Phylo-Spec: a phylogeny-fusion deep learning model advances microbiome status identification.

ABSTRACT: The human microbiome is crucial for health regulation and disease progression, presenting a valuable opportunity for health state classification. Traditional microbiome-based classification relies on pre-trained machine learning (ML) or deep learning (DL) models, which typically focus on microbial distribution patterns, neglecting the underlying relationships between microbes. As a result, model performance can be significantly affected by data sparsity, misclassified features, or incomplete microbial profiles. To overcome these challenges, we introduce Phylo-Spec, a phylogeny-driven deep learning algorithm that integrates multi-aspect microbial information for improved status recognition. Phylo-Spec fuses convolutional features of microbes within a phylogenetic hierarchy via a bottom-up i

SUBMITTER: Zhang J 

PROVIDER: S-EPMC12710343 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature