scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/ploscb/HaseTSNK09 |
P356 | DOI | 10.1371/JOURNAL.PCBI.1000550 |
P932 | PMC publication ID | 2760708 |
P698 | PubMed publication ID | 19876376 |
P5875 | ResearchGate publication ID | 38054824 |
P50 | author | So Nakagawa | Q39068698 |
P2093 | author name string | Hiroshi Tanaka | |
Takeshi Hase | |||
Yasuhiro Suzuki | |||
Hiroaki Kitano | |||
P2860 | cites work | Towards a proteome-scale map of the human protein–protein interaction network | Q21735930 |
Scale-free networks in cell biology | Q22306161 | ||
A robustness-based approach to systems-oriented drug design | Q51062307 | ||
A network solution | Q53527430 | ||
Growing network with local rules: preferential attachment, clustering hierarchy, and degree correlations | Q73478873 | ||
Scale-rich metabolic networks | Q81764933 | ||
Disordered domains and high surface charge confer hubs with the ability to interact with multiple proteins in interaction networks | Q82855583 | ||
DrugBank: a comprehensive resource for in silico drug discovery and exploration | Q24188653 | ||
MPact: the MIPS protein interaction resource on yeast | Q24538008 | ||
The human disease network | Q24678240 | ||
Protein complexes and functional modules in molecular networks | Q24683305 | ||
Network biology: understanding the cell's functional organization | Q27861027 | ||
Collective dynamics of 'small-world' networks | Q27861064 | ||
Global mapping of the yeast genetic interaction network | Q27934987 | ||
Specificity and stability in topology of protein networks | Q28216450 | ||
Drug-target network | Q29614447 | ||
Evidence for dynamically organized modularity in the yeast protein-protein interaction network | Q29614449 | ||
Stratus not altocumulus: a new view of the yeast protein interaction network | Q33258019 | ||
The "robust yet fragile" nature of the Internet | Q34056048 | ||
Quantitative systems-level determinants of human genes targeted by successful drugs. | Q36388813 | ||
Network properties of genes harboring inherited disease mutations | Q36670355 | ||
Towards a theory of biological robustness | Q42560167 | ||
Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome. | Q48337100 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P433 | issue | 10 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | protein design | Q410814 |
protein structure | Q735188 | ||
P304 | page(s) | e1000550 | |
P577 | publication date | 2009-10-01 | |
P1433 | published in | PLOS Computational Biology | Q2635829 |
P1476 | title | Structure of protein interaction networks and their implications on drug design | |
P478 | volume | 5 |
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