C-SEQer: An Open-Source de Novo Glycan Identification Tool in C++
| Autor: | Rob Smith, Christopher Burgoyne |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Glycan
biology Computer science General Chemistry Computational biology Python (programming language) Proteomics Biochemistry Bottleneck Glycoproteomics Glycomics Identification (information) Polysaccharides Tandem Mass Spectrometry biology.protein MIT License computer Algorithms computer.programming_language |
| Zdroj: | Journal of Proteome Research. 20:4068-4074 |
| ISSN: | 1535-3907 1535-3893 |
| DOI: | 10.1021/acs.jproteome.1c00379 |
| Popis: | Glycans play an important role in many biochemical processes, including protein function and cell signaling. Mass spectrometry (MS) provides the potential for high-throughput, high-sensitivity analysis of glycans but relies heavily on computational interpretation of experimental results. Open-source, stand-alone algorithms for de novo glycan MS analysis are few. One such algorithm, Sweet-SEQer, is available in Python. Glycan analysis of mass spectra can easily involve high volumes of data where Python's performance in time and memory is a noticeable bottleneck. This manuscript describes C-SEQer, a new implementation of the Sweet-SEQer algorithm in C++, which produces the same output as the original algorithm in approximately 15-fold less time with substantially less memory usage. The implementation is freely available with an MIT license. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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