Yi Lin

38.5k total citations · 4 hit papers
299 papers, 9.1k citations indexed

About

Yi Lin is a scholar working on Oncology, Molecular Biology and Hematology. According to data from OpenAlex, Yi Lin has authored 299 papers receiving a total of 9.1k indexed citations (citations by other indexed papers that have themselves been cited), including 159 papers in Oncology, 74 papers in Molecular Biology and 65 papers in Hematology. Recurrent topics in Yi Lin's work include CAR-T cell therapy research (134 papers), Multiple Myeloma Research and Treatments (56 papers) and Lymphoma Diagnosis and Treatment (33 papers). Yi Lin is often cited by papers focused on CAR-T cell therapy research (134 papers), Multiple Myeloma Research and Treatments (56 papers) and Lymphoma Diagnosis and Treatment (33 papers). Yi Lin collaborates with scholars based in United States, China and France. Yi Lin's co-authors include Anna Solovey, Robert P. Hebbel, Daniel J. Weisdorf, Allan B. Dietz, Sattva S. Neelapu, Frederick L. Locke, Michael P. Gustafson, Peggy A. Bulur, William G. Wierda and Naval Daver and has published in prestigious journals such as New England Journal of Medicine, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Yi Lin

274 papers receiving 8.9k citations

Hit Papers

Chimeric antigen receptor... 1997 2026 2006 2016 2017 2000 1997 2022 500 1000 1.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yi Lin 4.9k 3.8k 2.0k 1.8k 1.3k 299 9.1k
Julie R. Park 3.6k 0.7× 3.3k 0.9× 972 0.5× 305 0.2× 715 0.5× 185 8.5k
Torsten Tonn 3.5k 0.7× 2.9k 0.8× 3.6k 1.8× 1.0k 0.6× 2.7k 2.1× 162 9.7k
Catriona Jamieson 4.1k 0.8× 6.7k 1.7× 1.9k 1.0× 3.4k 1.9× 2.9k 2.2× 187 12.2k
Carmelo Carlo‐Stella 3.0k 0.6× 2.4k 0.6× 2.1k 1.0× 2.4k 1.4× 3.4k 2.6× 350 9.1k
Pablo Menéndez 1.4k 0.3× 5.1k 1.3× 706 0.3× 1.2k 0.7× 1.2k 0.9× 233 8.1k
Jane L. Liesveld 2.3k 0.5× 2.8k 0.7× 1.6k 0.8× 3.7k 2.1× 1.4k 1.1× 252 8.3k
Ulrich Dührsen 3.0k 0.6× 2.2k 0.6× 3.2k 1.6× 3.1k 1.7× 3.3k 2.5× 283 10.3k
Steven M. Devine 3.4k 0.7× 2.2k 0.6× 3.0k 1.5× 6.1k 3.4× 3.1k 2.4× 318 11.0k
Josef Vormoor 3.5k 0.7× 3.2k 0.8× 1.5k 0.7× 2.7k 1.5× 938 0.7× 117 7.8k
Ivan Borrello 7.3k 1.5× 3.3k 0.9× 7.3k 3.6× 3.5k 2.0× 916 0.7× 148 13.0k

