Integrated single cell data analysis reveals cell specific networks and novel coactivation markers
出版年份 2016 全文链接
标题
Integrated single cell data analysis reveals cell specific networks and novel coactivation markers
作者
关键词
Single-cell transcriptomics, RNA-sequencing, Mixture modelling, ScRNA-Seq, Olfactory sensory neuron, Neuron
出版物
BMC Systems Biology
Volume 10, Issue S5, Pages -
出版商
Springer Nature
发表日期
2016-12-05
DOI
10.1186/s12918-016-0370-4
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。- SCell: integrated analysis of single-cell RNA-seq data
- (2016) Aaron Diaz et al. BIOINFORMATICS
- pcaReduce: hierarchical clustering of single cell transcriptional profiles
- (2016) Justina žurauskienė et al. BMC BIOINFORMATICS
- Transcriptome Analysis of Murine Olfactory Sensory Neurons during Development Using Single Cell RNA-Seq
- (2016) Paul Scholz et al. CHEMICAL SENSES
- Adult mouse cortical cell taxonomy revealed by single cell transcriptomics
- (2016) Bosiljka Tasic et al. NATURE NEUROSCIENCE
- Identification of cell types from single-cell transcriptomes using a novel clustering method
- (2015) Chen Xu et al. BIOINFORMATICS
- Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
- (2015) Evan Z. Macosko et al. CELL
- Olfactory sensory neurons transiently express multiple olfactory receptors during development
- (2015) L. Tan et al. Molecular Systems Biology
- Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes
- (2015) János Fuzik et al. NATURE BIOTECHNOLOGY
- Single-cell transcriptomics reveals receptor transformations during olfactory neurogenesis
- (2015) N. K. Hanchate et al. SCIENCE
- Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
- (2015) A. Zeisel et al. SCIENCE
- Hierarchical deconstruction of mouse olfactory sensory neurons: from whole mucosa to single-cell RNA-seq
- (2015) Luis R. Saraiva et al. Scientific Reports
- Transcriptional Bursting in Gene Expression: Analytical Results for General Stochastic Models
- (2015) Niraj Kumar et al. PLoS Computational Biology
- HTSeq--a Python framework to work with high-throughput sequencing data
- (2014) S. Anders et al. BIOINFORMATICS
- Normalization of RNA-seq data using factor analysis of control genes or samples
- (2014) Davide Risso et al. NATURE BIOTECHNOLOGY
- Bayesian approach to single-cell differential expression analysis
- (2014) Peter V Kharchenko et al. NATURE METHODS
- Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue
- (2014) Ditte Lovatt et al. NATURE METHODS
- Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing
- (2014) Dmitry Usoskin et al. NATURE NEUROSCIENCE
- Single-cell RNA-seq: advances and future challenges
- (2014) Antoine-Emmanuel Saliba et al. NUCLEIC ACIDS RESEARCH
- Neuronal carbonic anhydrase VII provides GABAergic excitatory drive to exacerbate febrile seizures
- (2013) Eva Ruusuvuori et al. EMBO JOURNAL
- Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells
- (2013) Alex K. Shalek et al. NATURE
- Inferring the kinetics of stochastic gene expression from single-cell RNA-sequencing data
- (2013) Jong Kim et al. GENOME BIOLOGY
- STAR: ultrafast universal RNA-seq aligner
- (2012) Alexander Dobin et al. BIOINFORMATICS
- Genomics of mature and immature olfactory sensory neurons
- (2012) Melissa D. Nickell et al. JOURNAL OF COMPARATIVE NEUROLOGY
- Sonic Hedgehog Expression in Corticofugal Projection Neurons Directs Cortical Microcircuit Formation
- (2012) Corey C. Harwell et al. NEURON
- Heparan sulfate proteoglycan syndecan-3 is a novel receptor for GDNF, neurturin, and artemin
- (2011) Maxim M. Bespalov et al. JOURNAL OF CELL BIOLOGY
- Mammalian Genes Are Transcribed with Widely Different Bursting Kinetics
- (2011) D. M. Suter et al. SCIENCE
- A scaling normalization method for differential expression analysis of RNA-seq data
- (2010) Mark D Robinson et al. GENOME BIOLOGY
- The Sequence Alignment/Map format and SAMtools
- (2009) H. Li et al. BIOINFORMATICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started