The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
The ConsensusPathDB interaction database: 2013 update
Open accessAbstract
Knowledge of the various interactions between molecules in the cell is crucial for understanding cellular processes in health and disease. Currently available interaction databases, being largely complementary to each other, must be integrated to obtain a comprehensive global map of the different types of interactions. We have previously reported the development of an integrative interaction database called ConsensusPathDB (http://ConsensusPathDB.org) that aims to fulfill this task. In this update article, we report its significant progress in terms of interaction content and web interface tools. ConsensusPathDB has grown mainly due to the integration of 12 further databases; it now contains 215 541 unique interactions and 4601 pathways from overall 30 databases. Binary protein interactions are scored with our confidence assessment tool, IntScore. The ConsensusPathDB web interface allows users to take advantage of these integrated interaction and pathway data in different contexts. Recent developments include pathway analysis of metabolite lists, visualization of functional gene/metabolite sets as overlap graphs, gene set analysis based on protein complexes and induced network modules analysis that connects a list of genes through various interaction types. To facilitate the interactive, visual interpretation of interaction and pathway data, we have re-implemented the graph visualization feature of ConsensusPathDB using the Cytoscape.js library.
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Cites
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
Reactome: a database of reactions, pathways and biological processes
Croft, D., O'Kelly, G., Wu, G., Haw, R., Gillespie, M., Matthews, L., Caudy, M., Garapati, P., Gopinath, G., Jassal, B., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1018 · Cited by 1,751
Pathway Commons, a web resource for biological pathway data
Cerami, E. G., Gross, B. E., Demir, E., Rodchenkov, I., Babur, O., Anwar, N., Schultz, N., Bader, G. D., & Sander, C. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1039 · Cited by 1,101
The BioPAX community standard for pathway data sharing
Demir, E., Cary, M. P., Paley, S., Fukuda, K., Lemer, C., Vastrik, I., Wu, G., D'Eustachio, P., Schaefer, C., Luciano, J., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1666 · Cited by 745 · cited 6×
“BioPAX Level 3 export Networks viewed with the interaction visualization tool can now be exported in BioPAX Level 3 (4) format.”
MethodInfluentialConsensusPathDB: toward a more complete picture of cell biology
Kamburov, A., Pentchev, K., Galicka, H., Wierling, C., Lehrach, H., & Herwig, R. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1156 · Cited by 671 · cited 7×
“For example, we have previously described a new class of functional gene sets called NESTs (8).”
BackgroundMethodInfluentialSelf-citationConsensusPathDB--a database for integrating human functional interaction networks
Kamburov, A., Wierling, C., Lehrach, H., & Herwig, R. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn698 · Cited by 565
Self-citationPathguide: a Pathway Resource List
Bader, G. D. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj126 · Cited by 435
Cited by
Szklarczyk, D., Gable, A. L., Nastou, K. C., Lyon, D., Kirsch, R., Pyysalo, S., Doncheva, N. T., Legeay, M., Fang, T., Bork, P., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1074 · Cited by 8,056
Gene set knowledge discovery with enrichr
Xie, Z., Bailey, A., Kuleshov, M. V., Clarke, D. J. B., Evangelista, J. E., Jenkins, S. L., Lachmann, A., Wojciechowicz, M. L., Kropiwnicki, E., Jagodnik, K. M., et al. (2021) · Current Protocols · doi:10.1002/cpz1.90 · Cited by 3,451
NicheNet: Modeling intercellular communication by linking ligands to target genes
Browaeys, R., Saelens, W., & Saeys, Y. (2020) · Nature Methods · doi:10.1038/s41592-019-0667-5 · Cited by 2,192
Dangaj, D., Bruand, M., Grimm, A. J., Ronet, C., Barras, D., Duttagupta, P. A., Lanitis, E., Duraiswamy, J., Tanyi, J. L., Benencia, F., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.05.004 · Cited by 875
Systematic Evaluation of Molecular Networks for Discovery of Disease Genes
Huang, J. K., Carlin, D. E., Yu, M. K., Zhang, W., Kreisberg, J. F., Tamayo, P., & Ideker, T. (2018) · Cell Systems · doi:10.1016/j.cels.2018.03.001 · Cited by 289
Metadata
- Authors
- Kamburov, A., Stelzl, U., Lehrach, H., & Herwig, R.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-11-10
- Volume
- 41
- Issue
- D1
- Pages
- D793-D800
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2150420891
- Cited by
- 807
- References
- 7
- FWCI
- 11.50
- Type
- journal article
- Language
- en
- Open access
- gold
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