Cell growth analysis method based on spectral clustering and single cell Raman spectrum

• Main Authors: LI XINLI, WANG CHUNBO, CHEN SHUCHANG, ZHANG SIYU, FU WENLIN, YANG BAINAN
• Format: Patent
• Language: Chinese; English
• Published: 17.11.2023
• Subjects: BEER; BIOCHEMISTRY; CALCULATING; CHEMISTRY; COMPOSITIONS OR TEST PAPERS THEREFOR; COMPUTING; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; ENZYMOLOGY; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS; METALLURGY; MICROBIOLOGY; MUTATION OR GENETIC ENGINEERING; PHYSICS; PROCESSES OF PREPARING SUCH COMPOSITIONS; PROCESSES USING MICROORGANISMS; SPIRITS; VINEGAR; WINE

The invention belongs to the technical field of cell growth analysis, and particularly relates to a cell growth analysis method based on spectral clustering and single cell Raman spectroscopy, which comprises the following steps: collecting microbial SCRS data at different growth times under a synchronous culture condition, and preprocessing the microbial SCRS data; performing visual analysis on the preprocessed SCRS data by applying a t-SNE algorithm, guiding spectral clustering to perform clustering analysis on the high-dimensional SCRS data, evaluating an optimal cluster by applying a contour coefficient and a CH coefficient, and endowing each SCRS data cluster with a label; and carrying out fitting statistics on the intersection of the SCRS data cluster tag and the growth period tag by using cubic spline interpolation, identifying growth period heterogeneous data coexisting in the population, and carrying out accurate identification on the growth period of the single-cell microorganisms. Through accurate