| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/bmcsb/WinterbachMRWR13 |
| P6179 | Dimensions Publication ID | 1048352399 |
| P356 | DOI | 10.1186/1752-0509-7-90 |
| P2888 | exact match | https://scigraph.springernature.com/pub.10.1186/1752-0509-7-90 |
| P932 | PMC publication ID | 4231395 |
| P698 | PubMed publication ID | 24041013 |
| P5875 | ResearchGate publication ID | 256663585 |
| P2093 | author name string | Huijuan Wang | |
| Dick de Ridder | |||
| Piet Van Mieghem | |||
| Marcel Reinders | |||
| Wynand Winterbach | |||
| P2860 | cites work | Protein-protein interactions essentials: key concepts to building and analyzing interactome networks | Q21145336 |
| An automated method for finding molecular complexes in large protein interaction networks | Q21284295 | ||
| Towards a proteome-scale map of the human protein–protein interaction network | Q21735930 | ||
| Gene ontology: tool for the unification of biology | Q23781406 | ||
| Network motifs: structure does not determine function | Q24548927 | ||
| The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored | Q24607390 | ||
| BRENDA, the enzyme information system in 2011 | Q24613881 | ||
| Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data | Q24625913 | ||
| Design and implementation of three incoherent feed-forward motif based biological concentration sensors | Q24648654 | ||
| Survival of the sparsest: robust gene networks are parsimonious | Q24649377 | ||
| Network-based prediction of protein function | Q24670295 | ||
| Resolution limit in community detection | Q24675775 | ||
| Similarities and differences in genome-wide expression data of six organisms | Q24800747 | ||
| The evolution of connectivity in metabolic networks | Q24811759 | ||
| Preferential attachment in the evolution of metabolic networks | Q24813122 | ||
| Emergence of Scaling in Random Networks | Q27037290 | ||
| Generation of uncorrelated random scale-free networks | Q27349150 | ||
| Subgraph centrality in complex networks | Q27349248 | ||
| 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 | ||
| Surfing the p53 network | Q28032484 | ||
| The genetic landscape of a cell | Q28131628 | ||
| Subnetwork hierarchies of biochemical pathways. | Q48604133 | ||
| Controllability of complex networks. | Q51569838 | ||
| Network growth models and genetic regulatory networks. | Q51944109 | ||
| Revealing modular organization in the yeast transcriptional network. | Q52036243 | ||
| Network inference, analysis, and modeling in systems biology. | Q53556135 | ||
| Rewiring of transcriptional regulatory networks: hierarchy, rather than connectivity, better reflects the importance of regulators. | Q54376404 | ||
| Link communities reveal multiscale complexity in networks | Q57405864 | ||
| Spectral Coarse Graining of Complex Networks | Q57990768 | ||
| Guilt-by-association goes global | Q59048545 | ||
| Preferential Attachment in the Protein Network Evolution | Q59739522 | ||
| Superparamagnetic clustering of data | Q74567124 | ||
| Protein bipartivity and essentiality in the yeast protein-protein interaction network | Q80196261 | ||
| Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence | Q83227849 | ||
| How scale-free are biological networks | Q83363278 | ||
| The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics | Q35753717 | ||
| Genomic analysis of essentiality within protein networks | Q35774496 | ||
| PINALOG: a novel approach to align protein interaction networks--implications for complex detection and function prediction. | Q35916743 | ||
| Molecular signaling network complexity is correlated with cancer patient survivability | Q36061531 | ||
| The human phosphotyrosine signaling network: evolution and hotspots of hijacking in cancer | Q36093876 | ||
| A protein interaction map of Drosophila melanogaster | Q28131783 | ||
| Evolutionary capacitance as a general feature of complex gene networks | Q28191006 | ||
| Specificity and stability in topology of protein networks | Q28216450 | ||
| The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases | Q28253558 | ||
| Robustness can evolve gradually in complex regulatory gene networks with varying topology | Q28469133 | ||
| Structure of protein interaction networks and their implications on drug design | Q28476325 | ||
| Epistatic interaction maps relative to multiple metabolic phenotypes | Q28477135 | ||
| Randomizing genome-scale metabolic networks | Q28479041 | ||
| The protein-protein interaction map of Helicobacter pylori | Q28484787 | ||
| Evolution of biological interaction networks: from models to real data | Q28730461 | ||
| Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics data | Q28748376 | ||
| Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth | Q29397612 | ||
| Lethality and centrality in protein networks | Q29547267 | ||
