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MAINE: a web tool for multi-omics feature selection and rule-based data exploration

Aleksandra Gruca, Joanna Henzel, I. Kostorz, Tomasz Stęclik, Łukasz Wróbel, Marek Sikora

2021Bioinformatics11 citationsDOIOpen Access PDF

Abstract

SUMMARY: Patient multi-omics datasets are often characterized by a high dimensionality; however, usually only a small fraction of the features is informative, that is change in their value is directly related to the disease outcome or patient survival. In medical sciences, in addition to a robust feature selection procedure, the ability to discover human-readable patterns in the analyzed data is also desirable. To address this need, we created MAINE-Multi-omics Analysis and Exploration. The unique functionality of MAINE is the ability to discover multidimensional dependencies between the selected multi-omics features and event outcome prediction as well as patient survival probability. Learned patterns are visualized in the form of interpretable decision/survival trees and rules. AVAILABILITY AND IMPLEMENTATION: MAINE is freely available at maine.ibemag.pl as an online web application. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Topics & Concepts

Feature selectionOmicsComputer scienceData miningOutcome (game theory)Feature (linguistics)Selection (genetic algorithm)Dimensionality reductionMachine learningData scienceArtificial intelligenceBioinformaticsBiologyMathematicsLinguisticsMathematical economicsPhilosophyBioinformatics and Genomic NetworksFerroptosis and cancer prognosisGene expression and cancer classification
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