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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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초록· 키워드
오류제보하기
프로테오믹스(Proteomics)는 단백질 동정(Protein Identification)을 통해 단백질의 서열과 구조를 분석함으로써 단백질의 기능을 연구하는 학문이다. 단백질 동정은 단백질을 펩타이드로 분해하고 이를 질량 분석기를 이용하여 질량 스펙트럼을 분석하는 것이다. 이 때, Peak Picking 과정을 거치면 질량 스펙트럼에서 노이즈(Noise)를 제거하고 의미 있는 Peak를 추출하여 효율적인 단백질 동정을 수행할 수 있다.
Peak Picking을 효율적으로 하기 위한 방법으로는 Smoothing을 하는 것이다. Peak Picking을 수행하기 전에 질량 스펙트럼을 Smoothing하면, 불규칙한 패턴을 가진 스펙트럼 데이터를 평준화하여 Centroiding 할 수 있기 때문에 단백질 동정을 더 빠르게 수행할 수 있다. 널리 사용되는 Smoothing 알고리즘으로는 Moving Average Smoothing이다.
하지만 Moving Average Smoothing을 수행한 후 Peak Picking을 하게 될 경우, 하나의 Distribution에서 Peak가 많이 선택되는 문제가 있다. 또한, 원래의 Peak Intensity를 보존하지 못한다는 문제가 발생한다.
따라서 본 논문에서는 이러한 Moving Average Smoothing의 문제점을 해결하기 위해 HY Smoothing 알고리즘을 제안하였다. HY Smoothing 알고리즘은 Distribution을 분할하여 Centroiding을 수행하는 방식이다. HY Smoothing 알고리즘을 실험한 결과, 기존의 Decon2ls의 Centroiding이나 Moving Average Smoothing 방법에 비해 원래의 Peak Intensity를 잘 반영하였으며 Multiple Peak Centroided의 수를 절반 이하로 줄여 정확도가 향상된 것을 보였다.
Peak Picking을 효율적으로 하기 위한 방법으로는 Smoothing을 하는 것이다. Peak Picking을 수행하기 전에 질량 스펙트럼을 Smoothing하면, 불규칙한 패턴을 가진 스펙트럼 데이터를 평준화하여 Centroiding 할 수 있기 때문에 단백질 동정을 더 빠르게 수행할 수 있다. 널리 사용되는 Smoothing 알고리즘으로는 Moving Average Smoothing이다.
하지만 Moving Average Smoothing을 수행한 후 Peak Picking을 하게 될 경우, 하나의 Distribution에서 Peak가 많이 선택되는 문제가 있다. 또한, 원래의 Peak Intensity를 보존하지 못한다는 문제가 발생한다.
따라서 본 논문에서는 이러한 Moving Average Smoothing의 문제점을 해결하기 위해 HY Smoothing 알고리즘을 제안하였다. HY Smoothing 알고리즘은 Distribution을 분할하여 Centroiding을 수행하는 방식이다. HY Smoothing 알고리즘을 실험한 결과, 기존의 Decon2ls의 Centroiding이나 Moving Average Smoothing 방법에 비해 원래의 Peak Intensity를 잘 반영하였으며 Multiple Peak Centroided의 수를 절반 이하로 줄여 정확도가 향상된 것을 보였다.
목차
국문요지 ········································································································································· Ⅳ제 1장 서 론 ···································································································································· 1제 2장 관련연구 ······························································································································ 3제 1절 Amino acid, Peptide, Protein ··············································································· 3제 2절 Mass Spectrometry ·································································································· 6제 3절 Peptide Identification ······························································································ 9제 3장 Peak Picking ·················································································································· 10제 1절 Pick Picking 소개 ··································································································· 10제 2절 Decon2ls Centroiding ···························································································· 11제 3절 Moving Average Smoothing ··············································································· 13제 4절 Moving Average Smoothing의 문제점 ····························································· 14제 4장 HY smoothing 알고리즘 ······························································································ 15제 1절 HY Smoothing 알고리즘 소개 ·············································································· 15제 2절 HY Smoothing 알고리즘 수행과정 ······································································ 16제 3절 HY Smoothing 알고리즘 성능 ·············································································· 18제 5장 실 험 ································································································································· 19제 1절 실험 환경 ··················································································································· 20제 2절 실험 데이터 ··············································································································· 22제 3절 수행시간 비교 및 정확도 분석 ············································································· 23제 6장 결 론 ································································································································· 28참고 문헌 ······································································································································ 29
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