IC4R Overview

Mission Statement

IC4R (Information Commons for Rice) is a curated knowledgebase for the rice research community, dedicating to provide rice reference genome with standardized and accurate gene annotations based on a huge volume of omics data and a large number of rice-related literatures.

Features

IC4R is built based on an extensible and sustainable architecture that integrates multiple omics data through community-contributed modules. Each module is developed and maintained by different committed groups, deals with data collection, processing and visualization, and delivers data on-demand via web services. Designed for scalability and sustainability, IC4R features collaborative integration of rice data and low costs for database update and maintenance.

Committed Projects

To date, IC4R committed projects include:

  • Rice Expression Database: a repository of genome-wide expression profiles derived entirely from RNA-Seq data.
  • Rice Variation Database: an atlas of resequencing-based rice genomic variations.
  • Rice Homology Database: a database composed of plant homologous genes.
  • RiceWiki: a wiki-based, publicly editable and open-content platform for community curation of rice genes.
  • Rice Literature Miner: a comprehensive collection of rice-related publications with association with specific rice genes.

Future Directions

The ultimate goal of IC4R is to associate rice omics data with agronomically important phenotypic data, which will greatly help researchers and breeders to elucidate molecular mechanisms underlying these important agronomic traits.

Future directions of IC4R include incorporation of other omics data and association of multiple omics data with agronomically important traits, dedicating to build IC4R into a valuable knowledgebase for both basic and translational researches in rice. In addition, IC4R will also develop and integrate a variety of tools for functional annotation, co-expression network, genomic variation analysis, and literature mining as well as more interactive visualizations for various omics data.

We also call for worldwide collaborations and look forward to comments and suggestions from plant researchers and breeders, aiming to build IC4R into a more comprehensive knowledgebase covering all aspects of rice knowledge.