使用piRNA生物标志物进行乳腺癌的机器学习诊断
Amy R Zhao1, Valentina L Kouznetsova2,3,4, Santosh Kesari5
1Scholars Program, CureScience Institute, San Diego, CA, USA.
概括
与PIWI相互作用的RNAs (piRNAs) 显示为乳腺癌检测的非侵入性生物标志物具有前途. 机器学习模型使用piRNA属性准确预测乳腺癌,后勤回归达到90.7%的准确性.
科学领域:
- 生物分子科学 生物分子科学
- 计算生物学 计算生物学
- 在瘤学瘤学.
背景情况:
- 小型非编码RNAs (sncRNAs) 与癌症的发展有关.
- 一类小型ncRNAs的PIWI相互作用RNAs (piRNAs) 在癌症发作中起作用.
- 正在探索piRNAs作为乳腺癌的新型非侵入性诊断生物标志物.
研究的目的:
- 开发使用piRNA属性进行乳腺癌预测的计算方法.
- 评估piRNAs对乳腺癌的诊断潜力.
主要方法:
- 生成的piRNA序列描述器.
- 应用机器学习分类器 (逻辑回归,SMO,随机森林,LMT) 在WEKA.
- 使用Shapley添加式解释 (SHAP) 进行描述符相关性分析.
- 在独立数据集上验证的模型.
主要成果:
- 在乳腺癌预测中,物流回归实现了90.7%的准确性.
- 顺序最小优化 (SMO) 和物流模型树 (LMT) 显示出高准确度 (分别为89.7%和85.65%).
- 确定了促进预测准确性的关键piRNA描述器.
结论:
- 基于机器学习的piRNA分类器对乳腺癌诊断非常有效.
- 这项研究支持piRNAs作为癌症诊断中的有价值的生物标志物.
- 需要进一步的研究来验证临床适用性.
相关概念视频
02:57piRNA - Piwi-interacting RNAs
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PIWI-interacting RNAs, or piRNAs, are the most abundant short non-coding RNAs. More than 20,000 genes have been found in humans that code for piRNAs while only 2000 genes have been found for miRNAs. piRNAs can act at the transcriptional and post-transcriptional levels and have a vital role in silencing transposable elements present in germ cells. They are also involved in epigenetic silencing and activation. Previously, they were thought to function only in germ cells but new evidence suggests...
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02:39lncRNA - Long Non-coding RNAs
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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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