Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Genesis mechanism of iodide and fluoride in groundwater driven by high-salinity in Bohai Bay.

Journal of contaminant hydrology·2026

Same author

Nitrate pollution sources and associated biogeochemical mechanisms in coastal groundwater affected by seawater intrusion using multiple isotopes and source apportionment models.

Marine pollution bulletin·2026

Same author

A High-Resolution VOC Emission Inventory for Gas Stations in a Typical Yangtze River Delta City: Implications for Ozone Formation, Secondary Organic Aerosol Formation, and Health Risks.

Toxics·2026

Same author

High co-occurrence but low heterogeneity of virulence factors and resistance genes in farmland soil.

Journal of environmental sciences (China)·2026

Same author

Regulatory landscape of widespread stop codon readthrough in <i>Drosophila</i>.

bioRxiv : the preprint server for biology·2026

Same author

Mechanoelectrical metamaterials for broad-range, high-sensitivity pressure sensing.

Science (New York, N.Y.)·2026

Same journal

Common xenobiotics modulate gut microbial responses to low‑calorie sweeteners in vitro.

Molecular systems biology·2026

Same journal

ParTIpy: a scalable framework for archetypal analysis and Pareto task inference.

Molecular systems biology·2026

Same journal

Quantitative interactome mapping of skeletal muscle insulin resistance.

Molecular systems biology·2026

Same journal

Interpretable multi-omics integration across mixed-order tensors with MANTRA.

Molecular systems biology·2026

Same journal

To cleave or not to cleave: a systemic evaluation of DSS versus DSSO for cross-linking mass spectrometry analysis.

Molecular systems biology·2026

Same journal

Multiscale learning of gene network-driven phenotypic dynamics of single cells.

Molecular systems biology·2026

See all related articles

Search research articles

Home
Interpretable Deep Generative Ensemble Learning For Single-cell Omics With Hydra.

Home
Interpretable Deep Generative Ensemble Learning For Single-cell Omics With Hydra.

Related Experiment Video

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Interpretable deep generative ensemble learning for single-cell omics with Hydra.

Manoj M Wagle^1,2,3,4, Chunlei Liu^1,2, Zunpeng Liu^4,5

¹School of Mathematics and Statistics, Faculty of Science, The University of Sydney, Camperdown, NSW, Australia.

Molecular Systems Biology

|April 11, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

Hydra, a deep learning framework, effectively analyzes single-cell omics data, improving rare cell population identification. This method enhances cell-type annotation for both unimodal and multimodal datasets, aiding disease research.

More Related Videos

Generation of Transgenic Hydra by Embryo Microinjection

Generation of Transgenic Hydra by Embryo Microinjection

Published on: September 11, 2014

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

Related Experiment Videos

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Generation of Transgenic Hydra by Embryo Microinjection

Generation of Transgenic Hydra by Embryo Microinjection

Published on: September 11, 2014

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

Area of Science:

Computational Biology
Genomics
Bioinformatics

Background:

Single-cell omics data analysis faces challenges due to high dimensionality, noise, and sparsity.
Accurate annotation of rare cell populations is crucial but difficult, especially in multimodal datasets.

Purpose of the Study:

To develop a deep generative framework, Hydra, for effective analysis of unimodal and multimodal single-cell omics data.
To improve the identification and annotation of rare cell populations.

Main Methods:

Hydra utilizes an ensemble of variational autoencoders for data learning.
Incorporates interpretable modules for capturing cell-type-specific molecular signatures.
Ensemble approach enables reproducible feature selection and robust cell-type annotation.

Main Results:

Hydra demonstrated comparable or superior performance across 21 diverse single-cell omics datasets.
The framework excels in robustly annotating brain cellular subtypes.
Hydra effectively preserves disease-relevant signatures, as shown in Alzheimer's disease data.

Conclusions:

Hydra provides a powerful and robust framework for single-cell omics data integration and analysis.
The method shows particular promise for advancing the study of rare cell populations in development and disease.
Hydra facilitates deeper understanding of cellular heterogeneity and disease mechanisms.