The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Missing and spurious interactions and the reconstruction of complex networks
Open accessAbstract
Network analysis is currently used in a myriad of contexts, from identifying potential drug targets to predicting the spread of epidemics and designing vaccination strategies and from finding friends to uncovering criminal activity. Despite the promise of the network approach, the reliability of network data is a source of great concern in all fields where complex networks are studied. Here, we present a general mathematical and computational framework to deal with the problem of data reliability in complex networks. In particular, we are able to reliably identify both missing and spurious interactions in noisy network observations. Remarkably, our approach also enables us to obtain, from those noisy observations, network reconstructions that yield estimates of the true network properties that are more accurate than those provided by the observations themselves. Our approach has the potential to guide experiments, to better characterize network data sets, and to drive new discoveries.
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Citations
Cites
Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
The structure of the nervous system of the nematode Caenorhabditis elegans
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“We evaluate the performance of our approach using five high-quality networks: the social network of interactions between people in a karate club (23), the social network of frequent associations between 62 dolphins (24), the air transportation network of Eastern Europe (25), the neural network of the nematode Caenorha…”
MethodHierarchical structure and the prediction of missing links in networks
Clauset, A., Moore, C., & Newman, M. E. J. (2008) · Nature · doi:10.1038/nature06830 · Cited by 2,171
High-Quality Binary Protein Interaction Map of the Yeast Interactome Network
Yu, H., Braun, P., Yıldırım, M. A., Lemmens, I., Venkatesan, K., Sahalie, J., Hirozane-Kishikawa, T., Gebreab, F., Li, N., Simonis, N., et al. (2008) · Science · doi:10.1126/science.1158684 · Cited by 1,392
Effects of missing data in social networks
Kossinets, G. (2006) · Social Networks · doi:10.1016/j.socnet.2005.07.002 · Cited by 926
Modularity from fluctuations in random graphs and complex networks
Guimerà, R., Sales-Pardo, M., & Amaral, L. A. N. (2004) · Physical Review E · doi:10.1103/physreve.70.025101 · Cited by 894
Self-citationSocial Structure from Multiple Networks. II. Role Structures
Boorman, S. A., & White, H. C. (1976) · American Journal of Sociology · doi:10.1086/226228 · Cited by 788
Cited by
Newman, M. (2018) · doi:10.1093/oso/9780198805090.001.0001 · Cited by 2,297
Stochastic blockmodels and community structure in networks
Karrer, B., & Newman, M. E. J. (2011) · Physical Review E · doi:10.1103/physreve.83.016107 · Cited by 2,025
Community detection in networks: a user guide
Fortunato, S., & Hric, D. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.09.002 · Cited by 2,086
Uncovering disease-disease relationships through the incomplete interactome
Menche, J., Sharma, A., Kitsak, M., Ghiassian, S. D., Vidal, M., Loscalzo, J., & Barabási, A.-L. (2015) · Science · doi:10.1126/science.1257601 · Cited by 1,546
Structure and dynamics of molecular networks: A novel paradigm of drug discovery
Csermely, P., Korcsmáros, T., Kiss, H. J. M., London, G., & Nussinov, R. (2013) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2013.01.016 · Cited by 892
Metadata
- Authors
- Guimerà, R., & Sales-Pardo, M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2009-12-29
- Volume
- 106
- Issue
- 52
- Pages
- 22073-22078
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1994321911
- Cited by
- 797
- References
- 7
- FWCI
- 10.89
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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