Name
Abstract | ||
|---|---|---|
Proteins in organisms usually form protein complexes to perform cellular
functions rather than act alone. We represent the topological network structure
of protein complexes and their component proteins in the budding yeast in terms
of the bipartite network and its projections, where the complexes and proteins
are its two distinct components. Statistical properties of those networks are
compared to those of conventional protein-protein interaction networks, and it
turns out that the networks from the protein complexes show more homogeneous
structures than the binary protein interactions, which implies the formation of
complexes causing relatively more uniform numbers of interaction partners. In
addition, we suggest a new optimization method to determine the abundance and
function of protein complexes based on the information of their global
organization. Estimating abundance and biological functions is of great
importance, by giving much more quantitative description of behaviors in a cell
than just "catalogues" of list of protein interactions, for researches such as
kinetic modeling of the cell in the future. With our new optimization method,
we present genome-wide assignments of abundance and biological functions for
complexes, as well as previously unknown abundance and functions of proteins,
which can provide significant information for further investigations in
proteomics. It is strongly supported by a number of biologically relevant
examples, such as the relationship between the cytoskeleton proteins and signal
transduction and the metabolic enzyme Eno2's involvement in the cell division
process. We believe that our methods and findings are applicable not only to
the specific area of proteomics, but also to much broader areas of systems
biology with the concept of optimization principle. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1186/1752-0509-5-126 | BMC systems biology |
Keywords | DocType | Volume |
Core Protein, Degree Distribution, Function Assignment, Projection Network, Attachment Protein | Journal | 5 |
Issue | ISSN | Citations |
1 | 1752-0509 | 3 |
PageRank | References | Authors |
0.43 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sang Hoon Lee | 1 | 88 | 24.05 |
| Pan-Jun Kim | 2 | 28 | 4.06 |
| Hawoong Jeong | 3 | 988 | 190.47 |