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Related Experiment Video

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BEST: a web server for brain expression Spatio-temporal pattern analysis.

Liyuan Guo1,2, Wei Lin1,2, Yidan Zhang1,2

  • 1CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Chaoyang District, Beijing, 100101, China.

BMC Bioinformatics
|December 7, 2019
PubMed
Summary
This summary is machine-generated.

Researchers developed the Brain Expression Spatio-Temporal (BEST) web server to analyze gene expression patterns in mental disorders. This tool aids in linking genetic findings to molecular mechanisms by visualizing brain expression data.

Keywords:
Brain expression pattern analysisCo-expression clusterSpatio-temporalVisualizationWeb server

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Area of Science:

  • Neuroscience
  • Bioinformatics
  • Genetics

Background:

  • Dysregulated gene expression is implicated in mental disorders.
  • Psychiatric research often relies on genetic studies due to sample limitations.
  • Existing analyses of gene expression patterns in psychiatric genetics lack a dedicated online tool.

Purpose of the Study:

  • To develop a web server for systematic analysis of brain expression patterns in psychiatric genetics.
  • To provide a user-friendly platform for researchers without bioinformatics expertise.

Main Methods:

  • Developed the Brain Expression Spatio-Temporal (BEST) web server.
  • Integrated comprehensive human brain spatial-temporal expression data.
  • Implemented multi-dimensional analysis of gene sets and subsets, including co-expression patterns.

Main Results:

  • BEST offers user-friendly visualizations like heatmaps and gene networks.
  • The server integrates diverse brain expression data for comprehensive analysis.
  • BEST analyzes genes as single sets or co-expression clusters, correlating genetic and expression data.

Conclusions:

  • BEST is the first tool for comprehensive human brain spatial-temporal expression pattern analysis.
  • It bridges genetic and mechanistic studies in psychiatric research.
  • BEST aids in identifying key genes, molecular systems, and disease-relevant brain regions and ages.