AUTHOR=Zeng Pan , Chen Ji , Meng Yuhong , Zhou Yuan , Yang Jichun , Cui Qinghua TITLE=Defining Essentiality Score of Protein-Coding Genes and Long Noncoding RNAs JOURNAL=Frontiers in Genetics VOLUME=9 YEAR=2018 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2018.00380 DOI=10.3389/fgene.2018.00380 ISSN=1664-8021 ABSTRACT=

Measuring the essentiality of genes is critically important in biology and medicine. Here we proposed a computational method, GIC (Gene Importance Calculator), which can efficiently predict the essentiality of both protein-coding genes and long noncoding RNAs (lncRNAs) based on only sequence information. For identifying the essentiality of protein-coding genes, GIC outperformed well-established computational scores. In an independent mouse lncRNA dataset, GIC also achieved an exciting performance (AUC = 0.918). In contrast, the traditional computational methods are not applicable to lncRNAs. Moreover, we explored several potential applications of GIC score. Firstly, we revealed a correlation between gene GIC score and research hotspots of genes. Moreover, GIC score can be used to evaluate whether a gene in mouse is representative for its homolog in human by dissecting its cross-species difference. This is critical for basic medicine because many basic medical studies are performed in animal models. Finally, we showed that GIC score can be used to identify candidate genes from a transcriptomics study. GIC is freely available at http://www.cuilab.cn/gic/.