
Single-nucleus gene expression Identifying the genes expressed at the level of a single cell nucleus can better help us understand the human brain. Blue et al. developed a single-nuclei sequencing technique, which they applied to cells in classically defined Brodmann areas from a postmortem brain. Clustering of gene expression showed concordance with the area of origin and defining 16 neuronal subtypes. Both excitatory and inhibitory neuronal subtypes show regional variations that define distinct cortical areas and exhibit how gene expression clusters may distinguish between distinct cortical areas. This method opens the door to widespread sampling of the genes expressed in a diseased brain and other tissues of interest. Science , this issue p. 1586
Cell Nucleus, Cerebral Cortex, Neurons, Biomedical and Clinical Sciences, General Science & Technology, Sequence Analysis, RNA, 1.1 Normal biological development and functioning, Gene Expression Profiling, Human Genome, Bioinformatics and Computational Biology, Neurosciences, Biological Sciences, Brain Disorders, Mental Health, Underpinning research, Physical Sciences, Neurological, Genetics, RNA, Humans, Transcriptome, Sequence Analysis
Cell Nucleus, Cerebral Cortex, Neurons, Biomedical and Clinical Sciences, General Science & Technology, Sequence Analysis, RNA, 1.1 Normal biological development and functioning, Gene Expression Profiling, Human Genome, Bioinformatics and Computational Biology, Neurosciences, Biological Sciences, Brain Disorders, Mental Health, Underpinning research, Physical Sciences, Neurological, Genetics, RNA, Humans, Transcriptome, Sequence Analysis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 899 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |
