Our Services

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.

Pathway analysis

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

Text mining

Text remains one of the richest sources of information. The purpose of text mining is to convert unstructured descriptive text into a machine-readable format that can be used for downstream analysis. LifeGlimmer uses text mining techniques to automatically extract information from medical records and the abstracts of scientific papers. These data can then be incorporated into a variety of applications, such as defining parameters for patient stratification and the identification of biomarkers.

As part of the SysmedIBD project, LifeGlimmer has implemented a text mining pipeline that scans Electronic Health Records (EHRs) to find predictors of patient symptoms and disease courses.

LifeGlimmer’s solutions in this area include:

  • Digitalization of the text
  • De-identification of the text (with removal of protected health information)
  • Data cleaning and pre-processing
  • Creation of different types of datasets specific for the downstream analyses
  • Clustering of patients
  • Prediction of patient outcomes

Decision Support Systems (DSSs)

With the exponential increase and variety of health-related data, the methods to combine and make practical use of these data become ever more complex. But this also means that resulting applications have the potential to be more accurate and more powerful than ever. Decision support systems agglomerate such data to create adequate and easy-to-use tools that facilitate decision-making processes.

LifeGlimmer focuses on medical DSSs and offers the following:

  • Development of disease-specific DSSs that help clinical decision-makers to more accurately treat their patients
  • Inclusion of feedback from our partners and users to adapt tailored customizations
  • Deployment of DSSs to desktop and mobile solutions

Data integration and management

There is an increasing amount and diversity of medical and biological data available in public databases. Valuable data can also be siloed in proprietary databases (for example at hospitals or Pharma companies) and use legacy formats that require standardisation before they can be integrated with other data types. Moreover new types of data, e.g. data from sensors and wearables are increasingly being collected. Analyzing and exploring any of these data types alone has only limited value. LifeGlimmer addresses the challenge of converting and integrating these data into a single framework in order to gain a better understanding of biological complexity.

To get the best value from data it needs to be stored and managed in a way that ensures it can be easily understood and shared between researchers in multiple institutions across geographical boundaries. LifeGlimmer employs strategies to ensure data are Findable, Accessible, Interoperable and Reusable (FAIR principle). Standardisation of data facilitates its reuse and integration with other data sources.

LifeGlimmer’s solutions include:

  • Harmonisation of data from multiple sources to use shared terminologies e.g. ICD-10 terms for disease, Human Phenotype Ontology (HPO)
  • Conversion of data into formats for sharing, e.g. XML, RDF and Systems Biology Markup Language (SBML)
  • Liaison with researchers to prepare experimental and computational modeling data and associated metadata for sharing via platforms such as FAIRDOMHub
  • Exploiting semantic web technologies to create extensible and flexible databases for biological data

App development

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.

Data visualization

Capturing complex biological data as clear, accurate and understandable network representations that license their proper examination, communication and understanding.

Computational modeling

  • 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

Knowledge discovery

  • 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:

  • R
  • Python
  • Java
  • Perl
  • CSS/JavaScript
  • Shell scripting (free sample)
  • ...
  • Cytoscape
  • R Shiny
  • Android
  • Unity
  • ...

Your partner in Germany, in the EU and worldwide

If you are interested in our scientific partnering, consultancy or training solutions, please This email address is being protected from spambots. You need JavaScript enabled to view it. us!