通过图形卷积网络和注意力机制,识别小核RNA与疾病之间的关联
IEEE journal of biomedical and health informatics
|July 9, 2024
概括
这项研究介绍了GCASDA,一种使用图形卷积网络的计算方法,用于识别小核核RNA (snoRNA) -疾病关联. GCASDA有效地预测了潜在的联系,帮助疾病研究.
科学领域:
- 计算生物学 计算生物学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 小核RNAs (snoRNAs) 在生物过程中至关重要,但它们与疾病的关联尚未完全理解.
- 识别snoRNA与疾病的联系对于疾病发病研究至关重要.
- 协会发现的传统实验方法耗时且昂贵.
研究的目的:
- 开发一种高效的计算方法,用于识别潜在的小核细胞RNA与疾病的关联.
- 为了实现这一任务,利用图形卷积网络和多视图的注意力机制.
主要方法:
- 使用生物实体信息计算了snoRNA和疾病相似性矩阵.
- 采用随机森林模型来权衡snoRNA和疾病节点之间的边缘.
- 构建同质和异质图形,通过图形卷积网络提取特征并使用多视图图形注意力机制集成它们.
- 使用多层感知神经网络,具有全球和交互功能,用于最终的关联预测.
主要成果:
- 拟议的GCASDA方法实现了高性能,AUC为0.9356和AUPR为0.9294.
- 在各种评估指标上,GCASDA显著超过了现有的最先进的方法.
- 一个案例研究验证了GCASDA方法的实际可行性和有效性.
结论:
- GCASDA提供了一种高效准确的计算方法,用于发现新的snoRNA-疾病关联.
- 这种方法可以通过识别关键的snoRNA角色来加速对疾病病原学的研究.
- 这些发现突显了基于图形的深度学习模型在生物关联发现中的潜力.
相关概念视频
02:26Protein Networks
3.9K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.9K
02:39lncRNA - Long Non-coding RNAs
8.5K
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...
8.5K
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
01:05Single Nucleotide Polymorphisms-SNPs
15.0K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
15.0K
01:37Neural Regulation
39.3K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
39.3K
02:55The Nucleolus
8.8K
The nucleolus is the most prominent substructure of the nucleus. When it was first discovered, it was considered to be an isolated organelle that forms fibrils and granules. In 1931, the relationship between the nucleolus and chromosomes was first described by Heitz. He observed that the appearance and size of nucleolus varies depending on the stage of the cell cycle. He also noticed constricted regions on different chromosomes clustered together at definite cell cycle stages. These regions,...
8.8K