论文标题
转录爆发模型的特殊功能方法
Special Function Methods for Bursty Models of Transcription
论文作者
论文摘要
我们探讨了一种用于分析基因表达的Markov模型，涉及MRNA的爆发产生，其转化为成熟mRNA及其随之而来的降解。我们证明，可以通过评估特殊功能来近似用于计算随机系统解决方案的集成。此外，特殊功能解决方案的形式将概括为更广泛的爆发分布。鉴于转录组学数据的生物物理参数推断的更广泛的目标，我们将方法应用于模拟数据，并证明了对精度和运行时的有效控制。最后，我们建议一种将参数推理的计算复杂性降低到状态空间大小和候选参数数量的线性顺序的非乘坐方法。
We explore a Markov model used in the analysis of gene expression, involving the bursty production of pre-mRNA, its conversion to mature mRNA, and its consequent degradation. We demonstrate that the integration used to compute the solution of the stochastic system can be approximated by the evaluation of special functions. Furthermore, the form of the special function solution generalizes to a broader class of burst distributions. In light of the broader goal of biophysical parameter inference from transcriptomics data, we apply the method to simulated data, demonstrating effective control of precision and runtime. Finally, we suggest a non-Bayesian approach to reducing the computational complexity of parameter inference to linear order in state space size and number of candidate parameters.
