Analysis of Gene Expression Data


Infocomm - Big Data, Data Analytics, Data Mining & Data Visualisation
Healthcare - Telehealth, Medical Software & Imaging
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Omics technologies are advancing rapidly and dominating discovery-based studies for biomarkers. These methods can deliver above 10,000 readings per sample, thus generating a large amount of data, which can be overwhelming for the non-data specialist researcher.

A Danish biotechnology SME offers in-depth data analysis of gene expression data with the aim to make advanced data analysis easily accessible for all sizes of enterprises and researchers, fueling and focusing the search for new biomarkers for diseases and better treatments.

Currently in beta testing, the company seeks new collaboration partners from Europe and North America in terms of companies or organisations within the field of biotechnology or biomedicine that provide data on either gene or protein expressions. The SME is interested in commercial agreements with technical assistance or research agreements.


Based on the client data upload, the pre-process will filter, transform, normalise and distribute the assessment. This leads to unique identification based on parameter estimation and filtration. Estimation and visualisation of the variance will be carried out leading to a statistical test including P-value correction and box-plot visualisation. The company has engaged in international collaboration e.g. in the Swedish pharma industry and is furthermore a partner in a Horizon 2020 project.

The company is now looking for a partnering company or organisation such as a research institution or university within the field of biotechnology or biomedicine that provides data on either gene or protein expressions of human or animal models that need to be analysed. The company has started the final beta testing prior to launch and therefore feedback for product optimisation is a necessity. Publication of the project would be highly appreciated.

This cooperation is foreseen under a commercial agreement with technical assistance. Alternatively, companies or organisations intending to apply for funds for an ongoing project using the data could benefit for a joint application under a research agreement.


The technology provided uses state-of-the-art biostatistical methods and machine learning to offer deep data analysis for studies conducted in the field of biotechnology and biomedicine. In particular, it will be of great benefit for the analysis of gene or protein expressions in the search for new biomarkers for diseases and treatments.



The services offered provides the client with deep insight, and an advanced analysis of gene expression data. The major part of this SME's business is based on its pipeline of data that can automate much of the process during data analysis by using the right tests for decision making.

The programming behind the technology has been developed in-house but is based on state-of-the-art biostatistical methods and machine learning. To achieve deeper insight, the company uses several machine learning methods including several clustering methods like K-means. This enables discovery of subgroups and sub-studies within a single study, thus enabling expansion of the analyses and potential discovery of personalised medicine-based features.

The company continuously strives to improve the analysis method currently used in conventional expression data analysis. This is achieved by using advanced biostatistical and statistical methods to improve statistical accuracy. For partners, the company strives to provide an economical advantage in choosing its services, both regarding the content of the analysis as well as the duration normally required to conduct this kind of analysis. In this way the company can contribute to better and faster analysis for the biotechnology and medical industry.

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