Kun Leng

1.9k total citations · 2 hit papers
16 papers, 905 citations indexed

About

Kun Leng is a scholar working on Neurology, Molecular Biology and Physiology. According to data from OpenAlex, Kun Leng has authored 16 papers receiving a total of 905 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Neurology, 7 papers in Molecular Biology and 4 papers in Physiology. Recurrent topics in Kun Leng's work include Neuroinflammation and Neurodegeneration Mechanisms (10 papers), Single-cell and spatial transcriptomics (3 papers) and CRISPR and Genetic Engineering (3 papers). Kun Leng is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (10 papers), Single-cell and spatial transcriptomics (3 papers) and CRISPR and Genetic Engineering (3 papers). Kun Leng collaborates with scholars based in United States, Brazil and Germany. Kun Leng's co-authors include Martin Kampmann, Nina M. Dräger, Sayed Hadi Hashemi, Andrew Singleton, Jason Hong, Mike A. Nalls, Faraz Faghri, Rui Yan, Ke Xu and Emmy Li and has published in prestigious journals such as Nature Communications, Nature Neuroscience and Molecular Psychiatry.

In The Last Decade

Kun Leng

14 papers receiving 898 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.

Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease

2021 271 citations Kun Leng, Emmy Li et al. Nature Neuroscience profile →
Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis

2021 229 citations Ruilin Tian, Jason Hong et al. Nature Neuroscience profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kun Leng United States	9	485	343	229	113	91	16	905
Seung-Hye Lee United States	11	520 1.1×	436 1.3×	279 1.2×	133 1.2×	226 2.5×	13	1.1k
Sebastian Guelfi United Kingdom	9	529 1.1×	246 0.7×	246 1.1×	131 1.2×	101 1.1×	12	1.1k
Xianxiao Zhou United States	14	458 0.9×	145 0.4×	187 0.8×	83 0.7×	56 0.6×	34	751
Catherine Marneffe Belgium	6	252 0.5×	343 1.0×	93 0.4×	186 1.6×	83 0.9×	7	632
Jessica L. Larson United States	11	358 0.7×	541 1.6×	284 1.2×	144 1.3×	274 3.0×	14	964
Parham Nejad United States	9	583 1.2×	324 0.9×	248 1.1×	61 0.5×	167 1.8×	18	1.0k
Indigo V.L. Rose United States	11	359 0.7×	557 1.6×	202 0.9×	157 1.4×	212 2.3×	14	912
Samuel Morabito United States	8	528 1.1×	217 0.6×	140 0.6×	45 0.4×	148 1.6×	14	840
Bartłomiej Gielniewski Poland	15	326 0.7×	399 1.2×	81 0.4×	87 0.8×	253 2.8×	34	934

Countries citing papers authored by Kun Leng

Since Specialization

Citations

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

Fields of papers citing papers by Kun Leng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Leng

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

16 of 16 papers shown

McQuade, Amanda, Nina M. Dräger, Sydney M. Sattler, et al.. (2025). CRISPRi-based screen of autism spectrum disorder risk genes in microglia uncovers roles of ADNP in microglia endocytosis and synaptic pruning. Molecular Psychiatry. 30(9). 4176–4193. 4 indexed citations

Leng, Kun, Mervyn Maze, & Odmara L. Barreto Chang. (2025). Emerging biomarkers of postoperative delirium at the intersection of neuroinflammation and neurodegeneration. Frontiers in Aging Neuroscience. 17. 1632947–1632947.

Yadav, Alka, Annika Schmidt, Kun Leng, et al.. (2024). Evaluation of AAV Capsids and Delivery Approaches for Hereditary Hemorrhagic Telangiectasia Gene Therapy. Translational Stroke Research. 16(3). 914–924. 3 indexed citations

Leng, Kun, Brendan Rooney, Frank McCarthy, et al.. (2024). mTOR activation induces endolysosomal remodeling and nonclassical secretion of IL-32 via exosomes in inflammatory reactive astrocytes. Journal of Neuroinflammation. 21(1). 198–198. 9 indexed citations

Leng, Kun, Cathryn R. Cadwell, W. Patrick Devine, et al.. (2024). Cell-Type Specificity of Mosaic Chromosome 1q Gain Resolved by snRNA-seq in a Case of Epilepsy With Hyaline Protoplasmic Astrocytopathy. Neurology Genetics. 10(2). e200142–e200142. 1 indexed citations

Majo, Martina de, Mark Koontz, Elise Marsan, et al.. (2023). Granulin loss of function in human mature brain organoids implicates astrocytes in TDP-43 pathology. Stem Cell Reports. 18(3). 706–719. 19 indexed citations

Dräger, Nina M., Sydney M. Sattler, Cindy Huang, et al.. (2022). A CRISPRi/a platform in human iPSC-derived microglia uncovers regulators of disease states. Nature Neuroscience. 25(9). 1149–1162. 123 indexed citations

Replogle, Joseph M., Jessica L. Bonnar, Angela N. Pogson, et al.. (2022). Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors. eLife. 11. 52 indexed citations

Kim, Hyosung, Kun Leng, Jinhee Park, et al.. (2022). Reactive astrocytes transduce inflammation in a blood-brain barrier model through a TNF-STAT3 signaling axis and secretion of alpha 1-antichymotrypsin. Nature Communications. 13(1). 6581–6581. 99 indexed citations

10.

Leng, Kun & Martin Kampmann. (2022). Towards elucidating disease-relevant states of neurons and glia by CRISPR-based functional genomics. Genome Medicine. 14(1). 130–130. 3 indexed citations

11.

Pereira, Felipe Luiz, Song Hua Li, Martin Kampmann, et al.. (2022). Pathological Validation of RORB and CDH9 as Selectively Vulnerable Neurons in Alzheimer’s Disease. Alzheimer s & Dementia. 18(S3).

12.

Leng, Kun, Indigo V.L. Rose, Hyosung Kim, et al.. (2022). CRISPRi screens in human iPSC-derived astrocytes elucidate regulators of distinct inflammatory reactive states. Nature Neuroscience. 25(11). 1528–1542. 78 indexed citations

13.

Chin, Marcus Y., Kean-Hooi Ang, Carolina Alquézar, et al.. (2022). Phenotypic Screening Using High-Content Imaging to Identify Lysosomal pH Modulators in a Neuronal Cell Model. ACS Chemical Neuroscience. 13(10). 1505–1516. 8 indexed citations

14.

Tian, Ruilin, Jason Hong, Sayed Hadi Hashemi, et al.. (2021). Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis. Nature Neuroscience. 24(7). 1020–1034. 229 indexed citations breakdown →

15.

Leng, Kun, Emmy Li, Rana Eser, et al.. (2021). Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease. Nature Neuroscience. 24(2). 276–287. 271 indexed citations breakdown →

16.

Ehrenberg, Alexander J., Kun Leng, Israel Hernández, et al.. (2021). Patterns of neuronal Rhes as a novel hallmark of tauopathies. Acta Neuropathologica. 141(5). 651–666. 6 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.

Explore authors with similar magnitude of impact