嵌套的出生-死亡过程与参数重的神经网络竞争,因为蛋白质进化的时间依赖模型是具有竞争力的
bioRxiv : the preprint server for biology
|February 12, 2026
概括
基于进化理论的增强型遗传学模型提供了更高的参数效率. 一个嵌套的TKF92模型,结合了结构异质性,在分子进化分析的准确性方面与复杂的神经网络竞争.
科学领域:
- 计算生物学 计算生物学
- 分子进化分子进化
- 生物信息学是一种生物信息学.
背景情况:
- 统计遗传学通常使用简化的马尔科夫模型来研究分子进化.
- 这些模型往往忽略了插入,删除 (indels) 和氨基酸相互作用对选择压力的影响.
- 现有模型的简单假设限制了它们在植物遗传学分析中的现实性.
研究的目的:
- 通过结合嵌套结构和潜伏状态来扩展TKF92模型,以提高现实性.
- 将增强的TKF92模型的性能与基于神经网络的序列对序列模型进行比较.
- 为了评估模型的效率和适应真实生物序列数据.
主要方法:
- 扩展了TKF92模型以嵌套结构和潜伏状态来捕捉结构异质性.
- 开发了TKF92扩展作为即时过程的精确解决方案,以进化时间作为矩阵指数系数.
- 对比了TKF92扩展与两个类的神经seq2seq模型,使用PFam数据库上的每个字符困惑度.
主要成果:
- 一个基于32,000个参数的嵌套TKF模型显示了与数百万个参数的神经网络相比具有很高的竞争力.
- 增强的TKF92模型的性能超过了大多数测试的神经架构.
- 与不受约束的神经模型相比,TKF92扩展显示出更高的参数效率和适合真实对齐.
结论:
- 基于分子进化理论的家系学方法可以更有效地对参数进行分析,并提供比无约束的替代方案更好的适应.
- 将基于连续时间马尔科夫链 (CTMC) 的模型结构纳入神经遗传学方法得到支持.
- 增强的TKF92模型为统计遗传学提供了一个现实的,高效的替代方案.
相关概念视频
Protein Networks
4.6K
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,...
4.6K
Protein Networks
2.9K
2.9K
Competition
25.0K
When organisms require the same limited resources within an environment, they may have to compete for them. Competition is a net-negative interaction. Even if two competing individuals or populations do not interact directly, the overall fitness of both competitors is lowered as a result of not having full access to the limited resource.
25.0K
The Evidence for Evolution
48.4K
Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
48.4K
Chronopharmacokinetics: Time-Dependent Pharmacokinetics
419
Chronopharmacokinetics studies the temporal change in drug absorption and elimination. These changes can be cyclical or non-cyclical. Cyclical changes occur over a regular interval, while non-cyclical changes occur over a longer, irregular period.
Time-dependent pharmacokinetics refers to non-cyclical changes in drug rate processes over a period of time. It can lead to nonlinear pharmacokinetics, where the relationship between drug concentration and time is not proportional. Non-cyclical...
Time-dependent pharmacokinetics refers to non-cyclical changes in drug rate processes over a period of time. It can lead to nonlinear pharmacokinetics, where the relationship between drug concentration and time is not proportional. Non-cyclical...
419
Convergent Evolution
33.1K
Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
33.1K


