parafac4microbiome: exploratory analysis of longitudinal microbiome data using parallel factor analysis
ABSTRACT Studies investigating microbial temporal dynamics are increasingly common, leveraging longitudinal designs that collect microbial abundance data across multiple time points from the same subjects. Traditional exploratory approaches like principal component analysis fail to fully utilize thi...
Saved in:
| Main Authors: | G. R. van der Ploeg, J. A. Westerhuis, A. Heintz-Buschart, A. K. Smilde |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Society for Microbiology
2025-06-01
|
| Series: | mSystems |
| Subjects: | |
| Online Access: | https://journals.asm.org/doi/10.1128/msystems.00472-25 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Unmasking Machine Learning With Tensor Decomposition: An Illustrative Example for Media and Communication Researchers
by: Yu Won Oh, et al.
Published: (2025-04-01) -
MATHEMATICAL MODELS OF MULTIDIMENSIONAL DATA
by: V. S. Mukha
Published: (2019-06-01) -
Tensor Signal Modeling and Channel Estimation for Reconfigurable Intelligent Surface-Assisted Full-Duplex MIMO
by: Alexander James Fernandes, et al.
Published: (2024-01-01) -
A Two-Level Parallel Incremental Tensor Tucker Decomposition Method with Multi-Mode Growth (TPITTD-MG)
by: Yajian Zhou, et al.
Published: (2025-04-01) -
Covid-19 pandemic data analysis using tensor methods
by: Dipak Dulal, et al.
Published: (2024-03-01)