
extended Nordic consortium enables PERAID to advance to the next phase of implementing PM in
NSTI as well as extending the efforts into the sepsis field.
LifeGlimmer contributes by developing tools that support clinical decision making in treatment of NSTI
and sepsis patients.
The partners of SysmedIBD are working towards a systems medicine approach of Inflammatory Bowel Disease.
Mathematical experts develop models describing the process of chronic inflammation starting with one central
pathway present in each cell type, the NF-kb pathway. Biologists with expertise in animal models generate
data to validate the mathematical models and samples from patients are used to match experimental data to
patient cohorts. Within the consortium, specialists in chemical computing will suggest potential drugs to treat
LifeGlimmer provides advanced statistical methods in differential expression analysis of time series RNA
sequencing. We implement an interactive database that integrates the data produced during the project and allows
users to perform differential expression analysis with their own data. Health medical records from follow-up
cohorts are digitalised, anonymised and mined with specific text-mining tools to reveal information that was not
systematically collected before. We investigate new characterisation of patients with those new data using
machine learning algorithms.
PerICo is a multi-partner European Training Network under the European Union programme Horizon 2020.
PerICo aims at uncovering how peroxisomes, important cellular organelles, participate in the intricate
cellular interaction and signalling network. In light of the current understanding of the central role
of peroxisomes in a variety of metabolic diseases, cancer and aging – this timely research programme
will benefit society. PerICo trains a new generation of highly-qualified ESRs (Early stage researchers)
focusing on the identification and functional characterization of peroxisomal membrane contact-sites and
Research at LifeGlimmer will specifically contribute to the model-driven discovery and network modelling of
TranSYS, coordinated by K. Van Steen (KU Leuven), will recruit 15 ESRs (Early Stage Researchers) to highly skilled
jobs in the new area of Systems Health developing tools and approaches to exploit large and complex datasets, to advance
Precision (Personalised) Medicine in several disease areas. The training programme and experience of different international
research environments cuts across traditional data and life sciences silos. The emphasis on translational research will
support new collaborations between academics and the pharma and health analytics sectors. Our ESR projects will advance the
state of the art on biomarker discovery, improve understanding of disease-specific molecular mechanism and target
identification for optimal diagnostics, disease risk and treatment management, refine data generation and their management
(including warehousing, disease specific and standardised approaches for data processing, visualisation and model development)
leading to improved clinical study design, clinical sampling and more targeted therapeutics. This ETN (European Training Network)
will internationalise participants, and leverage EC (European Commission) and industry sponsorship, to structure and expand the
unique training programme and advance emerging research areas, combining wet-lab, clinical and Big Data resources with
computational and modelling know-how.
Focus of LifeGlimmer is on developing and demonstrating data mining and A.I. tools to better understand patient
heterogeneity and assist patient stratification.
The overarching aim of IBISBA is to create a coordinated network of research infrastructure facilities and thus
provide a novel and timely response to the main challenges that are currently hampering the development of
industrial biotechnology (IB) as a key enabling technology of Europe’s bioeconomy.
Building upon its expertise in large-scale functional annotation, analysis and integration of heterogeneous data sets
(in particular omics), semantic technologies and metabolic modeling, Lifeglimmer participates in various WPs, in
particular on the development and deployment of computational workflows
for biocatalyst and process design, semantic analysis and integration of data using a decision support system.
In silico analysis of algal metabolism for industrial application is often a challenge due to the fact
that algae are in general less understood in the research field than plants or bacteria. In the SPLASH project
LifeGlimmer is involved in genome-scale metabolic modelling and analysis of the green microalga Botryococcus
braunii which is capable of overproducing long-chain hydrocarbons, botryococcenes, and exopolysaccharides etc.
Microalgae are promising new renewable feedstocks for chemicals and plastics. They can be cultivated on non-arable
land and can yield valuable compounds for chemical industries. If microcalgae can be sustainably utilized at an
industrial scale this will provide new opportunities for decreased dependency on fossil feedstocks and potentially
contribute to climate mitigation and reduced pressure on land resources.
The Marie Curie Initial Training Network PerFuMe (PERoxisome Formation, Function, Metabolism)
is an interdisciplinary and intersectoral initial stage training network (ITN) at the interface of
medicine, plant and fungal biology, devoted to understanding the principles of peroxisome biology.
EmPowerPutida answers current market needs by the thorough application of Synthetic Biology.
This industrially driven project will pave the way to the production of so far non-accessible biological compounds.
Therefore, the lifestyle of Pseudomonas putida, a bacterium with remarkable metabolic endowment and stress tolerance, will be engineered.
The guiding idea is to embed optimised biosynthetic pathways into an optimised chassis offering new functionalities.
We have the ambition to establish Pseudomonas putida as the major European platform of choice for industrial, large-scale whole-cell
biocatalysis directed at the sustainable biotechnological production of bulk and specialty chemicals.
As part of the project LifeGlimmer engages in data management and dissemination activities. Intensive interaction with relevant stakeholder groups
contributes to the public debate on Synthetic Biology and maximises the socio-economic impact of the project.
The Chromatin3D project explores the molecular, cellular and systems level biology of chromatin through
the cross-disciplinary expertise of academic and non-academic partners. Chromatin is a key component of the
cell nucleus and the destabilization of regulatory mechanisms that act on the chromatin structure are implicated
in pathologies, such as cancer. The aim of this project is to gain mechanistic insight of the dynamic
assembly and modification of chromatin during developmental processes and its deregulation during the onset of disease.
The aim of NORM-SYS is to incorporate established community standards for data and in silico
models in systems biology into generalized concepts that enable easy communication between expert groups
and standardization organisations.