Research Article
A Bipartite Graph Based Model of Protein Domain Networks
@INPROCEEDINGS{10.1007/978-3-642-02466-5_50, author={J. Nacher and T. Ochiai and M. Hayashida and T. Akutsu}, title={A Bipartite Graph Based Model of Protein Domain Networks}, proceedings={Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1}, proceedings_a={COMPLEX PART 1}, year={2012}, month={5}, keywords={Growing networks protein domains scale-free networks}, doi={10.1007/978-3-642-02466-5_50} }- J. Nacher
T. Ochiai
M. Hayashida
T. Akutsu
Year: 2012
A Bipartite Graph Based Model of Protein Domain Networks
COMPLEX PART 1
Springer
DOI: 10.1007/978-3-642-02466-5_50
Abstract
Proteins are essential molecules of life in the cell and are involved in multiple and highly specialized tasks encoded in the amino acid sequence. In particular, protein function is closely related to fundamental units of protein structure called . Here, we investigate the distribution of kinds of domains in human cells. Our findings show that while the number of domain types shared by proteins follows a scale-free distribution, the number of proteins composed of types of domains decays as an exponential distribution. In contrast, previous data analyses and mathematical modeling reported a scale-free distribution for the protein domain distribution because the relation between kinds of domains and the number of domains in a protein was not considered. Based on this finding, we have developed an evolutionary model based on (1) growth process and (2) copy mechanism that explains the emergence of this mixing of exponential and scale-free distributions.
