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

Kinome state is predictive of cell viability in pancreatic cancer tumor and cancer-associated fibroblast cell lines.

激酶组状态可预测胰腺癌肿瘤和癌症相关成纤维细胞系的细胞活力

Berginski Matthew E, Jenner Madison R, Joisa Chinmaya U, Herrera Loeza Gabriela, Golitz Brian T, Lipner Matthew B, Leary Jack R, Rashid Naim, Johnson Gary L, Yeh Jen Jen, Gomez Shawn M

Kinome inhibition states and multiomics data enable prediction of cell viability in diverse cancer types

激酶组抑制状态和多组学数据能够预测多种癌症类型的细胞活力

Berginski, Matthew E; Joisa, Chinmaya U; Golitz, Brian T; Gomez, Shawn M

Differential Performance of Machine Learning Models in Prediction of Procedure-Specific Outcomes

机器学习模型在预测特定手术结果方面的差异化性能

Chen, Kevin A; Berginski, Matthew E; Desai, Chirag S; Guillem, Jose G; Stem, Jonathan; Gomez, Shawn M; Kapadia, Muneera R

The Dark Kinase Knowledgebase: an online compendium of knowledge and experimental results of understudied kinases

暗激酶知识库:一个在线汇编了研究不足的激酶的知识和实验结果

Berginski, Matthew E; Moret, Nienke; Liu, Changchang; Goldfarb, Dennis; Sorger, Peter K; Gomez, Shawn M

Transcriptomic analyses of gastrulation-stage mouse embryos with differential susceptibility to alcohol

对酒精敏感性不同的原肠胚形成期小鼠胚胎进行转录组分析

Boschen, Karen E; Ptacek, Travis S; Berginski, Matthew E; Simon, Jeremy M; Parnell, Scott E

Coral: Clear and Customizable Visualization of Human Kinome Data

Coral:清晰且可定制的人类激酶组数据可视化

Metz, Kathleen S; Deoudes, Erika M; Berginski, Matthew E; Jimenez-Ruiz, Ivan; Aksoy, Bulent Arman; Hammerbacher, Jeff; Gomez, Shawn M; Phanstiel, Douglas H

The Focal Adhesion Analysis Server: a web tool for analyzing focal adhesion dynamics

黏着斑分析服务器:用于分析黏着斑动力学的网络工具

Berginski, Matthew E; Gomez, Shawn M