标题
Using neural networks for reducing the dimensions of single-cell RNA-Seq data
作者
关键词
-
出版物
NUCLEIC ACIDS RESEARCH
Volume 45, Issue 17, Pages e156-e156
出版商
Oxford University Press (OUP)
发表日期
2017-07-25
DOI
10.1093/nar/gkx681
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning
- (2017) Bo Wang et al. NATURE METHODS
- Gene expression inference with deep learning
- (2016) Yifei Chen et al. BIOINFORMATICS
- pcaReduce: hierarchical clustering of single cell transcriptional profiles
- (2016) Justina žurauskienė et al. BMC BIOINFORMATICS
- Disentangling neural cell diversity using single-cell transcriptomics
- (2016) Jean-Francois Poulin et al. NATURE NEUROSCIENCE
- Computational genomics tools for dissecting tumour–immune cell interactions
- (2016) Hubert Hackl et al. NATURE REVIEWS GENETICS
- g:Profiler—a web server for functional interpretation of gene lists (2016 update)
- (2016) Jüri Reimand et al. NUCLEIC ACIDS RESEARCH
- A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages
- (2016) Robert J. Kimmerling et al. Nature Communications
- Identification of cell types from single-cell transcriptomes using a novel clustering method
- (2015) Chen Xu et al. BIOINFORMATICS
- Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells
- (2015) Allon M. Klein et al. CELL
- Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity
- (2015) Chang-Lin Li et al. CELL RESEARCH
- Single-Cell RNA-Seq with Waterfall Reveals Molecular Cascades underlying Adult Neurogenesis
- (2015) Jaehoon Shin et al. Cell Stem Cell
- Single Cell RNA-Sequencing of Pluripotent States Unlocks Modular Transcriptional Variation
- (2015) Aleksandra A. Kolodziejczyk et al. Cell Stem Cell
- Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells
- (2015) Florian Buettner et al. NATURE BIOTECHNOLOGY
- A survey of human brain transcriptome diversity at the single cell level
- (2015) Spyros Darmanis et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
- (2015) A. Zeisel et al. SCIENCE
- SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis
- (2015) Minzhe Guo et al. PLoS Computational Biology
- Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
- (2014) Barbara Treutlein et al. NATURE
- The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
- (2014) Cole Trapnell et al. NATURE BIOTECHNOLOGY
- Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types
- (2014) D. A. Jaitin et al. SCIENCE
- Single-Cell Gene Expression Profiles Define Self-Renewing, Pluripotent, and Lineage Primed States of Human Pluripotent Stem Cells
- (2014) Shelley R. Hough et al. Stem Cell Reports
- Identifying proteins controlling key disease signaling pathways
- (2013) Anthony Gitter et al. BIOINFORMATICS
- The role of focal adhesion complexes in fibroblast mechanotransduction during scar formation
- (2013) Kristine C. Rustad et al. DIFFERENTIATION
- Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells
- (2013) Alex K. Shalek et al. NATURE
- DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data
- (2012) Marcel H Schulz et al. BMC Systems Biology
- Detecting overlapping protein complexes in protein-protein interaction networks
- (2012) Tamás Nepusz et al. NATURE METHODS
- IRF6 in development and disease: A mediator of quiescence and differentiation
- (2011) Caleb M. Bailey et al. CELL CYCLE
- Mouse chimeras as a system to investigate development, cell and tissue function, disease mechanisms and organ regeneration
- (2011) Sigrid Eckardt et al. CELL CYCLE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now