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

Toward next-generation machine learning and deep learning for spatial omics

面向下一代空间组学机器学习和深度学习

Zirem, Yanis; Fournier, Isabelle; Salzet, Michel

Epithelial-Mesenchymal Transition Shapes the Lipotoxic Response of Colon Cancer Cells to Palmitic Acid

上皮-间质转化影响结肠癌细胞对棕榈酸的脂毒性反应

Vari, Francesco; Serra, Ilaria; Bisconti, Elisa; Stanca, Eleonora; Raffo-Romero, Antonella; Mehenni, Sarah; Zirem, Yanis; Vergara, Daniele; Fournier, Isabelle; Giudetti, Anna Maria; Salzet, Michel

Profiler: an open web platform for multi-omics analysis

Profiler:一个用于多组学分析的开放式网络平台

Zirem, Yanis; Ledoux, Léa; Fournier, Isabelle; Salzet, Michel

Uncovering injury-specific proteomic signatures and neurodegenerative risks in single and repetitive traumatic brain injury

揭示单次和重复性创伤性脑损伤中损伤特异性蛋白质组学特征和神经退行性风险

Mantash, Sarah; Aboulouard, Soulaimane; Dakik, Hassan; Zirem, Yanis; Ziane-Chaouche, Lydia; Nehme, Ali; Mallah, Khalil; El-Kurdi, Marya; Ramadan, Naify; Fournier, Isabelle; Zibara, Kazem; Kobeissy, Firas; Salzet, Michel

SCarP: Proteome Heterogeneity Characterization of Primary Mouse Cardiomyocytes

SCarP:小鼠原代心肌细胞蛋白质组异质性表征

Chazarin, Blandine; Binek, Aleksandra; Janssens, Johannes V; Becker, Lindsey E; Kreimer, Simion; Haghani, Ali; Cantlon, Joshua; Pham, Janet; Hutton, Alexandre; Meyer, Jesse G; Krieger, Jonathan R; Zirem, Yanis; Karlstaedt, Anja; Van Eyk, Jennifer E

Predicting Protein Pathways Associated to Tumor Heterogeneity by Correlating Spatial Lipidomics and Proteomics: The Dry Proteomic Concept

通过关联空间脂质组学和蛋白质组学预测与肿瘤异质性相关的蛋白质通路:干蛋白质组学概念

Lagache, Laurine; Zirem, Yanis; Le Rhun, Émilie; Fournier, Isabelle; Salzet, Michel

Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management

SpiderMass 实时评估胶质母细胞瘤肿瘤微环境,以改善患者管理

Yanis Zirem, Léa Ledoux, Lucas Roussel, Claude Alain Maurage, Pierre Tirilly, Émilie Le Rhun, Bertrand Meresse, Gargey Yagnik, Mark J Lim, Kenneth J Rothschild, Marie Duhamel, Michel Salzet, Isabelle Fournier

Protocol to analyze 1D and 2D mass spectrometry data from glioblastoma tissues for cancer diagnosis and immune cell identification

用于分析胶质母细胞瘤组织中一维和二维质谱数据的方案,以进行癌症诊断和免疫细胞鉴定

Zirem, Yanis; Ledoux, Léa; Salzet, Michel; Fournier, Isabelle