Countries citing papers authored by Yi Lin

Since Specialization
Citations

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

Fields of papers citing papers by Yi Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yi Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Yi Lin. A scholar is included among the top collaborators of Yi Lin 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 Yi Lin. Yi Lin 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
2.
Binder, Moritz, Joselle Cook, Morie A. Gertz, et al.. (2025). The ratio of brain to liver glucose activity and disease activity in multiple myeloma. Blood Cancer Journal. 15(1). 90–90.
3.
Cook, Joselle, Rahma Warsame, Francis K. Buadi, et al.. (2025). Interleukin-6 is a highly prognostic biomarker for POEMS syndrome. Leukemia. 39(9). 2281–2284.
5.
Gile, Jennifer, Matthew J. Maurer, Gordon Ruan, et al.. (2024). Low magnesium levels and prognosis in newly diagnosed diffuse large B-cell lymphoma. The Oncologist. 29(12). e1779–e1782.
6.
Wickland, Daniel P., Erik Jessen, Brian M. Necela, et al.. (2024). Comprehensive profiling of cancer neoantigens from aberrant RNA splicing. Journal for ImmunoTherapy of Cancer. 12(5). e008988–e008988. 4 indexed citations
7.
Saifi, Omran, Scott C. Lester, William G. Breen, et al.. (2023). Incorporating radiation with anti‐CD19 chimeric antigen receptor T‐cell therapy for relapsed/refractory non‐Hodgkin lymphoma: A multicenter consensus approach. American Journal of Hematology. 99(1). 124–134. 9 indexed citations
8.
Zhang, Jinwen, Xiaorui Liu, Lin Rao, et al.. (2023). Adverse obstetric and perinatal outcomes of patients with history of recurrent miscarriage: a retrospective cohort study. Fertility and Sterility. 120(3). 626–634. 8 indexed citations
9.
Rejeski, Kai, Doris K. Hansen, Yucai Wang, et al.. (2023). Applying the Novel EHA/EBMT Grading System for Icaht Following CAR-T Therapy: Comparative Incidence across Disease Entities and Association with Infections and Mortality. Blood. 142(Supplement 1). 359–359. 1 indexed citations
10.
Bansal, Radhika, Jeremy T. Larsen, Matthew Hathcock, et al.. (2023). Prognostic value of early bone marrow MRD status in CAR-T therapy for myeloma. Blood Cancer Journal. 13(1). 47–47. 13 indexed citations
12.
Abdallah, Nadine, Alexandra N. Smith, Susan M. Geyer, et al.. (2023). Conditional survival in multiple myeloma and impact of prognostic factors over time. Blood Cancer Journal. 13(1). 78–78. 12 indexed citations
13.
Bansal, Radhika, Jeremy T. Larsen, Matthew Hathcock, et al.. (2022). Prognostic Value of Early Bone Marrow MRD Status in CAR-T Therapy for Myeloma. Transplantation and Cellular Therapy. 28(3). S186–S187. 2 indexed citations
14.
Ye, Shuting, et al.. (2022). LncRNA OR2A1‐AS1 index predicts survival in germinal center‐like diffuse large B‐cell lymphoma. Journal of Clinical Laboratory Analysis. 36(10). e24680–e24680. 5 indexed citations
15.
Iqbal, Madiha, Radhika Bansal, Allison Rosenthal, et al.. (2022). Impact of Rituximab and Corticosteroids on Late Cytopenias Post-Chimeric Antigen Receptor T Cell Therapy. Transplantation and Cellular Therapy. 28(10). 668.e1–668.e6. 5 indexed citations
16.
Khurana, Arushi, Matthew Hathcock, Thomas M. Habermann, et al.. (2021). Lines of Therapy before Autologous Stem Cell Transplant (ASCT) and CAR-T Infusion Affect Outcomes in Aggressive Non-Hodgkin’s Lymphoma (NHL). Transplantation and Cellular Therapy. 27(3). S45–S47. 1 indexed citations
17.
Berdeja, Jesús G., Noopur Raje, David S. Siegel, et al.. (2021). Efficacy and Safety of Idecabtagene Vicleucel (ide-cel, bb2121) in Elderly Patients with Relapsed and Refractory Multiple Myeloma: KarMMa Subgroup Analysis. Transplantation and Cellular Therapy. 27(3). S397–S398. 2 indexed citations
18.
Gustafson, Michael P., Yi Lin, Jonathan Bleeker, et al.. (2015). Intratumoral CD14+ Cells and Circulating CD14+HLA-DRlo/neg Monocytes Correlate with Decreased Survival in Patients with Clear Cell Renal Cell Carcinoma. Clinical Cancer Research. 21(18). 4224–4233. 38 indexed citations
19.
Leung, Nelson, Shaji Kumar, Siobhán Glavey, et al.. (2015). The impact of dialysis on the survival of patients with immunoglobulin light chain (AL) amyloidosis undergoing autologous stem cell transplantation. Nephrology Dialysis Transplantation. 31(8). 1284–1289. 22 indexed citations
20.
Kapoor, Prashant, Shaji Kumar, Angela Dispenzieri, et al.. (2013). Importance of Achieving Stringent Complete Response After Autologous Stem-Cell Transplantation in Multiple Myeloma. Journal of Clinical Oncology. 31(36). 4529–4535. 120 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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