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Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

Dynamic-BM: multispecies Dynamic BodyMap database from temporal RNA-seq data.

Ya Cui¹, Xiaowei Chen², Yiwei Niu¹

¹Key Laboratory of RNA Biology, Institute of Biophysics and University of the Chinese Academy of Sciences, Beijing, China.

Briefings in Bioinformatics

|June 3, 2017

Summary

This summary is machine-generated.

Dynamic BodyMap (Dynamic-BM) is a new database offering temporal gene expression profiles from thousands of RNA sequencing samples across multiple species. It enables efficient exploration of dynamic gene expression patterns for protein-coding genes and long noncoding RNAs (lncRNAs) in development.

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Area of Science:

Developmental Biology
Genomics
Bioinformatics

Background:

Biological and developmental processes are dynamic, requiring analysis of temporal gene expression.
Existing databases lack comprehensive resources for dynamic gene expression patterns.
Recent advances in RNA sequencing (RNA-seq) have generated extensive time-series data for gene expression.

Purpose of the Study:

To introduce Dynamic BodyMap (Dynamic-BM), a novel database for exploring temporal gene expression profiles.
To provide a user-friendly platform for analyzing dynamic gene expression patterns of protein-coding genes and long noncoding RNAs (lncRNAs).
To support hypothesis generation in developmental biology research by facilitating data exploration.

Main Methods:

Compiled 2203 time-series RNA-seq samples covering over 25 tissues from five species.
Developed a user-friendly web interface for browsing and searching dynamic gene expression patterns.
Integrated a literature-based knowledgebase for lncRNAs involved in tissue development.

Main Results:

Dynamic-BM offers comprehensive temporal gene expression data for protein-coding genes and lncRNAs.
The database provides efficient tools for exploring dynamic expression patterns across various tissues and species.
Includes curated information on lncRNAs relevant to tissue development.

Conclusions:

Dynamic-BM serves as an open resource for researchers studying dynamic gene expression in development.
The database facilitates the investigation of temporal gene regulation and the role of lncRNAs in tissue development.
Enhances the exploration of complex biological processes through accessible, dynamic gene expression data.