TIN-X: target importance and novelty explorer
Open accessAbstract
MOTIVATION: The increasing amount of peer-reviewed manuscripts requires the development of specific mining tools to facilitate the visual exploration of evidence linking diseases and proteins. RESULTS: We developed TIN-X, the Target Importance and Novelty eXplorer, to visualize the association between proteins and diseases, based on text mining data processed from scientific literature. In the current implementation, TIN-X supports exploration of data for G-protein coupled receptors, kinases, ion channels, and nuclear receptors. TIN-X supports browsing and navigating across proteins and diseases based on ontology classes, and displays a scatter plot with two proposed new bibliometric statistics: Importance and Novelty. AVAILABILITY AND IMPLEMENTATION: http://www.newdrugtargets.org. CONTACT: cbologa@salud.unm.edu.
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The target-disease Novelty score is shown in the TIN-X panel on the disease details page.
“The target-disease Novelty score is shown in the Target-Importance Novelty eXplorer (TIN-X, (41) panel.”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [41]
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A comprehensive map of molecular drug targets
Santos, R., Ursu, O., Gaulton, A., Bento, A. P., Donadi, R. S., Bologa, C. G., Karlsson, A., Al-Lazikani, B., Hersey, A., Oprea, T. I., et al. (2017) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2016.230 · Cited by 2,427 · see citing works
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Self-citationKibbe, W. A., Arze, C., Felix, V., Mitraka, E., Bolton, E., Fu, G., Mungall, C., Binder, J. X., MALONE, J. M., Vasant, D., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1011 · Cited by 582 · see citing works
Biomedical Language Processing: What's Beyond PubMed?
Hunter, L., & Cohen, K. B. (2006) · Molecular Cell · doi:10.1016/j.molcel.2006.02.012 · Cited by 308 · see citing works
Pharos: collating protein information to shed light on the druggable genome
Nguyen, D.-T., Mathias, S., Bologa, C., Brunak, S., Fernandez, N., Gaulton, A., Hersey, A., Holmes, J., Jensen, L. J., Karlsson, A., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1072 · Cited by 279 · see citing works
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Pafilis, E., Frankild, S. P., Fanini, L., Faulwetter, S., Pavloudi, C., Vasileiadou, A., Arvanitidis, C., & Jensen, L. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065390 · Cited by 206 · see citing works
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Ren, F., Aliper, A., Chen, J., Zhao, H., Rao, S., Kuppe, C., Ozerov, I. V., Zhang, M., Witte, K., Kruse, C., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02143-0 · Cited by 348 · see citing works
“Unlike other target-discovery approaches such as Open Targets 43 or NewDrugTargets 44 , our method was designed and validated to search targets for multiple diseases and aging 15 .”
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TCRD and pharos 2021: mining the human proteome for disease biology
Sheils, T. K., Mathias, S. L., Kelleher, K. J., Siramshetty, V. B., Nguyen, D.-T., Bologa, C. G., Jensen, L. J., Vidović, D., Koleti, A., Schürer, S. C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa993 · Cited by 160 · see citing works
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Kelleher, K. J., Sheils, T. K., Mathias, S. L., Yang, J. J., Metzger, V. T., Siramshetty, V. B., Nguyen, D.-T., Jensen, L. J., Vidović, D., Schürer, S. C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1033 · Cited by 137 · see citing works
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- Authors
- Cannon, D. C., Yang, J. J., Mathias, S. L., Ursu, O., Mani, S., Waller, A., Schürer, S. C., Jensen, L. J., Sklar, L. A., Bologa, C. G., & Oprea, T. I.
- Affiliations
- University of New Mexico (US)
- University of Miami (US)
- University of Copenhagen (DK)
- Corresponding author
- Bologa, Cristian G
- ORCID
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-04-07
- Volume
- 33
- Issue
- 16
- Pages
- 2601-2603
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC5870731
- OpenAlex
- W2604190529
- Cited by
- 34
- References
- 6
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 5 · 2023: 4 · 2022: 7 · 2021: 3 · 2020: 3 · 2019: 2 · 2018: 1 · 2017: 5
- FWCI
- 1.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (acceptedVersion, cc-by)
- Funders
- National Institutes of Health (U54 CA189205-01)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- text mining, scientific literature mining, G protein-coupled receptors, kinases, ion channels, nuclear receptors, ontology classes, interactive visualization
- MeSH terms
- Computer Graphics, Disease, Humans, Ion Channels, Phosphotransferases, Software, Receptors, Cytoplasmic and Nuclear, Receptors, G-Protein-Coupled, Data Mining, Biological Ontologies
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