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smORFunction: a tool for predicting functions of small open reading frames and microproteins
BMC Bioinformatics ( IF 3 ) Pub Date : 2020-10-14 , DOI: 10.1186/s12859-020-03805-x
Xiangwen Ji , Chunmei Cui , Qinghua Cui

Small open reading frame (smORF) is open reading frame with a length of less than 100 codons. Microproteins, translated from smORFs, have been found to participate in a variety of biological processes such as muscle formation and contraction, cell proliferation, and immune activation. Although previous studies have collected and annotated a large abundance of smORFs, functions of the vast majority of smORFs are still unknown. It is thus increasingly important to develop computational methods to annotate the functions of these smORFs. In this study, we collected 617,462 unique smORFs from three studies. The expression of smORF RNAs was estimated by reannotated microarray probes. Using a speed-optimized correlation algorism, the functions of smORFs were predicted by their correlated genes with known functional annotations. After applying our method to 5 known microproteins from literatures, our method successfully predicted their functions. Further validation from the UniProt database showed that at least one function of 202 out of 270 microproteins was predicted. We developed a method, smORFunction, to provide function predictions of smORFs/microproteins in at most 265 models generated from 173 datasets, including 48 tissues/cells, 82 diseases (and normal). The tool can be available at https://www.cuilab.cn/smorfunction .

中文翻译:

smORFunction:用于预测开放阅读框和微蛋白功能的工具

小型开放阅读框(smORF)是长度小于100个密码子的开放阅读框。已发现从smORFs翻译的微蛋白可参与多种生物学过程,例如肌肉形成和收缩,细胞增殖和免疫激活。尽管先前的研究已经收集并注释了大量的smORF,但是大多数smORF的功能仍然未知。因此,开发计算方法以注释这些smORF的功能变得越来越重要。在这项研究中,我们从三项研究中收集了617,462个独特的smORF。通过重新注释的微阵列探针评估了smORF RNA的表达。使用速度优化的相关算法,通过具有已知功能注释的相关基因预测smORF的功能。将我们的方法应用于文献中的5种已知微蛋白后,我们的方法成功预测了它们的功能。UniProt数据库的进一步验证表明,预测到270种微蛋白中至少有202种功能。我们开发了一种方法smORFunction,以提供从173个数据集(包括48个组织/细胞,82种疾病(和正常))生成的最多265个模型中的smORFs /微蛋白的功能预测。该工具可以在https://www.cuilab.cn/smorfunction上获得。可以在173个数据集(包括48个组织/细胞,82种疾病(和正常))生成的最多265个模型中提供smORF /微蛋白的功能预测。该工具可以在https://www.cuilab.cn/smorfunction上获得。可以在173个数据集(包括48个组织/细胞,82种疾病(和正常))生成的最多265个模型中提供smORF /微蛋白的功能预测。该工具可以在https://www.cuilab.cn/smorfunction上获得。
更新日期:2020-10-14
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