Article

OmicSelector: automatic feature selection and deep learning modeling for omic experiments

2022-06-02

Abstract excerpt

<h4>ABSTRACT</h4> A crucial phase of modern biomarker discovery studies is selecting the most promising features from high-throughput screening assays. Here, we present the OmicSelector - Docker-based web application and R package that facilitates the analysis of such experiments. OmicSelector provides a consistent and overfitting-resilient pipeline that integrates 94 feature selection approaches based on 25 dist...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 331e43b8-a31c-500d-a303-e54d6e494068
DOI: 10.1101/2022.06.01.494299

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

OmicSelector: automatic feature selection and deep learning modeling for omic experimentsDOI 10.1101/2022.06.01.494299Read

Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer DiagnosticsSemantic proximity Read

A Benchmarking Study of Feature Screening Approaches Across Omics Classification SettingsSemantic proximity Read

Machine Learning Approaches for Identification of Potential Biomarkers from Cancer Omics DataSemantic proximity Read

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical dataSemantic proximity Read

Deep learning–driven multi-omics analysis: enhancing cancer diagnostics and therapeuticsSemantic proximity Read

Multi-omics and deep learning provide a multifaceted view of cancerSemantic proximity Read

playOmics: A multi-omics pipeline for interpretable predictions and biomarker discoverySemantic proximity Read

omicML: An Integrative Bioinformatics and Machine Learning Framework for Transcriptomic Biomarker IdentificationSemantic proximity Read

Identifying multi-omics biomarkers for ovarian cancer survival estimationSemantic proximity Read

DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics dataSemantic proximity Read

Transparent exploration of machine learning for biomarker discovery from proteomics and omics dataSemantic proximity Read

IOBR: Multi-omics Immuno-Oncology Biological Research to decode tumor microenvironment and signaturesSemantic proximity Read