Abstract
With the advancement of high throughput technologies, there has been a massive surge in the omics data generation and there is a growing need to integrate this data gain insights into the patterns that shape biological interactions. Complex networks not only enable representation of such interactions, but also offer a mechanism for visualization and understanding of big data at a systems level. In this work, we use a complex network approach to investigate functions of the plant amplified StAR-related lipid transfer (START) domains in rice. We analyse the data at three levels; namely the transcriptome, proteome, and regulome. Each of these distinct datasets was superimposed after generation of the respective co-expression, protein-protein interaction, and gene regulatory networks for rice START genes, to reveal domain specific features in the family. This work thus serves as a protocol for network-based approaches to understand biological processes of genes and to complement experimental strategy.
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Acknowledgement
The authors acknowledge support of National Institute of Plant Genome Research (NIPGR), New Delhi for funding and infrastructure.
Funding
SKM and C acknowledge the Department of Biotechnology (DBT) Government of India for PhD fellowship. AP received fellowship from the CSIR. Participation in CNA was funded by RCUK BBSRC Grant BB/P027970/1TIGR2ESS ‘Transforming India’s Green Revolution by Research and Empowerment for Sustainable food Supplies’.
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Mahtha, S.K., Citu, Prasad, A., Yadav, G. (2022). Complex Networks Reveal Biological Functions of START Domains in Rice: Insights from Computational Systems Biology. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications X. COMPLEX NETWORKS 2021. Studies in Computational Intelligence, vol 1073. Springer, Cham. https://doi.org/10.1007/978-3-030-93413-2_53
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