DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence
Authors
Keywords
-
Journal
BRIEFINGS IN BIOINFORMATICS
Volume -, Issue -, Pages -
Publisher
Oxford University Press (OUP)
Online
2020-12-19
DOI
10.1093/bib/bbaa414
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Interpretable Artificial Intelligence: Why and When
- (2020) Adarsh Ghosh et al. AMERICAN JOURNAL OF ROENTGENOLOGY
- Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas
- (2020) Reuben Moncada et al. NATURE BIOTECHNOLOGY
- Benchmarking single-cell RNA-sequencing protocols for cell atlas projects
- (2020) Elisabetta Mereu et al. NATURE BIOTECHNOLOGY
- Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
- (2019) Samuel G. Rodriques et al. SCIENCE
- Preparing next-generation scientists for biomedical big data: artificial intelligence approaches
- (2019) Jason H Moore et al. Personalized Medicine
- Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis
- (2019) Silas Maniatis et al. SCIENCE
- Dissecting intratumoral myeloid cell plasticity by single cell RNA‐seq
- (2019) Qianqian Song et al. Cancer Medicine
- Conserved cell types with divergent features in human versus mouse cortex
- (2019) Rebecca D. Hodge et al. NATURE
- A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation
- (2019) Alexandra Grubman et al. NATURE NEUROSCIENCE
- Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction
- (2019) Jin Li et al. BIOINFORMATICS
- A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart
- (2019) Michaela Asp et al. CELL
- Mapping the Mouse Cell Atlas by Microwell-Seq
- (2018) Xiaoping Han et al. CELL
- Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
- (2018) Laleh Haghverdi et al. NATURE BIOTECHNOLOGY
- Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity
- (2018) Emelie Berglund et al. Nature Communications
- Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain
- (2018) Arpiar Saunders et al. CELL
- scPipe: A flexible R/Bioconductor preprocessing pipeline for single-cell RNA-sequencing data
- (2018) Luyi Tian et al. PLoS Computational Biology
- Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
- (2018) et al. NATURE
- Linnorm: improved statistical analysis for single cell RNA-seq expression data
- (2017) Shun H. Yip et al. NUCLEIC ACIDS RESEARCH
- Massively parallel digital transcriptional profiling of single cells
- (2017) Grace X. Y. Zheng et al. Nature Communications
- RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes
- (2016) Yurong Xin et al. Cell Metabolism
- Visualization and analysis of gene expression in tissue sections by spatial transcriptomics
- (2016) P. L. Stahl et al. SCIENCE
- Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq
- (2016) I. Tirosh et al. SCIENCE
- A Single-Cell Transcriptome Atlas of the Human Pancreas
- (2016) Mauro J. Muraro et al. Cell Systems
- Spatially resolved, highly multiplexed RNA profiling in single cells
- (2015) K. H. Chen et al. SCIENCE
- Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development
- (2014) Sean C. Bendall et al. CELL
- The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
- (2014) Cole Trapnell et al. NATURE BIOTECHNOLOGY
- Highly Multiplexed Subcellular RNA Sequencing in Situ
- (2014) J. H. Lee et al. SCIENCE
- A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
- (2009) D. M. Witten et al. BIOSTATISTICS
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started