The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
TIMER2.0 for analysis of tumor-infiltrating immune cells
Open accessAbstract
Tumor progression and the efficacy of immunotherapy are strongly influenced by the composition and abundance of immune cells in the tumor microenvironment. Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition from bulk tumor transcriptome profiles. These estimated tumor immune infiltrate populations have been associated with genomic and transcriptomic changes in the tumors, providing insight into tumor–immune interactions. However, such investigations on large-scale public data remain challenging. To lower the barriers for the analysis of complex tumor–immune interactions, we significantly improved our previous web platform TIMER. Instead of just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms. TIMER2.0 provides four modules for investigating the associations between immune infiltrates and genetic or clinical features, and four modules for exploring cancer-related associations in the TCGA cohorts. Each module can generate a functional heatmap table, enabling the user to easily identify significant associations in multiple cancer types simultaneously. Overall, the TIMER2.0 web server provides comprehensive analysis and visualization functions of tumor infiltrating immune cells.
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Skoulidis, F., Araujo, H. A., Do, M. T., Qian, Y., Sun, X., Galan-Cobo, A., Le, J. T., Montesion, M., Palmer, R., Jahchan, N., et al. (2024) · Nature · doi:10.1038/s41586-024-07943-7 · Cited by 194
A pan-cancer analysis of the prognostic and immunological role of β-actin (ACTB) in human cancers
Gu, Y., Tang, S., Wang, Z., Cai, L., Lian, H., Shen, Y., & Zhou, Y. (2021) · Bioengineered · doi:10.1080/21655979.2021.1973220 · Cited by 99
Spatial immune scoring system predicts hepatocellular carcinoma recurrence
Jia, G., He, P., Dai, T., Goh, D., Wang, J., Sun, M., Wee, F., Li, F., Lim, J. C. T., Hao, S., et al. (2025) · Nature · doi:10.1038/s41586-025-08668-x · Cited by 104
Luo, F., Lu, F.-T., Cao, J.-X., Ma, W.-J., Xia, Z.-F., Zhan, J.-H., Zeng, K.-M., Huang, Y., Zhao, H.-Y., & Zhang, L. (2022) · Cancer Letters · doi:10.1016/j.canlet.2022.01.027 · Cited by 95
Metadata
- Authors
- Li, T., Fu, J., Zeng, Z., Cohen, D., Li, J., Chen, Q., Li, B., & Liu, X. S.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-05-22
- Volume
- 48
- Issue
- W1
- Pages
- W509-W514
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W3027286012
- Cited by
- 5,209
- References
- 9
- FWCI
- 230.09
- Type
- journal article
- Language
- en
- Open access
- gold
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- Li, T., Fu, J., Zeng, Z., Cohen, D., Li, J., Chen, Q., Li, B., & Liu, X. S. (2020). TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Research. https://doi.org/10.1093/nar/gkaa407
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