Gnosis is a common Greek noun for Knowledge (γνῶσις, gnôsis, f.). Our mission is to provide the knowledge to researchers and clinicians to understand the secrets of diseases from the analysis and use of biomedical "Big Data". We provide solutions using deep learning to enable healthcare providers to improve clinical outcomes, clinical researchers to understand the information from Next Generation Sequencing (NGS) data and academics to gain insights into the biological data.  


Our team comprises of engineers, visual design specialists, data scientists, biologists and artificial intelligence experts with years of expertise in statistical genetics, bioinformatics and clinical informatics.


The fusion of genetic, genomic and clinical data has been put in service to improve the patient outcomes.  Clinicians and researchers need improved methods, tools, and training to generate, analyze, and query data effectively. We provide professional consultancy, guidance and advice for handling and understanding better biomedical data.


Data-driven analysis Solutions

Explore our solutions for detailed analyses of the genome, transcriptome, microbiome and miRNAs. Through​ strategy and roadmap, we deliver business value to gain deeper and more accurate insights by putting in place an analytics approach and solution.

NGS Workshops

We organise introductory and advanced courses to get a deeper understanding in Next-Generation Sequencing (NGS).

Custom on-site bioinformatics Courses

Get trained by experts with proven record of academic and industrial experience. We customise the course, according to your requirements and create a personalised training package that will be conducted on your site. Start your experiment and by the end of the week you will be able to analyse your data.

With innovative approaches we are making sense of big data in health research.

Project Areas

Digital Health

Digital Health

Systems Biology

Systems Biology

Systems Medicine

Systems Medicine

Statistical Genetics

Statistical Genetics


Androniki Menelaou

Androniki Menelaou, PhD

Statistical Genetics

Androniki has studied statistics and obtained a PhD in Statistical Genetics from the University of Oxford. She has developed a novel method for imputing multi-allelic variants from sequencing data. Her software, MVNcall, has been used in the 1000 Genomes project. She is now working in different initiatives in the private sector as a senior data scientist and advisor.

Emmanouela Repapi

Emmanouela Repapi, PhD

Statistical Bioinformatics

Emmanouela is a statistical bioinformatician in the Computational Biology Research Group of the Weatherall Institute of Molecular Medicine, University of Oxford. Currently, her expertise is in the analysis of RNA Sequencing data, including single-cell analysis. She completed her DPhil at the Ludwig Institute for Cancer Research at the University of Oxford working on the identification and analysis of single nucleotide polymorphisms (SNPs) that affect cancer in humans. She was involved in numerous projects, working with clinical and genetic data of different types of cancer. Prior to her PhD, she worked as a training fellow in Genetic Epidemiology at the University of Leicester conducting a meta-analysis of Genome Wide Association Studies (GWAS) for pulmonary function.

Chrysanti Ainali

Chrysanthi Ainali, PhD

Clinical Bioinformatics

An expert in machine learning, and data integration. Chrysanthi has a background in informatics and received her PhD in Bioinformatics from King's College London. Her research focused on development and use of machine learning algorithms targeting in data integration, disease stratification, network inference and biomarker discovery. She contributed to over 20 research papers.  She previously worked as a scientist for a global biotechnology company, where she fostered and drove the bioinformatics component of design and development of genetic tests using Next Generation Sequencing.

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Our customers and partners include Leading Pharma, Biotech and Diagnostic Companies, and Renowned Research Institutions.




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