Comparison of Hubs in Effective Normal and Tumor Protein Interaction Networks

ABSTRACTIntroduction: Cancer is caused by genetic abnormalities, such as mutation of ontogenesis or tumor suppressor genes which alter downstream signaling pathways and protein-protein interactions. Comparison of protein interactions in cancerous and normal cells can be of help in mechanisms of dise...

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Main Authors: Mitra Mirzarezaee, Babak N. Araabi, Mehdi Sadeghi
Format: Article
Language:English
Published: Iran University of Medical Sciences 2010-11-01
Series:Basic and Clinical Neuroscience
Subjects:
Online Access:http://bcn.iums.ac.ir/browse.php?a_code=A-10-2-9&slc_lang=en&sid=1
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spelling doaj-d0cee8c40ed044de9dd00e090861dbb72020-11-25T00:21:53ZengIran University of Medical SciencesBasic and Clinical Neuroscience2008-126X2228-74422010-11-01214450Comparison of Hubs in Effective Normal and Tumor Protein Interaction NetworksMitra Mirzarezaee0Babak N. Araabi1Mehdi Sadeghi2 ABSTRACTIntroduction: Cancer is caused by genetic abnormalities, such as mutation of ontogenesis or tumor suppressor genes which alter downstream signaling pathways and protein-protein interactions. Comparison of protein interactions in cancerous and normal cells can be of help in mechanisms of disease diagnoses and treatments. Methods: We constructed protein interaction networks of cancerous and normal cells. These protein interaction networks are constructed using gene-expression profiles measured from different samples of cancerous and normal tissues from four different parts of the body including colon, prostate, lung, and central nervous system. We used pattern recognition techniques to construct these networks. We calculated ten graph related parameters including closeness centrality, graph diameter, index of aggregation, entropy of edge distribution, connectivity, number of edges divided by the number of vertices, entropy, graph centrality, sum of the wiener number, and modified vertex distance numbers for each of the cancerous and normal protein interaction networks. We have also compared number of edges and hubs of the both cancerous and normal resultant protein interaction networks. Results and Discussion: Our results show that in the studied tissue samples, effective normal protein interaction networks are denser in number of edges and hubs compared with their corresponding effective cancerous protein interaction networks. Number of hubs in effective cancerous protein interaction networks decreases dramatically in comparison with normal tissues. This can be used as a symptom for identification of cancerous tissues.http://bcn.iums.ac.ir/browse.php?a_code=A-10-2-9&slc_lang=en&sid=1CancerProtein InteractionNetwork.
collection DOAJ
language English
format Article
sources DOAJ
author Mitra Mirzarezaee
Babak N. Araabi
Mehdi Sadeghi
spellingShingle Mitra Mirzarezaee
Babak N. Araabi
Mehdi Sadeghi
Comparison of Hubs in Effective Normal and Tumor Protein Interaction Networks
Basic and Clinical Neuroscience
Cancer
Protein Interaction
Network.
author_facet Mitra Mirzarezaee
Babak N. Araabi
Mehdi Sadeghi
author_sort Mitra Mirzarezaee
title Comparison of Hubs in Effective Normal and Tumor Protein Interaction Networks
title_short Comparison of Hubs in Effective Normal and Tumor Protein Interaction Networks
title_full Comparison of Hubs in Effective Normal and Tumor Protein Interaction Networks
title_fullStr Comparison of Hubs in Effective Normal and Tumor Protein Interaction Networks
title_full_unstemmed Comparison of Hubs in Effective Normal and Tumor Protein Interaction Networks
title_sort comparison of hubs in effective normal and tumor protein interaction networks
publisher Iran University of Medical Sciences
series Basic and Clinical Neuroscience
issn 2008-126X
2228-7442
publishDate 2010-11-01
description ABSTRACTIntroduction: Cancer is caused by genetic abnormalities, such as mutation of ontogenesis or tumor suppressor genes which alter downstream signaling pathways and protein-protein interactions. Comparison of protein interactions in cancerous and normal cells can be of help in mechanisms of disease diagnoses and treatments. Methods: We constructed protein interaction networks of cancerous and normal cells. These protein interaction networks are constructed using gene-expression profiles measured from different samples of cancerous and normal tissues from four different parts of the body including colon, prostate, lung, and central nervous system. We used pattern recognition techniques to construct these networks. We calculated ten graph related parameters including closeness centrality, graph diameter, index of aggregation, entropy of edge distribution, connectivity, number of edges divided by the number of vertices, entropy, graph centrality, sum of the wiener number, and modified vertex distance numbers for each of the cancerous and normal protein interaction networks. We have also compared number of edges and hubs of the both cancerous and normal resultant protein interaction networks. Results and Discussion: Our results show that in the studied tissue samples, effective normal protein interaction networks are denser in number of edges and hubs compared with their corresponding effective cancerous protein interaction networks. Number of hubs in effective cancerous protein interaction networks decreases dramatically in comparison with normal tissues. This can be used as a symptom for identification of cancerous tissues.
topic Cancer
Protein Interaction
Network.
url http://bcn.iums.ac.ir/browse.php?a_code=A-10-2-9&slc_lang=en&sid=1
work_keys_str_mv AT mitramirzarezaee comparisonofhubsineffectivenormalandtumorproteininteractionnetworks
AT babaknaraabi comparisonofhubsineffectivenormalandtumorproteininteractionnetworks
AT mehdisadeghi comparisonofhubsineffectivenormalandtumorproteininteractionnetworks
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