ArticleBioinformatics (Oxford, England)2023
mb-PHENIX: diffusion and supervised uniform manifold approximation for denoizing microbiota data.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Digital modeling of metformin and diet interactions on gut-microbiota metabolism in prediabetic patients.Computational and structural biotechnology journal · 2026Article
- The role of the gut microbiota and its metabolites: a new predictor in diabetes and its complications.European journal of medical research · 2025Review
- Article
- Effect of metformin and metformin/linagliptin on gut microbiota in patients with prediabetes.Scientific reports · 2024Article
- Lightweight Gramian Angular Field classification for edge internet of energy applications.Cluster computing · 2023Article
- Dysbiosis signatures of gut microbiota and the progression of type 2 diabetes: a machine learning approach in a Mexican cohort.Frontiers in endocrinology · 2023Article
- A network perspective on the ecology of gut microbiota and progression of type 2 diabetes: Linkages to keystone taxa in a Mexican cohort.Frontiers in endocrinology · 2023Article
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Authors and funding
8 authors.
Funding
Abstract
motivationMicrobiota data encounters challenges arising from technical noise and the curse of dimensionality, which affect the reliability of scientific findings. Furthermore, abundance matrices exhibit a zero-inflated distribution due to biological and technical influences. Consequently, there is a growing demand for advanced algorithms that can effectively recover missing taxa while also considering the preservation of data structure.
resultsWe present mb-PHENIX, an open-source algorithm developed in Python that recovers taxa abundances from the noisy and sparse microbiota data. Our method infers the missing information of count matrix (in 16S microbiota and shotgun studies) by applying imputation via diffusion with supervised Uniform Manifold Approximation Projection (sUMAP) space as initialization. Our hybrid machine learning approach allows to denoise microbiota data, revealing differential abundance microbes among study groups where traditional abundance analysis fails. AVAILABILITY AND IMPLEMENTATION: The mb-PHENIX algorithm is available at https://github.com/resendislab/mb-PHENIX. An easy-to-use implementation is available on Google Colab (see GitHub).
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