Machine learning models for breast cancer outcome predictions and mRNA gene array exploratory data analysis Files are 2 python script files and one PowerPoint file with presentation of the main findings
This is my graduation project from NOD Python coding bootcamp for data analysis and machine learning (https://www.nod-coding.com/).
Datasets (METABRIC study) were taken from cBioportal repository where authors deposit their data prior or at the time of publication. Data were initially published in these articles: Pereira B et al. The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nat Commun. 2016 May 10;7:11479.
Rueda OM et al., Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups. Nature. 2019 Mar;567(7748):399-404.