Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Sep 23:12:722198.
doi: 10.3389/fgene.2021.722198. eCollection 2021.

NetGenes: A Database of Essential Genes Predicted Using Features From Interaction Networks

Vimaladhasan Senthamizhan  1   2 , Balaraman Ravindran  1   2   3 , Karthik Raman  1   2   4
Affiliations

NetGenes: A Database of Essential Genes Predicted Using Features From Interaction Networks

Vimaladhasan Senthamizhan et al. Front Genet. .

Abstract

Essential gene prediction models built so far are heavily reliant on sequence-based features, and the scope of network-based features has been narrow. Previous work from our group demonstrated the importance of using network-based features for predicting essential genes with high accuracy. Here, we apply our approach for the prediction of essential genes to organisms from the STRING database and host the results in a standalone website. Our database, NetGenes, contains essential gene predictions for 2,700+ bacteria predicted using features derived from STRING protein-protein functional association networks. Housing a total of over 2.1 million genes, NetGenes offers various features like essentiality scores, annotations, and feature vectors for each gene. NetGenes database is available from https://rbc-dsai-iitm.github.io/NetGenes/.

Keywords: database; essential genes; interaction network; machine learning; networks.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Workflow for creating NetGenes database. The initial 27 interactomes were used as the training dataset to build the machine learning (ML) model. The 2711 interactomes were run through the ML model to obtain the essential gene predictions. These predictions are curated and published in the “NetGenes” database.
Figure 2
Figure 2
Screenshot of Downloads page in the NetGenes database.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Azhagesan K., Ravindran B., Raman K. (2018). Network-based features enable prediction of essential genes across diverse organisms. PLoS ONE 13:e0208722. 10.1371/journal.pone.0208722 - DOI - PMC - PubMed
    1. Henderson K., Gallagher B., Li L., Akoglu L., Eliassi-Rad T., Tong H., et al. . (2011). It's who you know: graph mining using recursive structural features, in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '11 (New York, NY: Association for Computing Machinery; ), 663–671.
    1. Huerta-Cepas J., Serra F., Bork P. (2016). ETE 3: Reconstruction, analysis, and visualization of phylogenomic data. Mol. Biol. Evol. 33, 1635–1638. 10.1093/molbev/msw046 - DOI - PMC - PubMed
    1. Hwang Y.-C., Lin C.-C., Chang J.-Y., Mori H., Juan H.-F., Huang H.-C. (2009). Predicting essential genes based on network and sequence analysis. Mol. Biosyst. 5, 1672–1678. 10.1039/b900611g - DOI - PubMed
    1. L'Heureux A., Grolinger K., Elyamany H. F., Capretz M. A. M. (2017). Machine learning with big data: challenges and approaches. IEEE Access 5, 7776–7797. 10.1109/ACCESS.2017.2696365 - DOI

LinkOut - more resources

-