Yinyin Yuan

14.9k total citations
67 papers, 2.3k citations indexed

About

Yinyin Yuan is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Yinyin Yuan has authored 67 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 18 papers in Cancer Research and 17 papers in Oncology. Recurrent topics in Yinyin Yuan's work include Single-cell and spatial transcriptomics (12 papers), AI in cancer detection (12 papers) and Cancer Genomics and Diagnostics (11 papers). Yinyin Yuan is often cited by papers focused on Single-cell and spatial transcriptomics (12 papers), AI in cancer detection (12 papers) and Cancer Genomics and Diagnostics (11 papers). Yinyin Yuan collaborates with scholars based in United Kingdom, United States and China. Yinyin Yuan's co-authors include Andreas Heindl, Florian Markowetz, Konrad Koelble, Mitch Dowsett, Richard S. Savage, Rachael Natrajan, Henrik Failmezger, Chang‐Tsun Li, Christina Curtis and Carlos Caldas and has published in prestigious journals such as Nature Communications, Bioinformatics and PLoS ONE.

In The Last Decade

Yinyin Yuan

63 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yinyin Yuan United Kingdom 25 963 726 544 537 531 67 2.3k
Peter J. Schüffler Switzerland 16 1.1k 1.1× 483 0.7× 273 0.5× 268 0.5× 307 0.6× 49 2.2k
Anna Melissa Schlitter Germany 30 663 0.7× 1.4k 2.0× 585 1.1× 421 0.8× 449 0.8× 77 3.1k
Michael S. Toss United Kingdom 25 801 0.8× 854 1.2× 698 1.3× 373 0.7× 384 0.7× 116 2.0k
Håvard E. Danielsen Norway 32 839 0.9× 810 1.1× 600 1.1× 613 1.1× 510 1.0× 104 3.5k
Cleo‐Aron Weis Germany 22 375 0.4× 703 1.0× 243 0.4× 713 1.3× 844 1.6× 71 2.3k
Riku Turkki Finland 20 336 0.3× 541 0.7× 187 0.3× 496 0.9× 551 1.0× 35 1.6k
David Verbel United States 21 1.2k 1.3× 871 1.2× 322 0.6× 516 1.0× 289 0.5× 46 2.9k
Arvind Rao United States 32 884 0.9× 1.4k 1.9× 625 1.1× 1.5k 2.8× 503 0.9× 131 4.0k
Panu E. Kovanen Finland 26 627 0.7× 691 1.0× 237 0.4× 415 0.8× 422 0.8× 44 2.3k
Gulisa Turashvili Canada 29 1.9k 2.0× 1.2k 1.7× 1.4k 2.6× 305 0.6× 240 0.5× 109 3.9k

Countries citing papers authored by Yinyin Yuan

Since Specialization
Citations

This map shows the geographic impact of Yinyin Yuan'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 Yinyin Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yinyin Yuan more than expected).

Fields of papers citing papers by Yinyin Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yinyin Yuan. 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 Yinyin Yuan. The network helps show where Yinyin Yuan may publish in the future.

