scMonica: Single-cell Mosaic Omics Nonlinear Integration and Clustering Analysis DOI
Xiaoli Li, Rui Zhang, Saba Aslam

et al.

2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Journal Year: 2024, Volume and Issue: unknown, P. 1579 - 1583

Published: Dec. 3, 2024

Language: Английский

scmFormer Integrates Large‐Scale Single‐Cell Proteomics and Transcriptomics Data by Multi‐Task Transformer DOI Creative Commons
Jing Xu,

De‐Shuang Huang,

Xiujun Zhang

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: 11(19)

Published: March 14, 2024

Abstract Transformer‐based models have revolutionized single cell RNA‐seq (scRNA‐seq) data analysis. However, their applicability is challenged by the complexity and scale of single‐cell multi‐omics data. Here a novel multi‐modal/multi‐task transformer (scmFormer) proposed to fill up existing blank integrating proteomics with other omics Through systematic benchmarking, it demonstrated that scmFormer excels in large‐scale multimodal heterogeneous multi‐batch paired data, while preserving shared information across batchs distinct biological information. achieves 54.5% higher average F1 score compared second method transferring cell‐type labels from transcriptomics Using COVID‐19 datasets, presented successfully integrates over 1.48 million cells on personal computer. Moreover, also proved performs better than methods generating unmeasured modality well‐suited for spatial multi‐omic Thus, powerful comprehensive tool analyzing

Language: Английский

Citations

10
A joint analysis of single cell transcriptomics and proteomics using transformer DOI Creative Commons
Yuanyuan Chen, Xiaodan Fan,

Chaowen Shi

et al.

npj Systems Biology and Applications, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 2, 2025

CITE-seq provides a powerful method for simultaneously measuring RNA and protein expression at the single-cell level. The integrated analysis of in identical cells is crucial revealing cellular heterogeneity. However, high experimental costs associated with limit its widespread application. In this paper, we propose scTEL, deep learning framework based on Transformer encoder layers, to establish mapping from sequenced unobserved same cells. This computation-based approach significantly reduces sequencing. We are now able predict using sequencing (scRNA-seq) data, which well-established available lower cost. Moreover, our scTEL model offers unified integrating multiple datasets, addressing challenge posed by partial overlap panels across different datasets. Empirical validation public datasets demonstrates outperforms existing methods.

Language: Английский

Citations

0
A Map of the Lipid–Metabolite–Protein Network to Aid Multi-Omics Integration DOI Creative Commons
Uchenna Alex Anyaegbunam, Aimilia-Christina Vagiona, Vincent ten Cate

et al.

Biomolecules, Journal Year: 2025, Volume and Issue: 15(4), P. 484 - 484

Published: March 26, 2025

The integration of multi-omics data offers transformative potential for elucidating complex molecular mechanisms underlying biological processes and diseases. In this study, we developed a lipid-metabolite-protein network that combines protein-protein interaction enzymatic genetic interactions proteins with metabolites lipids to provide unified framework integration. Using hyperbolic embedding, the visualizes connections across omics layers, accessible through user-friendly Shiny R (version 1.10.0) software package. This ranks molecules layers based on functional proximity, enabling intuitive exploration. Application in cardiovascular disease (CVD) case study identified associated CVD-related proteins. analysis confirmed known associations, like cholesterol esters sphingomyelin, highlighted novel biomarkers, such as 4-imidazoleacetate indoleacetaldehyde. Furthermore, used analyze empagliflozin's temporal effects lipid metabolism. Functional enrichment signatures revealed dynamic shifts processes, early impacting phospholipid metabolism long-term affecting sphingolipid biosynthesis. Our versatile tool hypothesis generation, analysis, biomarker discovery. By bridging approach advances our understanding therapeutic effects, broad applications computational biology precision medicine.

Language: Английский

Citations

0
Research Progress on the Role and Intervention of the MAPK Signaling Pathway in the Imbalance of Bone Remodeling in Postmenopausal Osteoporosis DOI

雍霖 颜

Advances in Clinical Medicine, Journal Year: 2025, Volume and Issue: 15(04), P. 2483 - 2493

Published: Jan. 1, 2025

Language: Английский

Citations

0
Single-cell transcriptome profiling reveals the spatiotemporal distribution of triterpenoid saponin biosynthesis and transposable element activity in Gynostemma pentaphyllum shoot apexes and leaves DOI Creative Commons
Rucan Li, Ke Du, Chuyi Zhang

et al.

