ArticleFrontiers in microbiology2020
Creation of an Online Platform for Identification of Microorganisms: Peak Picking or Full-Spectrum Analysis.
Article in Frontiers in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Benchmarking deep learning architectures for MALDI-TOF mass spectrometry in infectious disease diagnostics and vector-borne disease surveillance.NPJ digital medicine · 2026Article
- Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder.Journal of integrative bioinformatics · 2023Article
- Performance of MALDI-TOF Mass Spectrometry in the Philippines.Tropical medicine and infectious disease · 2021Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Identification of microorganisms by MALDI-TOF mass spectrometry is a very efficient method with high throughput, speed, and accuracy. However, it is significantly limited by the absence of a universal database of reference mass spectra. This problem can be solved by creating an Internet platform for open databases of protein spectra of microorganisms. Choosing the optimal mathematical apparatus is the pivotal issue for this task. In our previous study we proposed the geometric approach for processing mass spectrometry data, which represented a mass spectrum as a vector in a multidimensional Euclidean space. This algorithm was implemented in a Jacob4 stand-alone package. We demonstrated its efficiency in delimiting two closely related species of the
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