日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Non-Reducing Proteomics Reveals Disulfide-dependent Proteoform Remodeling Under Oxidative Stress.

非还原性蛋白质组学揭示氧化应激下二硫键依赖性蛋白质异构体重塑。

Lee Yeonjoo, Kim Tae-Kyung, Na Seungjin, Lee Kong-Joo, Jeong Jaeho, Song Eun Joo

CyGate Provides a Robust Solution for Automatic Gating of Single Cell Cytometry Data

CyGate 为单细胞流式细胞术数据的自动设门提供了一种强大的解决方案

Na, Seungjin; Choo, Yujin; Yoon, Tae Hyun; Paek, Eunok

DbyDeep: Exploration of MS-Detectable Peptides via Deep Learning

DbyDeep:利用深度学习探索质谱可检测肽段

Son, Juho; Na, Seungjin; Paek, Eunok

TIDD: tool-independent and data-dependent machine learning for peptide identification

TIDD:一种用于肽段鉴定的工具无关、数据相关的机器学习方法

Li, Honglan; Na, Seungjin; Hwang, Kyu-Baek; Paek, Eunok

Computational methods in mass spectrometry-based structural proteomics for studying protein structure, dynamics, and interactions

基于质谱的结构蛋白质组学中的计算方法,用于研究蛋白质的结构、动力学和相互作用。

Na, Seungjin; Paek, Eunok

Advanced Proteogenomic Analysis Reveals Multiple Peptide Mutations and Complex Immunoglobulin Peptides in Colon Cancer

先进的蛋白质基因组学分析揭示结肠癌中多种肽突变和复杂的免疫球蛋白肽

Woo, Sunghee; Cha, Seong Won; Bonissone, Stefano; Na, Seungjin; Tabb, David L; Pevzner, Pavel A; Bafna, Vineet

Characterization of disulfide bonds by planned digestion and tandem mass spectrometry

利用计划消解和串联质谱法对二硫键进行表征

Na, Seungjin; Paek, Eunok; Choi, Jong-Soon; Kim, Duwoon; Lee, Seung Jae; Kwon, Joseph

Proteogenomic strategies for identification of aberrant cancer peptides using large-scale next-generation sequencing data

利用大规模新一代测序数据鉴定异常癌症肽的蛋白质组学策略

Woo, Sunghee; Cha, Seong Won; Na, Seungjin; Guest, Clark; Liu, Tao; Smith, Richard D; Rodland, Karin D; Payne, Samuel; Bafna, Vineet

Fast multi-blind modification search through tandem mass spectrometry

利用串联质谱法进行快速多盲修饰搜索

Na, Seungjin; Bandeira, Nuno; Paek, Eunok

High-throughput peptide quantification using mTRAQ reagent triplex

利用 mTRAQ 试剂三联体进行高通量肽定量

Yoon, Joo Young; Yeom, Jeonghun; Lee, Heebum; Kim, Kyutae; Na, Seungjin; Park, Kunsoo; Paek, Eunok; Lee, Cheolju