Qlucore Newsletter: Build classification models without programming skills

With Qlucore Omics Explorer you can without programming skills test and build machine learning classifiers. Qlucore Omics Explorer (QOE), contains built in machine learning functionality, available since 2016, which enables users without any need for programming to build classifiers and predict outcomes for a wide range of Omics data. Classifiers are built using frameworks such as Boosted trees, Support Vector Machines, Random trees, and kNN. A cross validation scheme enables integrated validation in addition to using an external data set. When a classifier is created, it can be used to classify a sample or samples in a second data set.

Classification is also useful when looking for new therapeutic targets and biomarkers, as it often delivers shortlists of variables that collectively can correctly predict the class of new samples with an estimated accuracy. For example, the class annotation can be response vs. nonresponse or case vs. control.  

If you have a need for companion diagnostics solutions, Qlucore has further enhanced and integrated machine learning functionality into its solutions – Qlucore Insights and Qlucore Diagnostics.  

Benefits: 

1. No programming required. 
2. Build classifiers using several different frameworks such as Random trees or SVM. 
3. Easy and fast. 

Watch webinar or test Qlucore Omics Explorer with a free trial. Find out more about companion and precision diagnostics by contacting us.

Register for the upcoming webinar:

Qlucore Omics Explorer: Basic Training

April 24th, 2024

14:00 CET

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