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Informatics for protein identification by tandem mass spectrometry; Focused on two most-widely applied algorithms, Mascot and SEQUEST
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  • Informatics for protein identification by tandem mass spectrometry; Focused on two most-widely applied algorithms, Mascot and SEQUEST
  • Informatics for protein identification by tandem mass spectrometry; Focused on two most-widely applied algorithms, Mascot and SEQUEST
저자명
Sohn. Chang-Ho,Jung. Jin-Woo,Kang. Gum-Yong,Kim. Kwang-Pyo
간행물명
Bioinformatics and Biosystems
권/호정보
2006년|1권 2호|pp.89-94 (6 pages)
발행정보
한국생물정보시스템생물학회
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정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Mass spectrometry (MS) is widely applied for high throughput proteomics analysis. When large-scale proteome analysis experiments are performed, it generates massive amount of data. To search these proteomics data against protein databases, fully automated database search algorithms, such as Mascot and SEQUEST are routinely employed. At present, it is critical to reduce false positives and false negatives during such analysis. In this review we have focused on aspects of automated protein identification using tandem mass spectrometry (MS/MS) spectra and validation of the protein identifications of two most common automated protein identification algorithms Mascot and SEQUEST.