Chapter title |
Detecting hierarchical modularity in biological networks.
|
---|---|
Chapter number | 7 |
Book title |
Computational Systems Biology
|
Published in |
Methods in molecular biology, April 2009
|
DOI | 10.1007/978-1-59745-243-4_7 |
Pubmed ID | |
Book ISBNs |
978-1-58829-905-5, 978-1-59745-243-4
|
Authors |
Ravasz E, Erzsébet Ravasz, Ravasz, Erzsébet |
Abstract |
Spatially or chemically isolated modules that carry out discrete functions are considered fundamental building blocks of cellular organization. However, detecting them in highly integrated biological networks requires a thorough understanding of the organization of these networks. In this chapter I argue that many biological networks are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units. On top of a scale-free degree distribution, these networks show a power law scaling of the clustering coefficient with the node degree, a property that can be used as a signature of hierarchical organization. As a case study, I identify the hierarchical modules within the Escherichia coli metabolic network, and show that the uncovered hierarchical modularity closely overlaps with known metabolic functions. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | 5% |
United Kingdom | 2 | 3% |
Hungary | 1 | 2% |
Sweden | 1 | 2% |
Unknown | 57 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 17 | 27% |
Student > Ph. D. Student | 16 | 25% |
Student > Doctoral Student | 5 | 8% |
Professor | 5 | 8% |
Student > Bachelor | 4 | 6% |
Other | 10 | 16% |
Unknown | 7 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 29 | 45% |
Computer Science | 7 | 11% |
Biochemistry, Genetics and Molecular Biology | 5 | 8% |
Engineering | 4 | 6% |
Medicine and Dentistry | 3 | 5% |
Other | 6 | 9% |
Unknown | 10 | 16% |