Yuhong Ning

2.1k total citations · 1 hit paper
19 papers, 1.2k citations indexed

About

Yuhong Ning is a scholar working on Molecular Biology, Cancer Research and Hematology. According to data from OpenAlex, Yuhong Ning has authored 19 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Cancer Research and 7 papers in Hematology. Recurrent topics in Yuhong Ning's work include Cancer Genomics and Diagnostics (8 papers), Epigenetics and DNA Methylation (6 papers) and Multiple Myeloma Research and Treatments (4 papers). Yuhong Ning is often cited by papers focused on Cancer Genomics and Diagnostics (8 papers), Epigenetics and DNA Methylation (6 papers) and Multiple Myeloma Research and Treatments (4 papers). Yuhong Ning collaborates with scholars based in United States, Switzerland and Canada. Yuhong Ning's co-authors include Anjan Thakurta, Anita K. Gandhi, Rajesh Chopra, Jian Kang, Courtney G. Havens, Anke Klippel, Thomas O. Daniel, Peter Schäfer, Michelle F. Waldman and Thomas A. Conklin and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Blood.

In The Last Decade

Yuhong Ning

18 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Immunomodulatory agents lenalidomide and pomalidomide co‐stimulate T cells by inducing degradation of T cell repressors I karos and A iolos via modulation of the E 3 ubiquitin ligase complex CRL 4 ^CRBN

2013 457 citations Anita K. Gandhi, Jian Kang et al. British Journal of Haematology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yuhong Ning United States	9	837	547	386	155	111	19	1.2k
Victoria M. Garbitt United States	8	932 1.1×	729 1.3×	461 1.2×	155 1.0×	202 1.8×	16	1.3k
Edward Allan R. Sison United States	11	1.5k 1.8×	844 1.5×	403 1.0×	220 1.4×	87 0.8×	22	1.9k
Daniel Magoon United States	8	1.5k 1.8×	893 1.6×	353 0.9×	185 1.2×	87 0.8×	22	1.9k
Meredith J. Taylor United States	6	1.8k 2.1×	775 1.4×	270 0.7×	117 0.8×	132 1.2×	11	2.0k
Marc‐Steffen Raab Germany	16	570 0.7×	537 1.0×	584 1.5×	399 2.6×	81 0.7×	50	1.2k
Taiju Utsugisawa Japan	15	772 0.9×	188 0.3×	285 0.7×	84 0.5×	106 1.0×	39	1.0k
Jesús Duque‐Afonso Germany	18	684 0.8×	468 0.9×	225 0.6×	161 1.0×	118 1.1×	46	1.1k
Shiyi Yang United States	9	369 0.4×	281 0.5×	377 1.0×	159 1.0×	65 0.6×	16	775
Kristin L.M. Boylan United States	17	375 0.4×	188 0.3×	416 1.1×	329 2.1×	130 1.2×	28	1.0k
Quentin Lécrevisse Spain	16	385 0.5×	397 0.7×	224 0.6×	292 1.9×	64 0.6×	35	933

Countries citing papers authored by Yuhong Ning

Since Specialization

Citations

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

Fields of papers citing papers by Yuhong Ning

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuhong Ning

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

All Works

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19 of 19 papers shown

1.

Guler, Gulfem D., Yuhong Ning, Ceyda Çoruh, et al.. (2024). Plasma cell-free DNA hydroxymethylation profiling reveals anti-PD-1 treatment response and resistance biology in non-small cell lung cancer. Journal for ImmunoTherapy of Cancer. 12(1). e008028–e008028. 10 indexed citations

2.

Polidan, R. S., Jack O. Burns, A. Ignatiev, et al.. (2024). FarView: An in-situ manufactured lunar far side radio array concept for 21-cm Dark Ages cosmology. Advances in Space Research. 74(1). 528–546. 9 indexed citations

3.

Haan, David, Anna Bergamaschi, Yuhong Ning, et al.. (2021). Genome-wide 5hmC profiles to enable cancer detection and tissue of origin classification in breast, colorectal, lung, ovarian, and pancreatic cancers.. Journal of Clinical Oncology. 39(15_suppl). 3044–3044. 1 indexed citations

4.

Guler, Gulfem D., Anna Bergamaschi, David Haan, et al.. (2021). Pancreatic cancer detection using EpiDetect signatures in plasma-derived cell free DNA in high-risk patients with new onset diabetes.. Journal of Clinical Oncology. 39(15_suppl). e16265–e16265.

5.

Sjöström, Martin, Shuang G. Zhao, Eric J. Small, et al.. (2021). 5-hydroxymethylcytosine as a liquid biopsy biomarker in mCRPC.. Journal of Clinical Oncology. 39(6_suppl). 148–148. 3 indexed citations

6.

