Single molecule sequencing is imperative to overall genetic analysis in areas such as genomics, transcriptomics, clinical test, drug development, and cancer screening. In addition, fluorescence-based sequencing is primarily applied in single molecule sequencing besides other methods, precisely in the fields of DNA sequencing. Modern-day fluorescence labeling methods exploit a charge-coupled device camera to capture snapshots of a number of pixels on the single molecule sequencing. The method discussed in this article involves fluorescence labeling detection with a single pixel, outrivals in high accuracy and low resource requirement under low signal-to-noise ratio conditions, as well as benefits from higher throughput comparing with others. Through discussion in this article, we explore the single molecule synthesis process modeling using negative binomial distributions. Furthermore, incorporating the method of maximum likelihood and Viterbi algorithm in this modeling enhances the signal detection accuracy. The fluorescence-based model benefits in simulating actual experiment processes and assisting in understanding relations between the fluorescence emission and the signal receiving events. Last but not least, the model offers potential candidates on fluorescence dye selection that yields more accurate experiment results.

中文翻译：

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单分子合成过程中优化的基于荧光的检测

单分子测序对于基因组学、转录组学、临床测试、药物开发和癌症筛查等领域的整体遗传分析必不可少。此外，荧光测序除了其他方法外，主要应用于单分子测序，也就是DNA测序领域。现代荧光标记方法利用电荷耦合器件相机来捕捉单分子测序上许多像素的快照。本文中讨论的方法涉及单个像素的荧光标记检测，在低信噪比条件下具有高精度和低资源需求的优势，以及与其他方法相比具有更高吞吐量的优势。通过本文的讨论，我们使用负二项式分布探索单分子合成过程建模。此外，在该建模中结合最大似然法和维特比算法提高了信号检测的准确性。基于荧光的模型有利于模拟实际实验过程，有助于理解荧光发射与信号接收事件之间的关系。最后但并非最不重要的是，该模型提供了荧光染料选择的潜在候选者，可产生更准确的实验结果。基于荧光的模型有利于模拟实际实验过程，有助于理解荧光发射与信号接收事件之间的关系。最后但并非最不重要的是，该模型提供了荧光染料选择的潜在候选者，可产生更准确的实验结果。基于荧光的模型有利于模拟实际实验过程，有助于理解荧光发射与信号接收事件之间的关系。最后但并非最不重要的是，该模型提供了荧光染料选择的潜在候选者，可产生更准确的实验结果。