The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.
Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets
Open accessAbstract
Significance: Large-scale biological network analyses often use concepts used in social networks analysis (e.g. finding “communities,” “hubs,” etc.). However, mathematically advanced engineering concepts have only been applied to analyze small and well-characterized networks so far in biology. Here, we applied a sophisticated engineering tool, from control theory, to analyze a large-scale directed human protein–protein interaction network. Our analysis revealed that the proteins that are indispensable, from a network controllability perspective, are also commonly targeted by disease-causing mutations and human viruses or have been identified as drug targets. Furthermore, we used the controllability analysis to prioritize novel cancer genes from cancer genomic datasets. Altogether, we demonstrated an application of network controllability analysis to identify new disease genes and drug targets.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Slotine, J.-J. E., & Li, W. (1991) · CERN Document Server (European Organization for Nuclear Research) · Cited by 18,975
Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal
Gao, J., Aksoy, B. A., Dogrusoz, U., Dresdner, G., Gross, B., Sumer, S. O., Sun, Y., Jacobsen, A., Sinha, R., Larsson, E., et al. (2013) · Science Signaling · doi:10.1126/scisignal.2004088 · Cited by 15,160
The protein kinase complement of the human genome
Manning, G., Whyte, D. B., Martinez, R., Hunter, T., & Sudarsanam, S. (2002) · Science · doi:10.1126/science.1075762 · Cited by 8,145
Integrated genomic analyses of ovarian carcinoma
Perou, C. M. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/hvp3-wg08 · Cited by 7,925
Isidori, A. (1989) · Springer eBooks · doi:10.1007/978-3-662-02581-9 · Cited by 7,869
Isidori, A. (1995) · Communications and Control Engineering · doi:10.1007/978-1-84628-615-5 · Cited by 6,755
Integrated genomic characterization of endometrial carcinoma
The Cancer Genome Atlas Research Network, & Levine, D. A. (2013) · Nature · doi:10.1038/nature12113 · Cited by 5,784
Comprehensive molecular profiling of lung adenocarcinoma
The Cancer Genome Atlas Research Network (2014) · Nature · doi:10.1038/nature13385 · Cited by 5,732
Cited by
Artificial intelligence in cancer target identification and drug discovery
You, Y., Lai, X., Pan, Y., Zheng, H., Vera, J., Liu, S., Deng, S., & Zhang, L. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00994-0 · Cited by 435
Cryo-EM structure of islet amyloid polypeptide fibrils reveals similarities with amyloid-β fibrils
Röder, C., Kupreichyk, T., Gremer, L., Schäfer, L. U., Pothula, K. R., Ravelli, R. B. G., Willbold, D., Hoyer, W., & Schröder, G. F. (2020) · Nature Structural & Molecular Biology · doi:10.1038/s41594-020-0442-4 · Cited by 180
Network Medicine in Pathobiology
Lee, L. Y.-H., & Loscalzo, J. (2019) · The American Journal of Pathology · doi:10.1016/j.ajpath.2019.03.009 · Cited by 95
Tsuji, S., Hase, T., Yachie-Kinoshita, A., Nishino, T., Ghosh, S., Kikuchi, M., Shimokawa, K., Aburatani, H., Kitano, H., & Tanaka, H. (2021) · Alzheimer's Research & Therapy · doi:10.1186/s13195-021-00826-3 · Cited by 75
Network control principles for identifying personalized driver genes in cancer
Guo, W.-F., Zhang, S.-W., Zeng, T., Akutsu, T., & Chen, L. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz089 · Cited by 44
Metadata
- Authors
- Vinayagam, A., Gibson, T. E., Lee, H.-J., Yilmazel, B., Roesel, C., Hu, Y., Kwon, Y., Sharma, A., Liu, Y.-Y., Perrimon, N., & Barabási, A.-L.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2016-04-18
- Volume
- 113
- Issue
- 18
- Pages
- 4976-4981
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2180749449
- Cited by
- 257
- References
- 74
- FWCI
- 15.50
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets. https://app.cochat.ai/papers/10.1073/pnas.1603992113
- The paper
- Vinayagam, A., Gibson, T. E., Lee, H.-J., Yilmazel, B., Roesel, C., Hu, Y., Kwon, Y., Sharma, A., Liu, Y.-Y., Perrimon, N., & Barabási, A.-L. (2016). Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1603992113
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
