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Related Experiment Video

Updated: May 16, 2026

IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae

IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae

Published on: January 15, 2020

RiceXPro version 3.0: expanding the informatics resource for rice transcriptome.

Yutaka Sato¹, Hinako Takehisa, Kaori Kamatsuki

¹Genome Resource Unit, Agrogenomics Research Center, National Institute of Agrobiological Sciences, Kannondai 2-1-2, Tsukuba, Ibaraki 305-8602, Japan.

Nucleic Acids Research

|November 28, 2012

Summary

This summary is machine-generated.

The updated RiceXPro database offers comprehensive rice gene expression profiles across the entire growth cycle and various conditions. This resource aids in characterizing gene function and exploring cereal crop genetics.

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Published on: May 9, 2017

Area of Science:

Plant Molecular Biology
Genomics
Bioinformatics

Background:

Gene expression profiling is crucial for understanding plant gene function.
Existing resources provide valuable data but require continuous updates for comprehensive analysis.

Purpose of the Study:

To update and enhance the RiceXPro database with more comprehensive rice transcriptome data.
To improve accessibility and analytical capabilities for researchers studying rice gene expression.

Main Methods:

Integration of new gene expression profile data covering the entire rice growth cycle and diverse experimental conditions.
Development of enhanced user interfaces for data retrieval, including single-gene and multi-dataset views.
Implementation of a BLAST search function for identifying genes with similar expression patterns.

Main Results:

The updated RiceXPro database now includes extensive data categorized into 'field/development' (572 data, 12 datasets), 'plant hormone' (143 data, 13 datasets), and 'cell- and tissue-type' (38 microarray data).
New interfaces facilitate efficient retrieval of gene expression information and global analysis across multiple datasets.
BLAST search enables exploration of expression profiles based on sequence similarity.

Conclusions:

The enhanced RiceXPro database provides a powerful and efficient tool for in-depth analysis of rice gene expression signatures.
The updated resource is expected to significantly aid in the characterization of gene function in rice and offer insights into other cereal crops.