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: May 8, 2024

Gynostemma pentaphyllum (Thunb.) Makino is an important producer of dammarene-type triterpenoid saponins. These saponins (gypenosides) exhibit diverse pharmacological benefits such as anticancer, antidiabetic, and immunomodulatory effects, have major potential in the pharmaceutical health care industries. Here, we employed single-cell RNA sequencing (scRNA-seq) to profile transcriptomes more than 50,000 cells derived from G. shoot apexes leaves. Following cell clustering annotation, identified five types four Each type displayed substantial transcriptomic heterogeneity both within between tissues. Examining gene expression patterns across various revealed that gypenoside biosynthesis predominantly occurred mesophyll cells, with heightened activity observed compared Furthermore, explored impact transposable elements (TEs) on landscapes. Our findings highlighted unbalanced certain TE families different leaves, marking first investigation at level plants. Additionally, dynamic genes involved specific during epidermal vascular development. The involvement regulating differentiation warrant further exploration. Overall, this study not only provides new insights into spatiotemporal organization leaves but also offers valuable cellular genetic resources for a deeper understanding developmental physiological processes resolution species.

Language: Английский

Citations

1
Dynamics of alternative polyadenylation in single root cells of Arabidopsis thaliana DOI Creative Commons

Xingyu Bi,

Sheng Zu Zhu, Fei Liu

et al.

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: Sept. 20, 2024

Introduction Single-cell RNA-seq (scRNA-seq) technologies have been widely used to reveal the diversity and complexity of cells, pioneering studies on scRNA-seq in plants began emerge since 2019. However, existing utilized focused only gene expression regulation. As an essential post-transcriptional mechanism for regulating expression, alternative polyadenylation (APA) generates diverse mRNA isoforms with distinct 3’ ends through selective use different sites a gene. APA plays important roles multiple developmental processes plants, such as flowering time stress response. Methods In this study, we developed pipeline identify integrate from data analyze dynamics single cells. First, high-confidence poly(A) root cells were identified quantified. Second, three kinds markers exploring including differentially expressed based site usages, switching genes 3′ UTR (untranslated region) length change. Moreover, cell type annotations refined by integrating both information profile. Results We comprehensively compiled single-cell atlas five studies, covering over 150,000 spanning four major tissue branches, twelve types, stages. quantified dynamic usages across tissues types. Further, integrated complementary profiles annotate types subtle differences between Discussion This study reveals that provides additional layer determining identity landscape during Arabidopsis development.

Language: Английский

Citations

1
Arabidopsis enters the single‐cell proteomics era DOI Creative Commons
Monique van Schie, Dolf Weijers

New Phytologist, Journal Year: 2024, Volume and Issue: 244(5), P. 1678 - 1680

Published: July 22, 2024

This article is a Commentary on Montes et al . (2024), 244 : 1750–1759

Language: Английский

Citations

0
scPlantFormer: A Lightweight Foundation Model for Plant Single-Cell Omics Analysis DOI Creative Commons
Xiujun Zhang, Jing Xu, Di Chen

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 21, 2024

Abstract Foundation models have revolutionized single-cell omics data analysis and the increasing adoption of technologies in plant biology highlights pressing need for efficient analytical tools. Developing a high-performance lightweight foundation model science is complex yet necessary. Inspired by fact that gene expression vector cells contain less information-dense than sentence, we offer new perspective on pretraining develop scPlantFormer, pretrained one million Arabidopsis thaliana scRNA-seq data. Systematic benchmarking reveals scPlantFormer excels analysis. Besides, two workflows are proposed to refine cell-type identification significantly enhance accuracy inter-dataset annotation. effectively integrates across species, identifying conserved cell types validated literature uncovering novel ones. Additionally, it constructs comprehensive atlas with approximately 400,000 cells, positioning as powerful tool omics.

Language: Английский

Citations

0
Single-cell spatial (scs) omics Recent developments in data analysis DOI
José Camacho, Michael Armstrong, Luz García

et al.

TrAC Trends in Analytical Chemistry, Journal Year: 2024, Volume and Issue: unknown, P. 118109 - 118109

Published: Dec. 1, 2024

Language: Английский

Citations

0
scMonica: Single-cell Mosaic Omics Nonlinear Integration and Clustering Analysis DOI
Xiaoli Li, Rui Zhang, Saba Aslam

et al.

2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Journal Year: 2024, Volume and Issue: unknown, P. 1579 - 1583

Published: Dec. 3, 2024

Language: Английский

Citations

0