Volume 10, Issue 4 (2019)
JMBS 2019, 10(4): 557-564 |
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Hekmati J, Alami A, Zahiri J. Constructing Hordeum vulgare Protein- Protein Interaction Network Based on Interolog Method. JMBS 2019; 10 (4) :557-564
URL: http://biot.modares.ac.ir/article-22-25562-en.html
URL: http://biot.modares.ac.ir/article-22-25562-en.html
1- Biotechnology Department, Agricultural Sciences Faculty, Guilan University, Gilan, Iran
2- Biophysics Department, Biological Sciences Faculty, Tarbiat Modares University, Tehran, Iran, Tarbiat Modares University, Nasr Bridge, Jalal-Al-Ahmad Highway, Tehran, Iran. Postal Code: 1411713116 , zahiri.j@gmail.com
2- Biophysics Department, Biological Sciences Faculty, Tarbiat Modares University, Tehran, Iran, Tarbiat Modares University, Nasr Bridge, Jalal-Al-Ahmad Highway, Tehran, Iran. Postal Code: 1411713116 , zahiri.j@gmail.com
Abstract: (6185 Views)
Hordeum vulgare is a one-year-old herb of the Poaceae family. It is an important cereal used by humans which has been applied in many cases instead of wheat. The limitation of experimental methods is one of the important problems for identifying protein-protein interactions. So, in recent years, computational methods have played an important role in predicting and identifying protein-protein interactions. In this study, for constructing protein-protein interaction (PPI) network, the experimental PPI information of six model organisms includes Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Homo sapiens, Oryza sativa, and Arabidopsis thalian were extracted from the Intact database. Inparanoid was used for identifying barley orthologous proteins with model organisms. The Interolog method which was used in this study can predict protein-protein interactions by mapping protein interactions of the model organisms on orthologous proteins. After removing repetitive interactions, the final predicted barley PPI network contained 235966 interactions between 7350 proteins. This study is the first report presented on protein-protein interaction prediction in barley.
Article Type: Qualitative Research |
Subject:
Bioinformatics
Received: 2018/10/19 | Accepted: 2019/02/10 | Published: 2019/12/21
Received: 2018/10/19 | Accepted: 2019/02/10 | Published: 2019/12/21
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