| KEGG for integration and interpretation of large-scale molecular data sets | Q29547277 | ||
| Network motifs: simple building blocks of complex networks | Q29547340 | ||
| Network medicine: a network-based approach to human disease | Q29547462 | ||
| From molecular to modular cell biology | Q29547493 | ||
| The large-scale organization of metabolic networks | Q29547498 | ||
| Evidence for dynamically organized modularity in the yeast protein-protein interaction network | Q29614449 | ||
| Discovering regulatory and signalling circuits in molecular interaction networks | Q29614951 | ||
| Network motifs: theory and experimental approaches | Q29615325 | ||
| Network-based classification of breast cancer metastasis | Q29616384 | ||
| Computational systems biology | Q29616655 | ||
| Evolutionary rate in the protein interaction network | Q29617048 | ||
| A general framework for weighted gene co-expression network analysis | Q29617580 | ||
| Hierarchical organization of modularity in metabolic networks | Q29618451 | ||
| JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles | Q29619342 | ||
| A network of protein-protein interactions in yeast | Q30004209 | ||
| Superfamilies of evolved and designed networks. | Q30339061 | ||
| DNA-protein interactions: methods for detection and analysis | Q31049689 | ||
| Convergent evolution of modularity in metabolic networks through different community structures | Q31090499 | ||
| Characterizing disease states from topological properties of transcriptional regulatory networks | Q33241989 | ||
| Why do hubs tend to be essential in protein networks? | Q33245657 | ||
| Identification of key processes underlying cancer phenotypes using biologic pathway analysis | Q33283999 | ||
| Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks | Q33286434 | ||
| Metabolic pathway alignment between species using a comprehensive and flexible similarity measure | Q33395883 | ||
| The metabolic world of Escherichia coli is not small | Q36159873 | ||
| Graphlet-based edge clustering reveals pathogen-interacting proteins | Q36218018 | ||
| Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues | Q36244121 | ||
| Interactome: gateway into systems biology | Q36257382 | ||
| A map of human cancer signaling | Q36327214 | ||
| Global network alignment using multiscale spectral signatures | Q36432222 | ||
| Probabilistic assembly of human protein interaction networks from label-free quantitative proteomics | Q36446314 | ||
| Graph-based methods for analysing networks in cell biology | Q36552759 | ||
| Observability of complex systems | Q36617090 | ||
| The evolution of modularity in bacterial metabolic networks. | Q36657624 | ||
| Cascading failure and robustness in metabolic networks | Q36869768 | ||
| Protein networks in disease | Q37125547 | ||
| Toolbox model of evolution of prokaryotic metabolic networks and their regulation. | Q37239039 | ||
| Optimal partition and effective dynamics of complex networks | Q37452847 | ||
| Local graph alignment and motif search in biological networks | Q37570636 | ||
| Protein-protein interaction networks: how can a hub protein bind so many different partners? | Q37616866 | ||
| The powerful law of the power law and other myths in network biology | Q37659825 | ||
| Protein-protein interactions: making sense of networks via graph-theoretic modeling | Q37824310 | ||
| Mass-balanced randomization of metabolic networks | Q37857537 | ||
| Differential network biology | Q37976573 | ||
| Understanding genomic alterations in cancer genomes using an integrative network approach | Q38069759 | ||
| Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors | Q39283917 | ||
| Multifunctional proteins revealed by overlapping clustering in protein interaction network | Q39965347 | ||
| Uncovering biological network function via graphlet degree signatures. | Q40140345 | ||
| Finding friends and enemies in an enemies-only network: a graph diffusion kernel for predicting novel genetic interactions and co-complex membership from yeast genetic interactions | Q41345892 | ||
| Topological network alignment uncovers biological function and phylogeny | Q41592105 | ||
| Influence of metabolic network structure and function on enzyme evolution | Q42235124 | ||
| Still stratus not altocumulus: further evidence against the date/party hub distinction | Q42745582 | ||
| Systematic identification of functional orthologs based on protein network comparison | Q43252162 | ||
| Integrating metabolic, transcriptional regulatory and signal transduction models in Escherichia coli. | Q43575020 | ||
| Statistical analysis of global connectivity and activity distributions in cellular networks. | Q44214456 | ||
| Gene co-expression network topology provides a framework for molecular characterization of cellular state | Q45205691 | ||
