Proteomics Approaches in Distinguishing the Hippocampus Abdominalis and Hippocampus Erectus
Hippocampus abdominalis and Hippocampus erectus are two varieties with similar appearance in the market. However, the accuracy of distinguishing two varieties based on morphology largely relies on experience and the unique shape. Distinguishing them based on proteomic differences seems to be an effective method, but it is difficult to establish an accurate connection between the proteins identified in two varieties respectively. Moreover, the identification efficiency is heavily depend on the quality of assembled genomes. Therefore, how to select a variety-specific proteome to identify all the peptides and proteins is urgently to be addressed. In this study, a cross-identification method is proposed to make a decision of proteome selection by comparing the identification efficiency between different protein sequence datasets. The number of peptides and proteins is significantly different, and the expression levels of proteins are calculated and functionally annotated using bioinformatics tools. The obvious difference of protein expression between the two varieties has been demonstrated by computing the Pearson correlation coefficient of all identified proteins. Experimental results show that a proteome analysis combined with a cross-identification method is capable of detecting the difference between H. abdominalis and H. erectus to accurately distinguish the two varieties.
Authors
- Jianhang Zhang
- Bowen Ma
- Hui Xu
- Jie Sun
- Ziwei Li (ORCID: https://orcid.org/0009-0009-1923-1611)
- Xianjun Fu (ORCID: https://orcid.org/0000-0002-9399-4635)
Institutions
- Shandong University of Traditional Chinese Medicine (CN)
- Harbin Engineering University (CN)
- Shandong Academy of Chinese Medicine (CN)
Publication Details
- Published
- 2025-01-10
- DOI
- https://doi.org/10.1145/3724979.3725037
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China