Abstract
As a major class of noncoding RNAs, long noncoding RNAs (lncRNAs) have been implicated in various critical biological processes. Accumulating researches have linked dysregulations and mutations of lncRNAs to a variety of human disorders and diseases. However, to date, only a few human lncRNAs have been associated with diseases. Therefore, it is very important to develop a computational method to globally predict potential associated diseases for human lncRNAs. In this paper, we developed a computational framework to accomplish this by combining human lncRNA expression profiles, gene expression profiles, and human disease-associated gene data. Applying this framework to available human long intergenic noncoding RNAs (lincRNAs) expression data, we showed that the framework has reliable accuracy. As a result, for non-tissue-specific lincRNAs, the AUC of our algorithm is 0.7645, and the prediction accuracy is about 89%. This study will be helpful for identifying novel lncRNAs for human diseases, which will help in understanding the roles of lncRNAs in human diseases and facilitate treatment. The corresponding codes for our method and the predicted results are all available at http://asdcd.amss.ac.cn/MingXiLiu/lncRNA-disease.html.
Highlights
In recent years, accumulated studies have shown that proteincoding genes account for a very small part of the mammalian whole genome, approximately 2% [1,2,3,4,5,6,7,8]
Identifying novel potential long noncoding RNAs (lncRNAs)-associated diseases is emerging in bioinformatics as a tool for improving the understanding of disease pathogenesis at the lncRNA level which, in turn, will improve the prognosis, diagnosis, treatment and prevention of human disease
We proposed the first computational method not based on known lncRNA-associated diseases to identify potential human lncRNA-associated diseases
Summary
In recent years, accumulated studies have shown that proteincoding genes account for a very small part of the mammalian whole genome, approximately 2% [1,2,3,4,5,6,7,8]. This fact challenges the traditional view that RNA is just an intermediary between gene and protein. With the development of both experimental technology and computational methods, an increasing number of lncRNAs have been identified in the human transcriptome [12]. More than 150 human diseases are associated with lncRNAs, according to the LncRNADisease database [15], such as breast cancer [16,17], leukemia [18,19], colon cancer [20], prostate cancer [21], Alzheimer’s disease [22], and psoriasis [23]
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