De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures
De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures
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DOI：
10.1093/bioinformatics/btm026
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发表时间：
2007-06-01
期刊：
影响因子：
5.8
通讯作者：
Mishra, Santosh K.
中科院分区：
文献类型：
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作者：
Ng, Kwang Loong Stanley;Mishra, Santosh K.
动机：microRNA（miRNA）是小的NCRNA，通过转录后基因调节途径参与各种细胞和生理过程。与miRNA的生物发生密切相关，发夹结构是新型前体miRNA（Pre-mirs）计算分类的必要特征。尽管许多丰富的基因组倒重复序列（伪发夹）可以被过滤计算，但新型物种特异性的预Mir可能仍然难以捉摸。回报：mipred是从头支持矢量机（SVM）识别预先培训的人不依赖系统发育保护。为了比现有的（准）从头预测变量获得明显更高的灵敏度和特异性，它采用高斯径向基函数核（RBF）作为29个全局和固有发夹折叠属性的相似度度量。它们表征了二核苷酸序列，发夹折叠，非线性统计热力学和拓扑水平的前MIR。 MIPRED接受了200个人类预Mir和400个伪发夹的培训，可实现93.50％（5倍的交叉验证精度）和0.9833（ROC得分）。在其余的123个人类前疗法和246个伪发夹上进行了测试，报告了84.55％（灵敏度），97.97％（特异性）和93.50％（准确性）。经过40种非人类物种和3836个伪发夹的1918年验证，它的平均敏感性，特异性，特异性和精度（总体）敏感性，特异性和准确性和精度（总体）敏感性和精度为97.75％（97.42％），97.75％（97.42％）和97.75％（97.42％）和97.75％（97.42％）和97.75％（97.42％）和97.75％（97.42％）和97.75％（97.42％），特异性和精度为97.75％（97.42％） 。值得注意的是，A.Mellifera，A.Geoffroyi，C.Familiaris，E.Barr，H-Simplex病毒，H。Cytomegalo病毒，O.Aries，P.Patens，R。lymphocryptovirus，simian Virus，simian Virus and Z.Mays均与均匀分类。 100.00％（灵敏度）和> 93.75％（特异性）。
Motivation: MicroRNAs (miRNAs) are small ncRNAs participating in diverse cellular and physiological processes through the posttranscriptional gene regulatory pathway. Critically associated with the miRNAs biogenesis, the hairpin structure is a necessary feature for the computational classification of novel precursor miRNAs (pre-miRs). Though many of the abundant genomic inverted repeats (pseudo hairpins) can be filtered computational ly, novel species-specific pre-miRs are likely to remain elusive.Results: miPred is a de novo Support Vector Machine (SVM) classifier for identifying pre-miRs without relying on phylogenetic conservation. To achieve significantly higher sensitivity and specificity than existing (quasi) de novo predictors, it employs a Gaussian Radial Basis Function kernel (RBF) as a similarity measure for 29 global and intrinsic hairpin folding attributes. They characterize a pre-miR at the dinucleotide sequence, hairpin folding, non-linear statistical thermodynamics and topological levels. Trained on 200 human pre-miRs and 400 pseudo hairpins, miPred achieves 93.50% (5-fold cross-validation accuracy) and 0.9833 (ROC score). Tested on the remaining 123 human pre-miRs and 246 pseudo hairpins, it reports 84.55% (sensitivity), 97.97% (specificity) and 93.50% (accuracy). Validated onto 1918 pre-miRs across 40 non-human species and 3836 pseudo hairpins, it yields 87.65% (92.08%), 97.75% (97.42%) and 94.38% (95.64%) for the mean (overall) sensitivity, specificity and accuracy. Notably, A.mellifera, A.geoffroyi, C.familiaris, E.Barr, H-Simplex virus, H. cytomegalo virus, O.aries, P.patens, R.lymphocryptovirus, Simian virus and Z.mays are unambiguously classified with 100.00% (sensitivity) and > 93.75% (specificity).