**Acknowledgements**

*Recent Advances in Rice Research*

database [74], SNP databases [53, 54, 78] and pathway databases [75, 76]. Each of

To date, several bioinformatics tools are available for the researcher to use and connect in an analysis pipeline. Criteria and parameter are the essential part that always carefully revised and look into while performing the bioinformatics analysis. This review highlights bioinformatics workflow used in the identification of SNPs in genomic and transcriptomic data, gene co-expression network analysis, omics data integration. This result facilitates the interpretation of SNPs

In this study, the flavonoid related gene, co-expressed gene and SNP are stored in a one-stop database that is specifically developed as a genetics and genomics repository to keep all information related to nutritional traits in rice known as *MyNutRice*Base (http://www.mynutricebase.org) (**Figure 2**). It provides a platform for data mining of SNPs and genes, data visualization and sequence similarity search analysis. *MyNutRice*Base aims to accelerate the genomics and genetic analysis by enabling the rice geneticist and breeders to mine and export the biological

these databases have their uniqueness and specific target users.

*The homepage of* MyNutRice*Base (http://www.mynutricebase.org).*

information for the application in rice breeding improvement.

**92**

**6. Conclusions**

**Figure 2.**

This work was carried out at the Centre for Bioinformatics Research, Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia and Malaysian Agricultural Research & Development Institute (MARDI). The open access publishing fees are funded by GP-2020-K007217 and GP-2019-K021204 grants.
