Automated Data Exploration.
AutoDiscovery is an intelligent automated exploratory data analysis software that helps biomed researchers unveiling complex relationships hidden in the data files of scientific experiments and clinical trials.
For Researchers. By Researchers.
With the outbreak of the pandemic in 2020, the IdiPAZ Innate Immune Response group, led by Dr. Eduardo López-Collazo, decided to start a project focusing on the immune system of COVID-19 patients.
In collaboration with the emergency service of Hospital La Paz (Madrid, Spain), we began to collect samples from patients as soon as they arrived at the emergency admission.
The main objective of the work was to recognize early markers of the disease that are associated with the final evolution of the patient.
The main objective was to evaluate the potential associations between clinical/epidemiological data and genetical microbial features in a cohort of patients under mechani-cal ventilation and isolation of Staphylococcus aureus in the respiratory tract.
Butler Scientifics is a proud member of Advance(CAT) platform which gathers the efforts and expertise of 18 catalan institutions, both public and private, to speed up the conversion of advanced therapies from the idea to the product.
This work has been developed with the support of ACCIÓ (Agència per la Competitivitat de l'Empresa; Generalitat de Catalunya) under the Catalonian ERDF operational program (European Regional Development Fund) 2014-2020.
Customers & Collaborators
What's In It For Me?
AutoDiscovery automatically evaluates the proper statistical tests to assess the relationships between every combination of variables at every individual subset of your data.
x10 times faster, x200 times wider analysis.
Cause-effect potential, false discovery rates, small-complex data, groups and treatments and traceability of results are common biomed research needs specifically covered by AutoDiscovery
AutoDiscovery is targeted to Principal Investigators with very little time for data analysis and limited statistical knowledge focused on productive, high impact research.