Teaching Case Study in Discrete Mathematics: Application of Clustering Algorithms in Brucella Traceability Research

Abstract

In this study, we combined discrete mathematics with computational biology to identify Brucella species using clustering algorithms. By analyzing the Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) spectra of 44 Brucella isolates, which included 21 Brucella melitensis, 12 Brucella suis, and 11 Brucella abortus, we utilized a feature selection strategy to pinpoint 22 key characteristics critical for species differentiation. We then developed a spectral clustering-based model for Brucella traceability. This model offers a rapid and cost-effective alternative to traditional, labor-intensive identification methods, significantly improving the efficiency and accuracy of Brucella strain identification. Additionally, it aids in monitoring disease transmission trends, identifying outbreak sources, and formulating effective control strategies to mitigate risks. Our findings demonstrate the practical application of discrete mathematics in computational biology, contributing significantly to both scientific research and educational methodologies. This approach illustrates how mathematical concepts can be effectively applied to solve real-world biological problems, providing valuable insights for future interdisciplinary studies and innovative solutions.

Received: 10 April 2024 | Revised: 19 November 2024 | Accepted: 16 December 2024

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

This study utilized publicly available data, reference [14], and no new data were generated.

Author Contribution Statement

Jiqing Gu: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft, Writing – review & editing. Jing Hu: Funding acquisition. Ju Huang: Software. Hui Yang: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.