Our Proprietary Solutions

Innovative frameworks, predictive models and scientific tools for next-generation research

O2Pmgen

The Omics to Phenomics model generator

AutoML framework that learns patterns of biomarker combinations in omics datasets. Builds optimal predictive models based on small bespoke biomarker panels using an evolution-inspired algorithm.

BMfinder

The Biomarker Finder

Systematically searches for biomarkers with statistical significance on large datasets. Uses smart hypothesis testing, ranks candidates and builds a single biomarker predictor.

CanTAP

Cancer Transcriptomics Assessment Platform

Predicts breast, renal, and lung cancer prognostics based on tumour gene expression profiles (RUO). Uses machine-learning–derived models based on key combinations of biomarkers.

MDeval

Model Development Evaluator

Framework for comprehensive predictive model evaluation using multiple performance metrics and ROC analysis. Integrates the proprietary MSDA methodology for model ranking, discrimination, and selection.

EpiDym

Epidemiology Dynamic Estimator

Framework for developing ODE-based SIR epidemiological models from demographic data and known disease parameters. Uses a proprietary hybrid machine-learning approach to calibrate model parameters and improve predictive accuracy.

CalEST

Caloric Estimator for Sports Training

A framework for estimating exercise energy expenditure required to achieve time-dependent fitness goals. Uses a machine learning–based calibration approach on an ODE model to predict inter-individual variability in metabolic response and adaptation dynamics.

Empowering Biotech and Biomedical Research instituitions with state-of-the-art predictive modelling and bioinformatics solutions.