DOI: 10.29007/8xwn
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Ranking Variable Combinations to Characterize Breast Cancer Subtypes using the IBIF-RF Metric

Abstract: Gene interactions play a fundamental role in the proneness to cancer. However, detect- ing and ranking these interactions is a complex problem due to the high dimensionality of genomic data. Hence, we aim to find patterns composed of multiple features to molecularly characterize breast cancer subtypes from the integration of different omics datasets using a data mining approach. To retrieve biological understanding from these computational results, we developed IBIF-RF (Importance Between Interactive Features … Show more

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