AE-RW:通过使用自编码器和随机步行在miRNA基因疾病异质网络上预测miRNA疾病关联
1School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, Gansu, PR China.
Computational biology and chemistry
|May 16, 2024
概括
这项研究引入了AE-RW,一种新的计算方法,通过整合miRNA,基因和疾病数据来预测microRNA-疾病关联. 该模型实现了高精度,性能优于现有方法,并显示出医学进步的前景.
科学领域:
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 异常的微RNA (miRNA) 表达与各种复杂疾病有关.
- 精确确定miRNA与疾病的关系对于医学进步至关重要.
- 对于预测miRNA-疾病关联的现有计算方法有局限性.
研究的目的:
- 开发一种有效的计算方法来预测miRNA与疾病的关联.
- 解决现有技术中未充分探索miRNA-基因-疾病异质网络的问题.
- 为了提高miRNA疾病关联预测的准确性.
主要方法:
- 构建了一个miRNA-基因-疾病异质网络,集成关联信息和相似之处.
- 应用自动编码器和随机步行用于独立的网络特征提取.
- 整合特征并利用深度神经网络 (DNN) 进行关联预测.
主要成果:
- 通过对HMDD v3.2数据集进行5倍交叉验证,AE-RW模型实现了0.9478的曲线下面面积 (AUC).
- 在预测准确度方面,AE-RW的表现优于现有的五种最先进的模型.
- 乳腺癌和肺癌的案例研究证实了该模型的卓越预测能力.
结论:
- 在AE-RW模型有效地预测miRNA-疾病协会使用异质网络方法.
- 将基因信息集成到miRNA疾病网络中可以提高预测性能.
- 这种方法为推进人类医学进步提供了一个有前途的计算工具.
相关概念视频
01:22MicroRNAs
3.0K
MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
3.0K
01:11Genome-wide Association Studies-GWAS
13.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
13.3K