使用自动编码器,SE-ResNet模型和转移学习模型预测LncRNA-蛋白相互作用
1School of Mathematics and Statistics, Qingdao University, Qingdao, Shandong, China.
MicroRNA (Shariqah, United Arab Emirates)
|April 9, 2024
概括
一个新的深度学习框架AR-LPI增强了对长非编码RNA-蛋白相互作用 (LPIs) 的预测. 这种方法提高了准确性和F值,为了解生物过程和疾病中的LPIs提供了更好的工具.
科学领域:
- 生物信息学是一种生物信息学.
- 分子生物学分子生物学
- 计算生物学 计算生物学
背景情况:
- 长非编码RNA (lncRNAs) 在生物过程中至关重要;它们的失调与癌症和神经退行性疾病等疾病有关.
- 了解lncRNA-蛋白相互作用 (LPIs) 对于破译细胞功能,疾病机制和病原体相互作用至关重要.
- 预测LPIs具有挑战性,目前的研究重点是特征选择和深度学习架构.
研究的目的:
- 开发一种先进的深度学习框架,用于准确预测 lncRNA-蛋白相互作用 (LPIs).
- 通过结合序列和次要结构特征来改进现有的LPI预测方法.
主要方法:
- 提出AR-LPI,一个深度学习框架,使用自动编码器从蛋白质和lncRNA序列和结构中提取特征.
- 使用SE-ResNet进行LPI预测和应用转移学习,以提高小数据集的性能.
主要成果:
- 与现有方法相比,AR-LPI在LPI预测方面表现优越.
- 获得了94.52% (2.86%的增加) 的精度和94.73% (2.71%的增加) 的F值.
结论:
- AR-LPI框架为LPI预测提供了更高的准确性和有效性.
- 在整体表现方面,AR-LPI超过了其他可用的LPI预测工具.
相关概念视频
lncRNA - Long Non-coding RNAs
8.6K
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...
8.6K
Protein 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
Protein-protein Interfaces
12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K