| Functional and evolutionary inference in gene networks: does topology matter? | Q45813418 | ||
| Mining coherent dense subgraphs across massive biological networks for functional discovery | Q46339422 | ||
| On the structure of protein-protein interaction networks | Q47356561 | ||
| Protein complex prediction via cost-based clustering | Q47387430 | ||
| Metabolic network modularity arising from simple growth processes | Q47563790 | ||
| Gene regulatory network growth by duplication | Q47610427 | ||
| Identifying functional modules using expression profiles and confidence-scored protein interactions | Q48291481 | ||
| Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome. | Q48337100 | ||
| Localized network centrality and essentiality in the yeast-protein interaction network. | Q48453179 | ||
| Disease candidate gene identification and prioritization using protein interaction networks | Q33412922 | ||
| Bayesian Markov Random Field analysis for protein function prediction based on network data | Q33535782 | ||
| Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks | Q33619022 | ||
| Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models | Q33642720 | ||
| Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy | Q33719832 | ||
| Multi-level reproducibility of signature hubs in human interactome for breast cancer metastasis | Q33741210 | ||
| Clustering gene expression patterns | Q33882299 | ||
| A toolbox model of evolution of metabolic pathways on networks of arbitrary topology | Q33916616 | ||
| Environmental versatility promotes modularity in genome-scale metabolic networks | Q34001801 | ||
| The identification of functional modules from the genomic association of genes | Q34027115 | ||
| Spontaneous evolution of modularity and network motifs | Q34048031 | ||
| Biological role of noise encoded in a genetic network motif | Q34067922 | ||
| Protein evolution in yeast transcription factor subnetworks | Q34189209 | ||
| Protein interaction data curation: the International Molecular Exchange (IMEx) consortium | Q34210192 | ||
| The connectivity structure, giant strong component and centrality of metabolic networks | Q34215978 | ||
| "Guilt by association" is the exception rather than the rule in gene networks | Q34220929 | ||
| Scalable global alignment for multiple biological networks | Q34247846 | ||
| Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods | Q34257056 | ||
| Identification of high-quality cancer prognostic markers and metastasis network modules | Q34275507 | ||
| Structure and evolution of transcriptional regulatory networks | Q34326530 | ||
| Modular organization of cellular networks | Q34329388 | ||
| Peeling the yeast protein network | Q34380924 | ||
| Revisiting "scale-free" networks | Q34451081 | ||
| Pathway alignment: application to the comparative analysis of glycolytic enzymes | Q34505049 | ||
| Chapter 4: Protein interactions and disease | Q34539656 | ||
| Chapter 5: Network biology approach to complex diseases. | Q34539662 | ||
| Does habitat variability really promote metabolic network modularity? | Q34674915 | ||
| Dynamic modularity in protein interaction networks predicts breast cancer outcome | Q34934057 | ||
| Topological structure analysis of the protein-protein interaction network in budding yeast | Q34980439 | ||
| Using graph theory to analyze biological networks | Q35005792 | ||
| Building with a scaffold: emerging strategies for high- to low-level cellular modeling | Q35146255 | ||
| Principles of microRNA regulation of a human cellular signaling network | Q35193525 | ||
| PathBLAST: a tool for alignment of protein interaction networks | Q35556674 | ||
| P921 | main subject | molecular interaction | Q33059490 |
| P304 | page(s) | 90 | |
| P577 | publication date | 2013-09-16 | |
| P1433 | published in | BMC Systems Biology | Q4835949 |
| P1476 | title | Topology of molecular interaction networks | |
| P478 | volume | 7 |
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| Q92862439 | Natural Product Target Network Reveals Potential for Cancer Combination Therapies |
| Q49983962 | Network Analyses in Plant Pathogens. |
| Q64984746 | Network Architecture and Mutational Sensitivity of the C. elegans Metabolome. |
| Q92138355 | Network analysis of hyphae forming proteins in Candida albicans identifies important proteins responsible for pathovirulence in the organism |
| Q34427904 | Network-based Prediction of Cancer under Genetic Storm |
| Q42282068 | Quantitative Analysis of Robustness of Dynamic Response and Signal Transfer in Insulin mediated PI3K/AKT Pathway |
| Q40749831 | Scale-space measures for graph topology link protein network architecture to function |
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