Computational Methods for Single-cell Multi-omics Integration and Alignment
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Title
Computational Methods for Single-cell Multi-omics Integration and Alignment
Authors
Keywords
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Journal
GENOMICS PROTEOMICS & BIOINFORMATICS
Volume -, Issue -, Pages -
Publisher
Elsevier BV
Online
2022-12-27
DOI
10.1016/j.gpb.2022.11.013
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Note: Only part of the references are listed.- Emerging Artificial Intelligence Applications in Spatial Transcriptomics Analysis
- (2022) Yijun Li et al. Computational and Structural Biotechnology Journal
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- (2021) Zhen Miao et al. Nature Reviews Nephrology
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- (2021) Lyla Atta et al. Nature Communications
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- (2021) Malte D. Luecken et al. NATURE METHODS
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- (2020) Hani Jieun Kim et al. BIOINFORMATICS
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- (2020) Mattia Forcato et al. BRIEFINGS IN BIOINFORMATICS
- BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data
- (2020) Xinjun Wang et al. NUCLEIC ACIDS RESEARCH
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- (2020) Anjun Ma et al. TRENDS IN BIOTECHNOLOGY
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- (2020) Jeongwoo Lee et al. EXPERIMENTAL AND MOLECULAR MEDICINE
- SCIM: universal single-cell matching with unpaired feature sets
- (2020) Stefan G Stark et al. BIOINFORMATICS
- Deep-joint-learning analysis model of single cell transcriptome and open chromatin accessibility data
- (2020) Chunman Zuo et al. BRIEFINGS IN BIOINFORMATICS
- SHARE-seq reveals chromatin potential
- (2020) Dorothy Clyde NATURE REVIEWS GENETICS
- Evaluation of Cell Type Annotation R Packages on Single-cell RNA-seq Data
- (2020) Qianhui Huang et al. GENOMICS PROTEOMICS & BIOINFORMATICS
- Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
- (2019) Samuel G. Rodriques et al. SCIENCE
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- (2019) Chee-Huat Linus Eng et al. NATURE
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- (2019) Nikolaos Papadopoulos et al. BIOINFORMATICS
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- (2019) Wouter Saelens et al. NATURE BIOTECHNOLOGY
- A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classification
- (2019) Ren-Hua Chung et al. GigaScience
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- (2019) Tim Stuart et al. CELL
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- (2019) Bin Duan et al. Nature Communications
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- (2019) Sanja Vickovic et al. NATURE METHODS
- High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell
- (2019) Song Chen et al. NATURE BIOTECHNOLOGY
- Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
- (2018) Ricard Argelaguet et al. Molecular Systems Biology
- scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells
- (2018) Stephen J. Clark et al. Nature Communications
- Joint profiling of chromatin accessibility and gene expression in thousands of single cells
- (2018) Junyue Cao et al. SCIENCE
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- (2018) Shuhui Bian et al. SCIENCE
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- (2017) Vanessa M Peterson et al. NATURE BIOTECHNOLOGY
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- (2017) Yang Wang et al. IEEE Transactions on Neural Networks and Learning Systems
- More Is Better: Recent Progress in Multi-Omics Data Integration Methods
- (2017) Sijia Huang et al. Frontiers in Genetics
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- (2016) Lih Feng Cheow et al. NATURE METHODS
- High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization
- (2016) Jeffrey R. Moffitt et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Visualization and analysis of gene expression in tissue sections by spatial transcriptomics
- (2016) P. L. Stahl et al. SCIENCE
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- (2015) Evan Z. Macosko et al. CELL
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- (2014) Cole Trapnell et al. NATURE BIOTECHNOLOGY
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- (2014) Bo Wang et al. NATURE METHODS
- Gromov–Wasserstein Distances and the Metric Approach to Object Matching
- (2011) Facundo Mémoli FOUNDATIONS OF COMPUTATIONAL MATHEMATICS
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