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.
Keywords: fluorescence dye selection; fluorescence labeling; genome sequencing; maximum likelihood; single molecule synthesis process.