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

Accelerating antibody development: sequence and structure-based models for predicting developability properties via size exclusion chromatography

加速抗体开发:基于序列和结构的模型,利用尺寸排阻色谱法预测抗体的可开发性

Abeer, A N M Nafiz; Boroumand, Mehdi; Sermadiras, Isabelle; Caldwell, Jenna G; Stanev, Valentin; Mody, Neil; Kaplan, Gilad; Savery, James; Croasdale-Wood, Rebecca; Pouryahya, Maryam

Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learning

利用大规模粘度数据和集成深度学习加速高浓度单克隆抗体的开发

Kalejaye, Lateefat A; Chu, Jia-Min; Wu, I-En; Amofah, Bismark; Lee, Amber; Hutchinson, Mark; Chakiath, Chacko; Dippel, Andrew; Kaplan, Gilad; Damschroder, Melissa; Stanev, Valentin; Pouryahya, Maryam; Boroumand, Mehdi; Caldwell, Jenna; Hinton, Alison; Kreitz, Madison; Shah, Mitali; Gallegos, Austin; Mody, Neil; Lai, Pin-Kuang

AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases

基于人工智能的肝病临床试验入组标准和终点评估自动化

Iyer, Janani S; Juyal, Dinkar; Le, Quang; Shanis, Zahil; Pokkalla, Harsha; Pouryahya, Maryam; Pedawi, Aryan; Stanford-Moore, S Adam; Biddle-Snead, Charles; Carrasco-Zevallos, Oscar; Lin, Mary; Egger, Robert; Hoffman, Sara; Elliott, Hunter; Leidal, Kenneth; Myers, Robert P; Chung, Chuhan; Billin, Andrew N; Watkins, Timothy R; Patterson, Scott D; Resnick, Murray; Wack, Katy; Glickman, Jon; Burt, Alastair D; Loomba, Rohit; Sanyal, Arun J; Glass, Ben; Montalto, Michael C; Taylor-Weiner, Amaro; Wapinski, Ilan; Beck, Andrew H

Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH

整合基于深度学习的组织病理学和转录组学,揭示了晚期非酒精性脂肪性肝炎(NASH)患者纤维化发生相关的关键基因。

Conway, Jake; Pouryahya, Maryam; Gindin, Yevgeniy; Pan, David Z; Carrasco-Zevallos, Oscar M; Mountain, Victoria; Subramanian, G Mani; Montalto, Michael C; Resnick, Murray; Beck, Andrew H; Huss, Ryan S; Myers, Robert P; Taylor-Weiner, Amaro; Wapinski, Ilan; Chung, Chuhan

Pan-Cancer Prediction of Cell-Line Drug Sensitivity Using Network-Based Methods

基于网络的泛癌细胞系药物敏感性预测方法

Pouryahya, Maryam; Oh, Jung Hun; Mathews, James C; Belkhatir, Zehor; Moosmüller, Caroline; Deasy, Joseph O; Tannenbaum, Allen R

aWCluster: A Novel Integrative Network-Based Clustering of Multiomics for Subtype Analysis of Cancer Data

aWCluster:一种用于癌症数据亚型分析的多组学新型整合网络聚类方法

Pouryahya, Maryam; Oh, Jung Hun; Javanmard, Pedram; Mathews, James C; Belkhatir, Zehor; Deasy, Joseph O; Tannenbaum, Allen R

Reproducibility of radiomic features using network analysis and its application in Wasserstein k-means clustering

利用网络分析评估放射组学特征的可重复性及其在 Wasserstein k-means 聚类中的应用

Oh, Jung Hun; Apte, Aditya P; Katsoulakis, Evangelia; Riaz, Nadeem; Hatzoglou, Vaios; Yu, Yao; Mahmood, Usman; Veeraraghavan, Harini; Pouryahya, Maryam; Iyer, Aditi; Shukla-Dave, Amita; Tannenbaum, Allen; Lee, Nancy Y; Deasy, Joseph O

Functional network analysis reveals an immune tolerance mechanism in cancer

功能网络分析揭示了癌症中的免疫耐受机制

Mathews, James C; Nadeem, Saad; Pouryahya, Maryam; Belkhatir, Zehor; Deasy, Joseph O; Levine, Arnold J; Tannenbaum, Allen R

A novel kernel Wasserstein distance on Gaussian measures: An application of identifying dental artifacts in head and neck computed tomography

一种基于高斯测度的新型核Wasserstein距离:在头颈部计算机断层扫描中识别牙科伪影的应用

Oh, Jung Hun; Pouryahya, Maryam; Iyer, Aditi; Apte, Aditya P; Deasy, Joseph O; Tannenbaum, Allen

Robust and interpretable PAM50 reclassification exhibits survival advantage for myoepithelial and immune phenotypes

稳健且可解释的PAM50重新分类显示出肌上皮和免疫表型的生存优势

Mathews, James C; Nadeem, Saad; Levine, Arnold J; Pouryahya, Maryam; Deasy, Joseph O; Tannenbaum, Allen