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Application of Computational Biology to Decode Brain Transcriptomes
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作者 Jie Li Guang-Zhong Wang 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2019年第4期367-380,共14页
The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases,providing great opportunities for systematically investigating gene expression characteristic... The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases,providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental stages.Recent studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain complexity.However,our knowledge of brain transcriptional characteristics remains very limited.With the immense efforts to generate high-quality brain transcriptome atlases,new computational approaches to analyze these highdimensional multivariate data are greatly needed.In this review,we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field,which would aid in making new discoveries in brain development and disorders. 展开更多
关键词 brain transcriptome atlas Computational analysis Spatiotemporal pattern Coexpression analysis Single-cell analysis
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