Deeptaxim: Comprehensive classification analysis for taxonomic datasets using image-based deep-learning models

doi:10.1016/j.compbiolchem.2026.109063

Deeptaxim: Comprehensive classification analysis for taxonomic datasets using image-based deep-learning models

2026-04-20

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U. Gülfem Elgün Çiftcioğlu *

Ö

Özkan Ufuk Nalbantoğlu

DOI：10.1016/j.compbiolchem.2026.109063

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Abstract

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• Proposes Deeptaxim that transforms microbiome data into images via taxonomic cladograms. • Deeptaxim, a comprehensive framework that applies DL models for disease classification. • Utilizes CNN-based Autoencoder, U-Net, and GAN models for deep feature learning. • Applies transfer learning across diverse disease datasets to enhance generalization and robustness. • Offers a biologically informed and adaptable solution for microbiome-based health assessment.

Keywords:

Deeptaxim

microbiome data

taxonomic cladograms

deep learning

disease classification

Deeptaxim: Comprehensive classification analysis for taxonomic datasets using image-based deep-learning models

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