Customer-oriented in scientific consulting, contract research and customised training, LifeGlimmer provides you with efficient means to outsource your bioinformatics
and systems biology needs. Our experts work in close collaboration with you, providing tailor-made solutions in a result-driven manner, whilst remaining flexible with
preferred formats and workflows.
Let our biological data analysts work for you. Discover new links in complex datasets, visualise and understand dynamic networks, and predict systems behaviour.
A thorough understanding of any biological system requires not only the knowledge of which genes, proteins or metabolites are
responding to a stimulus but how the network of these molecules interact and regulate each other in biological pathways.
Pathway analysis can be applied to interpret omics data in a broad variety of experimental and clinical contexts. In medical
applications we can gain insights into the molecular basis of disease by comparing healthy and diseased tissue or investigating
the response to drug treatments. In synthetic biology, genome engineering can be used to introduce new traits into bacteria and
the effect of these on a pathway level can be explored.
LifeGlimmer combines a variety of analytical algorithms that utilise data from publicly available bioinformatics resources for pathway
analysis in these application areas.
LifeGlimmer’s solutions include:
- Gene Set Enrichment Analysis using a variety of Gene Sets, e.g. Gene Ontology and MSigDB Broad Institute
- Use of topological methods implemented in R for investigating interactions between differentially expressed genes
- Weighted gene co-expression network analysis to search for correlation patterns in RNASeq data
- Implementation of Cytoscape apps (e.g. SyncVis) for visualizing omics data on molecular pathways
Mobile apps are playing an ever increasing role in our everyday life, and the health area is not an exception. On the contrary:
Apps are an integral part in personalized medicine and will become even more so in the near future. With the benefit of being always
connected to the cloud, independent of location and time, apps can constantly monitor a user’s well-being and improve their quality of life.
This effect is enhanced when using apps in combination with wearable devices, like sensors.
LifeGlimmer’s solutions in this area include:
- Apps for clinical decision support (as developed for the INFECT project)
- Apps for personalized medicine
- Apps for citizen/patient adherence
- Development of native Android apps
- Experience with the Unity (game) engine for streamlined cross-platform software development:
- mobile (e.g. iOS or Android)
- stationary (e.g. web browser or VR/AR environments)
Scientific project management
Having an outstanding expertise in the management of international research projects in the life sciences
(in particular in the systems biology/medicine sector), our services comprise the whole project pipeline from grant preparation
to project management and financial monitoring.
Capturing complex biological data as clear, accurate and understandable network representations that license their proper examination, communication and
As part of the SysmedIBD project LifeGlimmer has implemented
a text mining pipeline that scans Electronic Health Records (EHRs) for predictors of patient symptoms. We incorporate all steps from
digitalization, de-identification and data cleaning of documents to classification of patients with machine learning and prediction of disease severity and outcome.
- Model-assisted integration of metabolomics, proteomics, and transcriptomics expression
- Combining data of different types, from different assays and from different sources into workable models that allow for meta-analysis and holistic studies.
- Genome-scale metabolic network reconstruction
- Metabolic flux balance and variability analysis
- Model-based gene knockout prediction
- Dynamic modeling of signalling and metabolic pathways for understanding, targeting and optimising dynamic network behaviour
- Predictive modeling for biomarkers, physiological effects, and clinical outcomes
- Unveiling hidden links and correlations within and among your datasets through advanced biostatistics
- Extracting information via text and data mining and linking these data with bioinformatics tools
In case you require training in bioinformatics-related tools and/or specific programming languages, our experienced team
of computational biologists will be happy to help you out:
- Shell scripting (free sample)
- R Shiny
Your partner in Germany, in the EU and worldwide