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ACE: A Workbench using Evolutionary Genetic Algorithms for analysing association in TCGA Data

By Alan Gilmore, Kienan I Savage, Paul F O'Reilly, Aideen C Roddy, Philip D. Dunne, Mark Lawler, Simon S McDade, David J. Waugh, Darragh G McArt

Posted 01 Mar 2018
bioRxiv DOI: 10.1101/274175

Modern methods in generating molecular data have dramatically scaled in recent years, allowing researchers to efficiently acquire large volumes of information. However, this has increased the challenge of recognising interesting patterns within the data. Atlas Correlation Explorer (ACE) is a user-friendly workbench for seeking associations between attributes in the cancer genome atlas (TCGA) database. It allows any combination of clinical and genomic data streams to be selected for searching, and highlights significant correlations within the chosen data. It is based on an evolutionary algorithm which is capable of producing results for very large searches in a short time.

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