Methodology developed by Sbider

Methodology

Underpinning our medical and biological work are new methodologies in statistics, mathematics, and computer science. Sbider's experts are at the forefront of using in applications the most recent developments in these fields, and in developing new methods inspired by challenging applications.

Mathematical modelling

Our modelling work includes applications in neuroscience, systems biology, epidemiology and phylodynamics.

Vorticity field ω monitored inside a follicular environment using a computational fluid dynamics model to describe fluid movement and enable the design of new flow-informed needle features.

Inference and numerics

For a model to be realistic it must be calibrated using data. Sbider develops new inference algorithms to facilitate this process.

An illustrationof the individual forward filtering backward sampling algorithm.

Machine learning and AI

Machine learning methods discover patterns in data. We develop such approaches for predicting and extracting signals from data.

Comparison of percentages of errors for the derivation and validation sets in an algorithm for predicting phenotype from genomic data.