Gerald J. Sun

2.0k total citations · 1 hit paper
13 papers, 1.5k citations indexed

About

Gerald J. Sun is a scholar working on Cellular and Molecular Neuroscience, Developmental Neuroscience and Molecular Biology. According to data from OpenAlex, Gerald J. Sun has authored 13 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cellular and Molecular Neuroscience, 6 papers in Developmental Neuroscience and 4 papers in Molecular Biology. Recurrent topics in Gerald J. Sun's work include Neurogenesis and neuroplasticity mechanisms (6 papers), Neuroscience and Neuropharmacology Research (3 papers) and Axon Guidance and Neuronal Signaling (3 papers). Gerald J. Sun is often cited by papers focused on Neurogenesis and neuroplasticity mechanisms (6 papers), Neuroscience and Neuropharmacology Research (3 papers) and Axon Guidance and Neuronal Signaling (3 papers). Gerald J. Sun collaborates with scholars based in United States, United Kingdom and Switzerland. Gerald J. Sun's co-authors include Guo‐li Ming, Hongjun Song, Michael A. Bonaguidi, Jason Shapiro, Michael A. Wheeler, Kimberly M. Christian, Chun Zhong, Juan Song, Derek Y. Hsu and Shaoyu Ge and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Gerald J. Sun

13 papers receiving 1.5k citations

Hit Papers

In Vivo Clonal Analysis Reveals Self-Renewing and Multipo... 2011 2026 2016 2021 2011 200 400 600
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.

  1. In Vivo Clonal Analysis Reveals Self-Renewing and Multipotent Adult Neural Stem Cell Characteristics
    2011 653 citations Michael A. Bonaguidi, Michael A. Wheeler et al. Cell profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gerald J. Sun United States 10 1.1k 659 650 268 181 13 1.5k
Nathan A. DeCarolis United States 12 870 0.8× 557 0.8× 597 0.9× 227 0.8× 149 0.8× 12 1.6k
Xiaoqing Yuan United States 16 801 0.8× 818 1.2× 743 1.1× 367 1.4× 103 0.6× 24 1.6k
Sonja Rakić United Kingdom 24 793 0.8× 802 1.2× 662 1.0× 239 0.9× 223 1.2× 27 1.7k
Silvia De Marchis Italy 23 886 0.8× 705 1.1× 525 0.8× 326 1.2× 108 0.6× 51 1.6k
Giulio Srubek Tomassy United States 15 582 0.6× 628 1.0× 854 1.3× 231 0.9× 268 1.5× 19 1.6k
Ryan Dammerman United States 11 1.1k 1.0× 760 1.2× 926 1.4× 204 0.8× 156 0.9× 17 1.8k
Noah M. Walton United States 14 605 0.6× 419 0.6× 561 0.9× 307 1.1× 180 1.0× 19 1.4k
Matthew Grist United Kingdom 6 1.0k 1.0× 562 0.9× 659 1.0× 377 1.4× 127 0.7× 8 1.5k
Ute Häussler Germany 20 646 0.6× 1.0k 1.6× 625 1.0× 262 1.0× 200 1.1× 33 1.7k
Jean‐Claude Platel United States 21 671 0.6× 596 0.9× 676 1.0× 236 0.9× 168 0.9× 34 1.4k

Countries citing papers authored by Gerald J. Sun

Since Specialization
Citations

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

Fields of papers citing papers by Gerald J. Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gerald J. Sun. 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 Gerald J. Sun. The network helps show where Gerald J. Sun may publish in the future.

Co-authorship network of co-authors of Gerald J. Sun

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

All Works

13 of 13 papers shown
1.
Arango-Argoty, Gustavo, Damián E. Bikiel, Gerald J. Sun, et al.. (2025). AI-driven predictive biomarker discovery with contrastive learning to improve clinical trial outcomes. Cancer Cell. 43(5). 875–890.e8. 9 indexed citations
2.
Arango-Argoty, Gustavo, et al.. (2025). Pretrained transformers applied to clinical studies improve predictions of treatment efficacy and associated biomarkers. Nature Communications. 16(1). 2101–2101. 7 indexed citations
3.
Arango-Argoty, Gustavo, Marzieh Haghighi, Gerald J. Sun, et al.. (2025). An artificial intelligence-based model for prediction of clonal hematopoiesis variants in cell-free DNA samples. npj Precision Oncology. 9(1). 147–147. 1 indexed citations
4.
Sun, Gerald J., Gustavo Arango-Argoty, Gary J. Doherty, et al.. (2024). Machine learning modeling of patient health signals informs long-term survival on immune checkpoint inhibitor therapy. iScience. 27(9). 110634–110634. 2 indexed citations
5.
Verdugo, Carmen Diaz, et al.. (2019). Mating Suppresses Alarm Response in Zebrafish. Current Biology. 29(15). 2541–2546.e3. 24 indexed citations
6.
Sailor, Kurt A., Matthew T. Valley, Martin T. Wiechert, et al.. (2016). Persistent Structural Plasticity Optimizes Sensory Information Processing in the Olfactory Bulb. Neuron. 91(2). 384–396. 44 indexed citations
7.
Sun, Jiaqi, Michael A. Bonaguidi, Heechul Jun, et al.. (2015). A septo-temporal molecular gradient of sfrp3 in the dentate gyrus differentially regulates quiescent adult hippocampal neural stem cell activation. Molecular Brain. 8(1). 52–52. 24 indexed citations
8.
Sun, Gerald J., Yi Zhou, Michael A. Bonaguidi, et al.. (2015). Latent tri-lineage potential of adult hippocampal neural stem cells revealed by Nf1 inactivation. Nature Neuroscience. 18(12). 1722–1724. 30 indexed citations
9.
Sun, Gerald J., Yi Zhou, Jonathan Moss, et al.. (2015). Tangential migration of neuronal precursors of glutamatergic neurons in the adult mammalian brain. Proceedings of the National Academy of Sciences. 112(30). 9484–9489. 93 indexed citations
10.
Song, Juan, Jiaqi Sun, Jonathan Moss, et al.. (2013). Parvalbumin interneurons mediate neuronal circuitry–neurogenesis coupling in the adult hippocampus. Nature Neuroscience. 16(12). 1728–1730. 174 indexed citations
11.
Song, Juan, Chun Zhong, Michael A. Bonaguidi, et al.. (2012). Neuronal circuitry mechanism regulating adult quiescent neural stem-cell fate decision. Nature. 489(7414). 150–154. 400 indexed citations
12.
Bonaguidi, Michael A., Michael A. Wheeler, Jason Shapiro, et al.. (2011). In Vivo Clonal Analysis Reveals Self-Renewing and Multipotent Adult Neural Stem Cell Characteristics. Cell. 145(7). 1142–1155. 653 indexed citations breakdown →
13.
Ray, Aditi, Gerald J. Sun, Leanne Lai-Hang Chan, et al.. (2010). Morphological alterations in retinal neurons in the S334ter-line3 transgenic rat. Cell and Tissue Research. 339(3). 481–491. 47 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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