Tin Nguyen

3.6k total citations
70 papers, 1.9k citations indexed

About

Tin Nguyen is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Tin Nguyen has authored 70 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Molecular Biology, 11 papers in Cancer Research and 8 papers in Oncology. Recurrent topics in Tin Nguyen's work include Gene expression and cancer classification (27 papers), Bioinformatics and Genomic Networks (27 papers) and Single-cell and spatial transcriptomics (10 papers). Tin Nguyen is often cited by papers focused on Gene expression and cancer classification (27 papers), Bioinformatics and Genomic Networks (27 papers) and Single-cell and spatial transcriptomics (10 papers). Tin Nguyen collaborates with scholars based in United States, Canada and Vietnam. Tin Nguyen's co-authors include Sorin Drăghici, Lori Frappier, Hung Nguyen, Adib Shafi, Kathy Shire, Duc Tran, C.H. Arrowsmith, Yi Sheng, Rebecca Tagett and Bang Tran and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Tin Nguyen

66 papers receiving 1.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tin Nguyen United States	21	1.4k	455	209	206	172	70	1.9k
Katsuhisa Horimoto Japan	24	1.6k 1.1×	303 0.7×	440 2.1×	382 1.9×	136 0.8×	109	2.6k
Jennifer Walling United States	18	1.6k 1.1×	526 1.2×	244 1.2×	684 3.3×	180 1.0×	25	2.5k
Charles Vaske United States	17	1.1k 0.8×	318 0.7×	71 0.3×	421 2.0×	133 0.8×	39	1.6k
Emily Clough United States	7	1.4k 1.0×	208 0.5×	178 0.9×	500 2.4×	173 1.0×	8	2.1k
Bhavneet Bhinder United States	20	891 0.6×	333 0.7×	108 0.5×	415 2.0×	93 0.5×	51	1.7k
Xiao‐Jun Tian United States	18	1.1k 0.7×	466 1.0×	188 0.9×	299 1.5×	129 0.8×	62	1.8k
Andreas Schlicker Germany	21	1.4k 1.0×	778 1.7×	96 0.5×	422 2.0×	98 0.6×	35	2.2k
Phillip Stafford United States	27	1.3k 0.9×	224 0.5×	118 0.6×	380 1.8×	190 1.1×	79	2.1k
Sohyun Hwang South Korea	22	1.1k 0.8×	338 0.7×	70 0.3×	355 1.7×	289 1.7×	69	1.8k
Sol Efroni Israel	27	1.7k 1.2×	371 0.8×	121 0.6×	419 2.0×	208 1.2×	76	2.8k

Countries citing papers authored by Tin Nguyen

Since Specialization

Citations

This map shows the geographic impact of Tin Nguyen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tin Nguyen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tin Nguyen more than expected).

Fields of papers citing papers by Tin Nguyen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tin Nguyen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tin Nguyen. The network helps show where Tin Nguyen may publish in the future.

Co-authorship network of co-authors of Tin Nguyen

This figure shows the co-authorship network connecting the top 25 collaborators of Tin Nguyen. A scholar is included among the top collaborators of Tin Nguyen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tin Nguyen. Tin Nguyen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Nguyen, Ha Nam, Thi Ngoc Phuong Nguyen, Hung N. Luu, et al.. (2025). A comprehensive review of cancer survival prediction using multi-omics integration and clinical variables. Briefings in Bioinformatics. 26(2). 3 indexed citations

Nguyen, Ha Nam, et al.. (2024). Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review. Briefings in Bioinformatics. 25(6). 6 indexed citations

Jayawardana, Kalana W., et al.. (2024). Superhydrophobic Array Devices for the Enhanced Formation of 3D Cancer Models. ACS Nano. 18(34). 23637–23654. 4 indexed citations

Nguyen, Hung, Ha Nam Nguyen, Duc Tran, Sorin Drăghici, & Tin Nguyen. (2024). Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges. Nucleic Acids Research. 52(9). 4761–4783. 19 indexed citations

Craig, Douglas B., et al.. (2023). A novel approach for predicting upstream regulators (PURE) that affect gene expression. Scientific Reports. 13(1). 18571–18571. 3 indexed citations

Zhang, Yifan, Duc Tran, Tin Nguyen, Sergiu M. Dascalu, & J. S. Harris. (2023). A robust and accurate single-cell data trajectory inference method using ensemble pseudotime. BMC Bioinformatics. 24(1). 55–55. 8 indexed citations

Nguyen, Tin, et al.. (2022). DrGA: cancer driver gene analysis in a simpler manner. BMC Bioinformatics. 23(1). 86–86. 1 indexed citations

Nguyen, Tin, et al.. (2022). Identification and Validation of a Novel Three Hub Long Noncoding RNAs With m6A Modification Signature in Low-Grade Gliomas. Frontiers in Molecular Biosciences. 9. 801931–801931. 3 indexed citations

Laiakis, Evagelia C., Maísa Pinheiro, Tin Nguyen, et al.. (2022). Quantitative proteomic analytic approaches to identify metabolic changes in the medial prefrontal cortex of rats exposed to space radiation. Frontiers in Physiology. 13. 971282–971282. 6 indexed citations

10.

Tran, Duc, Hung Nguyen, Bang Tran, et al.. (2021). Fast and precise single-cell data analysis using a hierarchical autoencoder. Nature Communications. 12(1). 1029–1029. 85 indexed citations

11.

Yen, Nguyen Thi Hai, et al.. (2021). Re-Identification of Patient Subgroups in Uveal Melanoma. Frontiers in Oncology. 11. 731548–731548. 1 indexed citations

12.

Tran, Duc, et al.. (2020). A Novel Method for Cancer Subtyping and Risk Prediction Using Consensus Factor Analysis. Frontiers in Oncology. 10. 1052–1052. 13 indexed citations

13.

Nguyen, Tin, et al.. (2020). NBIA: a network-based integrative analysis framework – applied to pathway analysis. Scientific Reports. 10(1). 4188–4188. 7 indexed citations

14.

Shafi, Adib, et al.. (2019). Correction to: Identifying significantly impacted pathways: a comprehensive review and assessment. Genome biology. 20(1). 234–234. 11 indexed citations

15.

Shafi, Adib, Tin Nguyen, Azam Peyvandipour, Hung Nguyen, & Sorin Drăghici. (2019). A Multi-Cohort and Multi-Omics Meta-Analysis Framework to Identify Network-Based Gene Signatures. Frontiers in Genetics. 10. 159–159. 19 indexed citations

16.

Shafi, Adib, et al.. (2019). Identifying significantly impacted pathways: a comprehensive review and assessment. Genome biology. 20(1). 203–203. 146 indexed citations

17.

Nguyen, Tin, et al.. (2017). A novel approach for data integration and disease subtyping. Genome Research. 27(12). 2025–2039. 126 indexed citations

18.

Nguyen, Tin, Cristina Mitrea, Rebecca Tagett, & Sorin Drăghici. (2016). DANUBE: Data-Driven Meta-ANalysis Using UnBiased Empirical Distributions—Applied to Biological Pathway Analysis. Proceedings of the IEEE. 105(3). 496–515. 20 indexed citations

19.

Nguyen, Tin, et al.. (2016). Overcoming the matched-sample bottleneck: an orthogonal approach to integrate omic data. Scientific Reports. 6(1). 29251–29251. 20 indexed citations

20.

Sheng, Yi, et al.. (2003). Protein Interaction Domains of the Ubiquitin-specific Protease, USP7/HAUSP. Journal of Biological Chemistry. 278(48). 47753–47761. 151 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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