Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Ghareyazi Amin"'
Autor:
Yahyazadeh Hossein, Mafi Ahmad Rezazadeh, Beheshti Marzieh, Ghareyazi Amin, Abdollahinejad Azita, Tahbaz Sahel Valadan
Publikováno v:
Forum of Clinical Oncology, Vol 13, Iss 1, Pp 9-14 (2023)
The presence of lymph node metastasis is one of the most important prognostic factors for long-term survival of patients with colorectal cancer. Therefore, thorough pathologic examination of at least 12 lymph nodes is essential for accurate staging o
Externí odkaz:
https://doaj.org/article/a69638ae9d814260b87e50278df11434
Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a system
Externí odkaz:
http://arxiv.org/abs/2405.08031
The protein-ligand binding affinity (PLA) prediction goal is to predict whether or not the ligand could bind to a protein sequence. Recently, in PLA prediction, deep learning has received much attention. Two steps are involved in deep learning-based
Externí odkaz:
http://arxiv.org/abs/2405.07452
Autor:
Mohammadzadeh-Vardin, Taha1 (AUTHOR), Ghareyazi, Amin1 (AUTHOR), Gharizadeh, Ali1 (AUTHOR), Abbasi, Karim1,2 (AUTHOR) karim.abbasi@ut.ac.ir, Rabiee, Hamid R.1 (AUTHOR) karim.abbasi@ut.ac.ir
Publikováno v:
PLoS ONE. 7/26/2024, Vol. 19 Issue 7, p1-18. 18p.
Autor:
Ghareyazi, Amin1 (AUTHOR), Kazemi, Amirreza1,2 (AUTHOR), Hamidieh, Kimia3 (AUTHOR), Dashti, Hamed1 (AUTHOR), Tahaei, Maedeh Sadat1 (AUTHOR), Rabiee, Hamid R.1 (AUTHOR) rabiee@sharif.edu, Alinejad-Rokny, Hamid4,5,6 (AUTHOR), Dehzangi, Iman7,8 (AUTHOR) i.dehzangi@rutgers.edu
Publikováno v:
BMC Bioinformatics. 7/25/2022, Vol. 23 Issue 1, p1-21. 21p.
Autor:
Ghareyazi, Amin, Kazemi, Amirreza, Hamidieh, Kimia, Dashti, Hamed, Tahaei, Maedeh Sadat, Rabiee, Hamid R., Alinejad-Rokny, Hamid, Dehzangi, Iman
Additional file 2: Fig. S1. Evaluation plots for finding optimal number of signatures. Fig. S2. Mutational load of feature genes in each cancer type. Fraction of samples that have mutated in each 684 candidate genes for all cancer types separately. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25c6d7ae8a71f5b4dc5466c98293557f
Akademický článek
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Autor:
Yahyazadeh, Hossein, Mafi, Ahmad Rezazadeh, Beheshti, Marzieh, Ghareyazi, Amin, Abdollahinejad, Azita, Tahbaz, Sahel Valadan
Publikováno v:
Forum of Clinical Oncology; 2022, Vol. 13 Issue 1, p9-14, 6p
Autor:
Gharizadeh A; Department of Computer Engineering, Sharif University of Technology, Tehran, P.O. Box 11155-9517, Iran., Abbasi K; Department of Computer Engineering, Sharif University of Technology, Tehran, P.O. Box 11155-9517, Iran., Ghareyazi A; Department of Computer Engineering, Sharif University of Technology, Tehran, P.O. Box 11155-9517, Iran., Mofrad MRK; Departments of Bioengineering and Mechanical Engineering, University of California, Berkeley, CA, P.O. Box 94720-1740, United States., Rabiee HR; Department of Computer Engineering, Sharif University of Technology, Tehran, P.O. Box 11155-9517, Iran.
Publikováno v:
Bioinformatics (Oxford, England) [Bioinformatics] 2024 Jul 01; Vol. 40 (7).