Co-authorship network of co-authors of Yinyin Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Yinyin Yuan. A scholar is included among the top collaborators of Yinyin Yuan 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 Yinyin Yuan. Yinyin Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kouzy, Ramez, Michael K. Rooney, Jean Feng, et al.. (2025). The state of the art in artificial intelligence and digital pathology in prostate cancer. Nature Reviews Urology. 23(1). 13–28. 1 indexed citations
2.
Pan, Ziwen, Yi Liu, Zebin Lin, et al.. (2024). Feasibility and optimization study of a two-dimensional density reconstruction method for large-object muography. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1061. 169138–169138. 1 indexed citations
3.
Patel, Dominic, et al.. (2023). Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies. Cancer Research. 84(3). 493–508. 8 indexed citations
4.
Gálvez‐Cancino, Felipe, et al.. (2023). The tumour ecology of quiescence: Niches across scales of complexity. Seminars in Cancer Biology. 92. 139–149. 3 indexed citations
5.
Zhang, Hanyun, Khalid AbdulJabbar, Ayse U. Akarca, et al.. (2023). Self-supervised deep learning for highly efficient spatial immunophenotyping. EBioMedicine. 95. 104769–104769. 4 indexed citations
6.
Nederlof, Iris, Shan E Ahmed Raza, Khalid AbdulJabbar, et al.. (2022). Spatial interplay of lymphocytes and fibroblasts in estrogen receptor-positive HER2-negative breast cancer. npj Breast Cancer. 8(1). 56–56. 8 indexed citations
7.
Lagree, Andrew, Fang‐I Lu, Jonathan Klein, et al.. (2022). Comparative Evaluation of Tumor-Infiltrating Lymphocytes in Companion Animals: Immuno-Oncology as a Relevant Translational Model for Cancer Therapy. Cancers. 14(20). 5008–5008. 13 indexed citations
8.
Winfield, Jessica, James D. Brenton, Khalid AbdulJabbar, et al.. (2021). Biomarkers for site-specific response to neoadjuvant chemotherapy in epithelial ovarian cancer: relating MRI changes to tumour cell load and necrosis. British Journal of Cancer. 124(6). 1130–1137. 10 indexed citations
9.
Poon, Evon, Matthew Clarke, Neil P. Jerome, et al.. (2020). Noninvasive MRI Native T1 Mapping Detects Response to MYCN -targeted Therapies in the Th- MYCN Model of Neuroblastoma. Cancer Research. 80(16). 3424–3435. 21 indexed citations
10.
Li, Jin, Jessica K.R. Boult, Andreas Heindl, et al.. (2019). Investigating the Contribution of Collagen to the Tumor Biomechanical Phenotype with Noninvasive Magnetic Resonance Elastography. Cancer Research. 79(22). 5874–5883. 43 indexed citations
11.
Failmezger, Henrik, Sathya Muralidhar, Antonio Rullan, et al.. (2019). Topological Tumor Graphs: A Graph-Based Spatial Model to Infer Stromal Recruitment for Immunosuppression in Melanoma Histology. Cancer Research. 80(5). 1199–1209. 54 indexed citations
12.
Naidoo, Kuban D., Patty T. Wai, Sarah Maguire, et al.. (2018). Evaluation of CDK12 Protein Expression as a Potential Novel Biomarker for DNA Damage Response–Targeted Therapies in Breast Cancer. Molecular Cancer Therapeutics. 17(1). 306–315. 54 indexed citations
13.
Heindl, Andreas, Ivana Šestak, Kuban D. Naidoo, et al.. (2017). Relevance of Spatial Heterogeneity of Immune Infiltration for Predicting Risk of Recurrence After Endocrine Therapy of ER+ Breast Cancer. JNCI Journal of the National Cancer Institute. 110(2). 166–175. 114 indexed citations
14.
Booth, Thomas C., Timothy J. Larkin, Yinyin Yuan, et al.. (2017). Analysis of heterogeneity in T2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma. PLoS ONE. 12(5). e0176528–e0176528. 31 indexed citations
15.
Khan, Adnan Mujahid & Yinyin Yuan. (2016). Biopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score. Scientific Reports. 6(1). 36231–36231. 26 indexed citations
16.
Natrajan, Rachael, Heba Sailem, Faraz K. Mardakheh, et al.. (2016). Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology–Genomic Integration Analysis. PLoS Medicine. 13(2). e1001961–e1001961. 94 indexed citations
17.
Yuan, Yinyin, et al.. (2015). Computational pathology: Exploring the spatial dimension of tumor ecology. Cancer Letters. 380(1). 296–303. 50 indexed citations
18.
Maley, Carlo C., Konrad Koelble, Rachael Natrajan, Athena Aktipis, & Yinyin Yuan. (2015). An ecological measure of immune-cancer colocalization as a prognostic factor for breast cancer. Breast Cancer Research. 17(1). 131–131. 71 indexed citations
19.
Jäger, Roland, Gabriele Migliorini, Marc Henrion, et al.. (2015). Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci. Nature Communications. 6(1). 6178–6178. 146 indexed citations
20.
Lan, Chunyan, Andreas Heindl, Xin Huang, et al.. (2015). Quantitative histology analysis of the ovarian tumour microenvironment. Scientific Reports. 5(1). 16317–16317. 31 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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