Cheryl Kim

2.5k total citations
8 papers, 330 citations indexed

About

Cheryl Kim is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Cheryl Kim has authored 8 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Immunology and 2 papers in Infectious Diseases. Recurrent topics in Cheryl Kim's work include Single-cell and spatial transcriptomics (5 papers), Immune cells in cancer (3 papers) and Acute Myeloid Leukemia Research (2 papers). Cheryl Kim is often cited by papers focused on Single-cell and spatial transcriptomics (5 papers), Immune cells in cancer (3 papers) and Acute Myeloid Leukemia Research (2 papers). Cheryl Kim collaborates with scholars based in United States, Sri Lanka and Nicaragua. Cheryl Kim's co-authors include Catherine C. Hedrick, Paola Marcovecchio, Huy Q. Dinh, Amy Blatchley, Pandurangan Vijayanand, Grégory Seumois, Runpei Wu, Lindsey E. Padgett, Yanfang Peipei Zhu and Ariel Madrigal and has published in prestigious journals such as The Journal of Immunology, Scientific Reports and Arteriosclerosis Thrombosis and Vascular Biology.

In The Last Decade

Cheryl Kim

8 papers receiving 327 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cheryl Kim United States	6	245	99	50	41	33	8	330
Francisco M. Bianchetto-Aguilera Italy	9	314 1.3×	94 0.9×	48 1.0×	34 0.8×	35 1.1×	15	423
Gabriela Trentin Scortegagna Brazil	5	255 1.0×	85 0.9×	28 0.6×	44 1.1×	82 2.5×	10	371
Sibel Durlanik Germany	8	215 0.9×	66 0.7×	63 1.3×	34 0.8×	30 0.9×	10	305
Catherine Nakao United States	3	212 0.9×	97 1.0×	23 0.5×	24 0.6×	43 1.3×	5	291
Markus M. Xie United States	12	370 1.5×	56 0.6×	42 0.8×	20 0.5×	23 0.7×	20	491
Miglena G. Prabagar United States	7	312 1.3×	110 1.1×	23 0.5×	27 0.7×	44 1.3×	12	423
Haruna Otsuka Japan	9	310 1.3×	73 0.7×	71 1.4×	14 0.3×	36 1.1×	12	419
Tina Nham Canada	8	256 1.0×	63 0.6×	140 2.8×	24 0.6×	28 0.8×	13	336
Tineke van der Pouw‐Kraan Netherlands	7	294 1.2×	32 0.3×	40 0.8×	43 1.0×	49 1.5×	10	414
Fanny Delfanti Italy	9	186 0.8×	43 0.4×	92 1.8×	39 1.0×	70 2.1×	11	342

Countries citing papers authored by Cheryl Kim

Since Specialization

Citations

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

Fields of papers citing papers by Cheryl Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheryl Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Cheryl Kim. A scholar is included among the top collaborators of Cheryl Kim 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 Cheryl Kim. Cheryl Kim 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:

8 of 8 papers shown

1.

Ecklu-Mensah, Gertrude, et al.. (2024). Modulating the human gut microbiome and health markers through kombucha consumption: a controlled clinical study. Scientific Reports. 14(1). 31647–31647. 8 indexed citations

2.

Zhu, Yanfang Peipei, Lindsey E. Padgett, Huy Q. Dinh, et al.. (2019). Preparation of Whole Bone Marrow for Mass Cytometry Analysis of Neutrophil-lineage Cells. Journal of Visualized Experiments. 8 indexed citations

3.

Tian, Yuan, Grégory Seumois, Luzia Maria de‐Oliveira‐Pinto, et al.. (2019). Molecular Signatures of Dengue Virus-Specific IL-10/IFN-γ Co-producing CD4 T Cells and Their Association with Dengue Disease. Cell Reports. 29(13). 4482–4495.e4. 26 indexed citations

4.

Zhu, Yanfang Peipei, Lindsey E. Padgett, Huy Q. Dinh, et al.. (2019). Preparation of Whole Bone Marrow for Mass Cytometry Analysis of Neutrophil-lineage Cells. Journal of Visualized Experiments. 1 indexed citations

5.

Zhu, Yanfang Peipei, Lindsey E. Padgett, Huy Q. Dinh, et al.. (2018). Identification of an Early Unipotent Neutrophil Progenitor with Pro-tumoral Activity in Mouse and Human Bone Marrow. Cell Reports. 24(9). 2329–2341.e8. 151 indexed citations

6.

Carlin, Aaron F., Jinsheng Wen, Edward A. Vizcarra, et al.. (2018). A longitudinal systems immunologic investigation of acute Zika virus infection in an individual infected while traveling to Caracas, Venezuela. PLoS neglected tropical diseases. 12(12). e0007053–e0007053. 7 indexed citations

7.

Hamers, Anouk A.J., Huy Q. Dinh, Graham D. Thomas, et al.. (2018). Human Monocyte Heterogeneity as Revealed by High-Dimensional Mass Cytometry. Arteriosclerosis Thrombosis and Vascular Biology. 39(1). 25–36. 126 indexed citations

8.

Hamers, Anouk A.J., Graham D. Thomas, Cheryl Kim, & Catherine C. Hedrick. (2017). Diversity of Human Monocyte Subsets Revealed by CyTOF Mass Cytometry. The Journal of Immunology. 198(Supplement_1). 208.5–208.5. 3 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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