Application of Computational Biology for Decoding Brain Transcriptomes

Publication date: Available online 23 October 2019Source: Genomics, Proteomics & BioinformaticsAuthor(s): Jie Li, Guang-Zhong WangAbstractThe 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 high-dimensional 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.
Source: Genomics, Proteomics and Bioinformatics - Category: Bioinformatics Source Type: research