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

Structure-based calculation of excipient effects on the viscosity of concentrated antibody solutions

基于结构的赋形剂对浓缩抗体溶液粘度影响的计算

Shelley, John C; Chai, Qing; Wu, Lina; Vafaei, Shaghayegh; Shelley, Mee Y; Feyfant, Eric; Feng, Jiangyan; Woldeyes, Mahlet A; Babin, Volodymyr; Jou, Jonathan D

Growth of Clusters toward Liquid-Liquid Phase Separation of Monoclonal Antibodies as Characterized by Small-Angle X-ray Scattering and Molecular Dynamics Simulation

利用小角X射线散射和分子动力学模拟表征单克隆抗体液-液相分离过程中团簇的生长

Kimball, William D; Lanzaro, Alfredo; Hurd, Christian; Jhaveri, Neel; Huang, Jintian; Lewandowski, Joshua; Qian, Ken K; Woldeyes, Mahlet A; Majumdar, Ranajoy; Witek, Marta A; Feng, Jiangyan; Gillilan, Richard E; Huang, Qingqiu; Marras, Alexander E; Truskett, Thomas M; Johnston, Keith P

ESMDynamic: Fast and Accurate Prediction of Protein Dynamic Contact Maps from Single Sequences

ESMDynamic:基于单序列快速准确地预测蛋白质动态接触图

Kleiman, Diego E; Feng, Jiangyan; Xue, Zhengyuan; Shukla, Diwakar

How minor sequence changes enable mechanistic diversity in MFS transporters? An atomic-level rationale for symport emergence in NarU

微小的序列变化如何导致MFS转运蛋白的机制多样性?NarU中同向转运的出现机制的原子级解释

Dean, Tanner J; Feng, Jiangyan; Shukla, Diwakar

Predicting the clinical subcutaneous absorption rate constant of monoclonal antibodies using only the primary sequence: a machine learning approach

仅使用一级序列预测单克隆抗体的临床皮下吸收速率常数:一种机器学习方法

Bei, Ronghua; Thomas, Justin; Kapur, Shiven; Woldeyes, Mahlet; Rauk, Adam; Robarge, Jason; Feng, Jiangyan; Abbou Oucherif, Kaoutar

Antibody apparent solubility prediction from sequence by transfer learning.

利用迁移学习从序列预测抗体表观溶解度

Feng Jiangyan, Jiang Min, Shih James, Chai Qing

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

三十年来对蛋白质翻译后修饰的分子动力学模拟

Weigle, Austin T; Feng, Jiangyan; Shukla, Diwakar