earticle

논문검색

Abstracts for poster Presentation

Web based IQ-GPA Cloud Computing System for Glycoproteomics

초록

영어

We have developed GlycoProteomeAnalyzer (GPA) for high throughput identification and quantification of N- and O-glycoproteins. GPA is a program for automatic identification of the glycan compositions and glycopeptide sequences by using three different scoring systems such as M-score for glycopeptide selection from oxonium-ions, S-score for theoretical isotope pattern match of molecular ion, and Y-score for glycopeptide identification from MS/MS fragmentation.[1] We here present the IQ-GPA Cloud which is a web based GPA application for automatic identification and quantification of site-specific N- and O-glycoproteins. IQ-GPA Cloud is a publicly accessible web application that enables users to quickly provision on-demand infrastructures for high-performance gylcoproteome analysis using Microsoft Azure cloud platforms. Users have instant access to a range of a glycan database builder as well as Nand O-GPA modules. IQ-GPA Cloud has been designed to easily handle high-throughput glycoproteomic data with graphical user interfaces. Microsoft Azure Cloud provides more than thousands of CPU to increase throughput of data analysis. Therefore, users can use glycoproteome analysis easily through IQ-GPA Cloud without any high-powered computer. The IQ-GPA Cloud is demonstrated on the website, https://cloud.igpa.kr/

저자정보

  • Young-Mook Kang Department of Mass Spectrometry, Korea Basic Science Institute, Ochang, Cheongju, Republic of Korea
  • Gun Wook Park Department of Mass Spectrometry, Korea Basic Science Institute, Ochang, Cheongju, Republic of Korea Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, Republic of Korea
  • Hyun Kyoung Lee Department of Mass Spectrometry, Korea Basic Science Institute, Ochang, Cheongju, Republic of Korea Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, Republic of Korea
  • Ju Yeon Lee Department of Mass Spectrometry, Korea Basic Science Institute, Ochang, Cheongju, Republic of Korea
  • Jin Young Kim Department of Mass Spectrometry, Korea Basic Science Institute, Ochang, Cheongju, Republic of Korea
  • Jong Shin Yoo Department of Mass Spectrometry, Korea Basic Science Institute, Ochang, Cheongju, Republic of Korea Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, Republic of Korea

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.