Published March 15, 2023 | Version 1.0
Poster Open

TIN-X Version 3: Update with expanded dataset and modernized architecture

Creators

  • 1. University of New Mexico, Albuquerque, NM, USA
  • 2. Elevato Digital, Columbia, MO, USA
  • 3. Center for Molecular Discovery, University of New Mexico Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, USA
  • 4. Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, Florida, USA;
  • 5. Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark;
  • 6. Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico, USA

Description

Target Importance and Novelty eXplorer (TIN-X) is an Interactive web-based visualization tool for illuminating associations between diseases and drug targets. TIN-X uses natural language processing to identify disease and protein mentions within PubMed content. Two important metrics, novelty and importance, are computed from this data, and when plotted as log(importance) vs log(novelty), help users visually explore the novelty of drug targets and their associated importance to diseases.  The primary data sources are TCRD/Pharos and PubMed content. 

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TINX_v4_2023_IDGFace2Face.pdf

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Additional details

References

  • DC Cannon, JJ Yang, SL Mathias, O Ursu, S Mani, A Waller, SC Schürer, LJ Jensen, LA Sklar, CG Bologa, and TI Oprea, "TIN-X: Target Importance and Novelty Explorer." (2017) Bioinformatics, btx200, doi: 10.1093/bioinformatics/btx200
  • Sheils, T., Mathias, S. et al, "TCRD and Pharos 2021: mining the human proteome for disease biology." (2021) Nucl. Acids Res., DOI: 10.1093/nar/gkaa993
  • Dhouha Grissa, Alexander Junge, Tudor I. Oprea, and Lars Juhl Jensen. "DISEASES 2.0: a weekly updated database of disease–gene associations from text mining and data integration." (2022) Database, 1-8; doi/10.1093/database/baac019/6554833
  • NIH Strategic Plan for Data Science, accessed Feb 2022, https://datascience.nih.gov/sites/default/files/NIH_Strategic_Plan_for_Data_Science_Final_508.pdf