Title |
Comparative analysis of differential network modularity in tissue specific normal and cancer protein interaction networks
|
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Published in |
Journal of Clinical Bioinformatics, October 2013
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DOI | 10.1186/2043-9113-3-19 |
Pubmed ID | |
Authors |
Md Fahmid Islam, Md Moinul Hoque, Rajat Suvra Banik, Sanjoy Roy, Sharmin Sultana Sumi, F M Nazmul Hassan, Md Tauhid Siddiki Tomal, Ahmad Ullah, K M Taufiqur Rahman |
Abstract |
Large scale understanding of complex and dynamic alterations in cellular and subcellular levels during cancer in contrast to normal condition has facilitated the emergence of sophisticated systemic approaches like network biology in recent times. As most biological networks show modular properties, the analysis of differential modularity between normal and cancer protein interaction networks can be a good way to understand cancer more significantly. Two aspects of biological network modularity e.g. detection of molecular complexes (potential modules or clusters) and identification of crucial nodes forming the overlapping modules have been considered in this regard. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 3% |
Korea, Republic of | 1 | 3% |
Saudi Arabia | 1 | 3% |
Unknown | 30 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 6 | 18% |
Student > Ph. D. Student | 5 | 15% |
Student > Master | 5 | 15% |
Student > Bachelor | 3 | 9% |
Professor > Associate Professor | 2 | 6% |
Other | 6 | 18% |
Unknown | 6 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 10 | 30% |
Biochemistry, Genetics and Molecular Biology | 5 | 15% |
Computer Science | 5 | 15% |
Social Sciences | 2 | 6% |
Unspecified | 1 | 3% |
Other | 3 | 9% |
Unknown | 7 | 21% |