Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Sumeyye Su"'
Publikováno v:
SoftwareX, Vol 18, Iss , Pp 101072- (2022)
There are many experimental methods for characterizing immune profiles of tumors, such as flow and mass cytometry. However, these approaches are time and resource intensive. Thus, several “digital cytometry” methods have been developed to extract
Externí odkaz:
https://doaj.org/article/8c6a61dffffb42238fb2aae6b19e0a31
Publikováno v:
Mathematical Biosciences and Engineering, Vol 18, Iss 2, Pp 1879-1897 (2021)
Tumor immune microenvironment has been shown to be important in predicting the tumor progression and the outcome of treatments. This work aims to identify different immune patterns in osteosarcoma and their clinical characteristics. We use the latest
Externí odkaz:
https://doaj.org/article/223f2d3220d743309b86840a33a6934f
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract Since the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytome
Externí odkaz:
https://doaj.org/article/1f1588e959d940e1b678b1fd5a2615fc
Autor:
Navid Mohammad Mirzaei, Navid Changizi, Alireza Asadpoure, Sumeyye Su, Dilruba Sofia, Zuzana Tatarova, Ioannis K Zervantonakis, Young Hwan Chang, Leili Shahriyari
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 3, p e1009953 (2022)
The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven math
Externí odkaz:
https://doaj.org/article/122095f35a6449aaaa3bbaf5e59e4063
Autor:
Sumeyye Su, Leili Shahriyari
Publikováno v:
Royal Society Open Science, Vol 7, Iss 4 (2020)
Recent advances in biotechnology led to generation of large complex biological and clinical datasets that can be used to infer the underlying mechanism of many diseases and arrive at personalized treatments. One of these datasets are the whole genome
Externí odkaz:
https://doaj.org/article/2c71b3bb72684ef993d8a8f978dc2187
Publikováno v:
Cells, Vol 10, Iss 8, p 2009 (2021)
Since all tumors are unique, they may respond differently to the same treatments. Therefore, it is necessary to study their characteristics individually to find their best treatment options. We built a mathematical model for the interactions between
Externí odkaz:
https://doaj.org/article/a12c56fc8fe0458687d5079008bd80f0
Publikováno v:
Mathematical Biosciences and Engineering, Vol 18, Iss 2, Pp 1879-1897 (2021)
Mathematical biosciences and engineering : MBE
Mathematical biosciences and engineering : MBE
Tumor immune microenvironment has been shown to be important in predicting the tumor progression and the outcome of treatments. This work aims to identify different immune patterns in osteosarcoma and their clinical characteristics. We use the latest
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66bfbb05981f196a8d3c3ea58813e4b1
http://www.aimspress.com/article/doi/10.3934/mbe.2021098?viewType=HTML
http://www.aimspress.com/article/doi/10.3934/mbe.2021098?viewType=HTML
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Scientific Reports
Scientific Reports
Since the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a355a296ef45c156609649bb2c02157
https://doaj.org/article/1f1588e959d940e1b678b1fd5a2615fc
https://doaj.org/article/1f1588e959d940e1b678b1fd5a2615fc
Autor:
Navid Mohammad Mirzaei, Navid Changizi, Alireza Asadpoure, Sumeyye Su, Dilruba Sofia, Zuzana Tatarova, Ioannis K. Zervantonakis, Young Hwan Chang, Leili Shahriyari
Publikováno v:
PLoS computational biology. 18(3)
The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven math
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a227e164811f8e5fa98e9c0f6bfe017f
https://pubmed.ncbi.nlm.nih.gov/35294447
https://pubmed.ncbi.nlm.nih.gov/35294447
Autor:
Adrian V. Lee, Ioannis K. Zervantonakis, Zuzana Tatarova, Sumeyye Su, Navid Mohammad Mirzaei, Leili Shahriyari, Wenrui Hao, Mohamed H. Abdel-Rahman, Pamela R. Jackson, Daniel G. Stover, Maura Hegarty, Colleen M. Cebulla, Dilruba Sofia, Young Hwan Chang, Alireza Asadpoure
Publikováno v:
Journal of Personalized Medicine, Vol 11, Iss 1031, p 1031 (2021)
Journal of Personalized Medicine
Volume 11
Issue 10
Journal of Personalized Medicine
Volume 11
Issue 10
Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76926ad36c85081e9ca82f98bba3fc54
https://www.mdpi.com/2075-4426/11/10/1031
https://www.mdpi.com/2075-4426/11/10/1031