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MAINE: a web tool for multi-omics feature selection and rule-based data exploration
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 fe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896606/ https://www.ncbi.nlm.nih.gov/pubmed/34954788 http://dx.doi.org/10.1093/bioinformatics/btab862 |
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author | Gruca, Aleksandra Henzel, Joanna Kostorz, Iwona Stęclik, Tomasz Wróbel, Łukasz Sikora, Marek |
author_facet | Gruca, Aleksandra Henzel, Joanna Kostorz, Iwona Stęclik, Tomasz Wróbel, Łukasz Sikora, Marek |
author_sort | Gruca, Aleksandra |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8896606 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-88966062022-03-07 MAINE: a web tool for multi-omics feature selection and rule-based data exploration Gruca, Aleksandra Henzel, Joanna Kostorz, Iwona Stęclik, Tomasz Wróbel, Łukasz Sikora, Marek Bioinformatics Applications Notes 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. Oxford University Press 2021-12-25 /pmc/articles/PMC8896606/ /pubmed/34954788 http://dx.doi.org/10.1093/bioinformatics/btab862 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Gruca, Aleksandra Henzel, Joanna Kostorz, Iwona Stęclik, Tomasz Wróbel, Łukasz Sikora, Marek MAINE: a web tool for multi-omics feature selection and rule-based data exploration |
title | MAINE: a web tool for multi-omics feature selection and rule-based data exploration |
title_full | MAINE: a web tool for multi-omics feature selection and rule-based data exploration |
title_fullStr | MAINE: a web tool for multi-omics feature selection and rule-based data exploration |
title_full_unstemmed | MAINE: a web tool for multi-omics feature selection and rule-based data exploration |
title_short | MAINE: a web tool for multi-omics feature selection and rule-based data exploration |
title_sort | maine: a web tool for multi-omics feature selection and rule-based data exploration |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896606/ https://www.ncbi.nlm.nih.gov/pubmed/34954788 http://dx.doi.org/10.1093/bioinformatics/btab862 |
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