Bioenhancer Systems is a UK-based R&D private company that focuses on developing and deploying novel predictive models and user-friendly bioinformatics tools for the biomedical/scientific community.
We are particularly interested in developing solutions for tackling complex biological problems such as cancer with a holistic view of biomarker discovery, diagnostics, prognostics and therapy assessment.
We believe that tools that predict phenotypical information from complex “omics” data in biological systems can transform the current medical approaches and enable accurate diagnostics, prognostics and effective interventions.
Our technology (models and algorithms) can be used as tools under a Software as a Service (SaaS) business model. We offer personalised plans based on a subscription fee. The services can be made available as a MICROSERVICE via API or under our PLATFORMS . We also are open to collaborative research projects and joint ventures for technology development.
Our solutions are tailored to biological systems and thoroughly tested to empower our users with high-quality standards of performance.
Bioenhancer Systems has substantial experience in developing and deploying automated bioinformatics solutions and predictive models for biological systems that encompass the following frameworks:
Bioenhancer Systems relies on state-of-the-art proprietary technology for optimal predictive model generation biomarkers from “omics” data (e.g O2Pmgen), developed by the founder ( Dr Ricardo J. Pais).
Ricardo J. Pais is a senior bioinformatician and data scientist that works in the UK biomedical industry. Ricardo holds a PhD degree in Systems biology, gathering more than 15 years of experience in mathematical modelling of physiological systems and software development. His work is focused on the development of algorithms and mathematical models for disease diagnostics, prognostics and personalized medicine. Ricardo is also an active researcher and an invited professor of bioinformatics at EGAS MONIZ SCHOOL OF HEALTH & SCIENCE (Portugal).
User-friendly and code-free AI-driven platform for automated generation of predictive models from "omics" data (e.g. transcriptomics and proteomics). The platform uses an "in-house" developed Evolutionary/genetic algorithm (O2Pmgen) that enables building models with optimal sensitivity and specificity (Filho et al 2023) . Also enables users to analyse models performance and make predictions on new data (Learn more, register and login)
The Costumisable Hosting Application for Model Predictions. Relies on an “in-house” developed Python Framework that facilitates the integration and customisation of different types of Models (e.g. ML classifiers, ODE, logical, etc). Ideal for a simple generation of model predictions online. The Framework includes a simple Graphical User Interface and secure user login ( for more information, please contact us )
If you wish to develop a tailor-made model or algorithm for your biological system, we may also offer a solution.