Guler, Gulfem D., Yuhong Ning, Chin‐Jen Ku, et al.. (2020). Detection of early stage pancreatic cancer using 5-hydroxymethylcytosine signatures in circulating cell free DNA. Nature Communications. 11(1). 5270–5270. 119 indexed citations

7.

Collin, François, Yuhong Ning, Gulfem D. Guler, et al.. (2019). Abstract 1372: Detection of early stage pancreatic cancer using 5–hydroxymethylcytosine signatures in circulating cell free DNA. Cancer Research. 79(13_Supplement). 1372–1372. 1 indexed citations

8.

Collin, François, Yuhong Ning, Gulfem D. Guler, et al.. (2019). Abstract 1372: Detection of early stage pancreatic cancer using 5–hydroxymethylcytosine signatures in circulating cell free DNA. 1372–1372. 1 indexed citations

9.

Zhu, Dan, Shuichan Xu, Gordafaried Deyanat‐Yazdi, et al.. (2018). Synthetic Lethal Strategy Identifies a Potent and Selective TTK and CLK1/2 Inhibitor for Treatment of Triple-Negative Breast Cancer with a Compromised G1–S Checkpoint. Molecular Cancer Therapeutics. 17(8). 1727–1738. 28 indexed citations

10.

Rychak, Emily, Derek Mendy, Tao Shi, et al.. (2016). Pomalidomide in combination with dexamethasone results in synergistic anti‐tumour responses in pre‐clinical models of lenalidomide‐resistant multiple myeloma. British Journal of Haematology. 172(6). 889–901. 40 indexed citations

11.

Bjorklund, Chad C., Ling Lu, Jian Kang, et al.. (2015). Rate of CRL4CRBN substrate Ikaros and Aiolos degradation underlies differential activity of lenalidomide and pomalidomide in multiple myeloma cells by regulation of c-Myc and IRF4. Blood Cancer Journal. 5(10). e354–e354. 154 indexed citations

12.

Gandhi, Anita K., Jian Kang, Courtney G. Havens, et al.. (2013). Immunomodulatory agents lenalidomide and pomalidomide co‐stimulate T cells by inducing degradation of T cell repressors I karos and A iolos via modulation of the E 3 ubiquitin ligase complex CRL 4 ^CRBN . British Journal of Haematology. 164(6). 811–821. 457 indexed citations breakdown →

13.

Kang, Lin, Yuhong Ning, David Dong, et al.. (2013). Characterization and ex vivo Expansion of Human Placenta-Derived Natural Killer Cells for Cancer Immunotherapy. Frontiers in Immunology. 4. 101–101. 37 indexed citations

14.

Thakurta, Anjan, Anita K. Gandhi, Michelle F. Waldman, et al.. (2013). Absence Of Mutation In Cereblon (CRBN) and DNA Damage Binding Protein 1 (DDB1) Genes In Myeloma Cells and Patients and Its Clinical Significance. Blood. 122(21). 3139–3139. 3 indexed citations

15.

Hollenbach, Paul W., Aaron Nguyen, Helen Brady, et al.. (2010). A Comparison of Azacitidine and Decitabine Activities in Acute Myeloid Leukemia Cell Lines. PLoS ONE. 5(2). e9001–e9001. 288 indexed citations

16.

Yang, Dong‐Hua, Thomas Winder, Pierre Bohanes, et al.. (2010). Correlations of mRNA expression levels of genes in the targeted pathways and Kras mutation status in patients with colorectal cancer.. Journal of Clinical Oncology. 28(15_suppl). 10641–10641. 1 indexed citations

17.

MacBeth, Kyle J., Eric Laille, Yuhong Ning, et al.. (2009). A Comparative Pharmacokinetic/Pharmacodynamic (PK/PD) Evaluation of Azacitidine Following Subcutaneous (SC) and Oral Administration in Subjects with Myelodysplastic Syndromes (MDS) or Acute Myelogenous Leukemia (AML), Results From a Phase 1 Study.. Blood. 114(22). 1772–1772. 2 indexed citations

18.

Garcia‐Manero, Guillermo, Steven D. Gore, Barry Skikne, et al.. (2009). A Phase 1, Open-Label, Dose-Escalation Study to Evaluate the Safety, Pharmacokinetics, and Pharmacodynamics of Oral Azacitidine in Patients with Myelodysplastic Syndromes (MDS) or Acute Myelogenous Leukemia (AML).. Blood. 114(22). 117–117. 6 indexed citations

19.

Madhusudan, M. D., Lothar Krause, Yuhong Ning, et al.. (2004). The laboratory information management system (LIMS) for handling the heterogeneous data from high throughput experiments in the post-genome sequencing era. 98–104. 1 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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