Novel algorithm for analysis of cellular fluorescence spectrum based on optimization iteration

When using the spectral measurement method for multi-color fluorescence analysis of cells, the emission spectrum can produce partial spectral overlap, which poses certain difficulties for qualitative and quantitative analysis. Aiming at the problem, a novel algorithm was developed to effectively decompose the overlapped spectral peaks based on optimization iteration. First, the separation model of overlapped peak was built up to obtain the peak vertex of overlapping peaks. And then, according to the size of each constructed peak area, the structure of the constructed peak was re-determined, and finally the vertex and area information of the simulated peak was obtained.Moreover, the algorithm was used to analyze the overlapping peaks formed by the superposition of Gaussian functions, and compared with the conventional methods. The results show that the analytical error of the optimized iterative algorithm is stable within 0.15%, while it can be stabilized within 0.85% after adding random noise, which are all better that the other two algorithms. In addition, the iterative efficiency under the algorithm was calculated, and the results show that the algorithm is 32.2% higher than the conventional method.