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When it comes to data science and the successful fruition of a project, diverse knowledge is a frequent prerequisite. Bioinformatics spans multi-disciplines with chemistry and biology embraced through Physics.  At the core of Physics lies math and without math,  insightful analytics would remain very much in the dark.

At the core of Multicore’s beating heart lies a deep understanding of math. It is through this understanding that we are able to antagonise,manipulate and extract the previously unseen and disconnected.

Image by Conny Schneider


Topological Data Analysis (TDA) is one of the advanced tools available in our analysis toolbox. 


TDA is particularly relevant when other more traditional approaches have failed.  TDA extracts information based upon the geometric structure of data to enable hypothesis generation.  Moreover, the quality of TDA results can be evaluated via Persistent Homology diagrams, serving as feature selection tools and signal-to-noise filters.

When applied in conjunction with machine learning methods, TDA-PH delivers data-driven models that statistically can outperform traditional cluster-based  approaches.     

We strive to push the boundaries when it comes to making use of current technologies and methods to progress data analytics and ultimately data science.

"Data has shape, and shape matters."


Image by Conny Schneider


The below graphics reveal a few examples of how visual connections can help unlock previously unobserved relationships from within complex data.

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