Science

Biomarker analytics describes the laboratory and computational analysis of biomarkers. Insilicos concentrates on techniques that are data-intensive, so that the scale of the data itself becomes a challenge. Such data-rich experiments can produce deep insights into biological systems, in an approach that is often called systems biology.

Insilicos uses advanced machine learning approaches to identify, characterize, and measure biomarkers. We concentrate on data-intensive techniques, primarily genomics and proteomics.

Machine learning from our perspective embraces a range of statistical, search, and pattern-recognition approaches to build automated systems for characterizing or classifying data. We have developed leading expertise in the range of techniques necessary for biomarker analytics, including data mining, pattern recognition, linear and non-linear modeling, variable selection, ensemble learning, cloud computing, and GPGPU computing.

Diagnostics are our primary research goal. PreClue, our diagnostic for cardiovascular disease, is currently undergoing a clinical trial.

For more information, please refer to papers, posters, and presentations related to Insilicos' work.