Xiang-Chun Ju

1.2k total citations · 1 hit paper
17 papers, 796 citations indexed

About

Xiang-Chun Ju is a scholar working on Molecular Biology, Developmental Neuroscience and Cell Biology. According to data from OpenAlex, Xiang-Chun Ju has authored 17 papers receiving a total of 796 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Developmental Neuroscience and 4 papers in Cell Biology. Recurrent topics in Xiang-Chun Ju's work include Neurogenesis and neuroplasticity mechanisms (10 papers), RNA Research and Splicing (4 papers) and Pluripotent Stem Cells Research (2 papers). Xiang-Chun Ju is often cited by papers focused on Neurogenesis and neuroplasticity mechanisms (10 papers), RNA Research and Splicing (4 papers) and Pluripotent Stem Cells Research (2 papers). Xiang-Chun Ju collaborates with scholars based in China, Japan and Germany. Xiang-Chun Ju's co-authors include Zhen‐Ge Luo, Xin-Yao Sun, Libing Shen, Peng-Ming Zeng, Yuejun Chen, Yingying Zhou, Yang Li, Cai-Yun Deng, Wenliang Lei and Tieqiao Wen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Xiang-Chun Ju

17 papers receiving 783 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.

Generation of vascularized brain organoids to study neurovascular interactions

2022 222 citations Xin-Yao Sun, Xiang-Chun Ju et al. eLife profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiang-Chun Ju China	11	481	139	128	125	123	17	796
Jonas Simon Fleck Switzerland	9	724 1.5×	144 1.0×	90 0.7×	123 1.0×	105 0.9×	11	895
Takaaki Kuwajima United States	13	608 1.3×	116 0.8×	280 2.2×	115 0.9×	156 1.3×	20	1.0k
Alejandro De Los Angeles United States	15	1.0k 2.1×	157 1.1×	104 0.8×	78 0.6×	171 1.4×	32	1.3k
Silvia Velasco United States	12	944 2.0×	222 1.6×	197 1.5×	279 2.2×	85 0.7×	18	1.3k
Cindy Huang United States	9	748 1.6×	174 1.3×	228 1.8×	94 0.8×	93 0.8×	10	980
Keerthana Devarajan United States	7	740 1.5×	105 0.8×	65 0.5×	50 0.4×	77 0.6×	7	1.1k
Nadejda M. Tsankova United States	18	543 1.1×	79 0.6×	155 1.2×	104 0.8×	56 0.5×	58	1.1k
Kevin J. Kim United States	12	850 1.8×	173 1.2×	226 1.8×	69 0.6×	160 1.3×	16	1.2k
Kee-Pyo Kim Germany	20	1.0k 2.2×	200 1.4×	171 1.3×	121 1.0×	158 1.3×	35	1.3k
Neal D. Amin United States	11	596 1.2×	185 1.3×	236 1.8×	242 1.9×	49 0.4×	14	906

Countries citing papers authored by Xiang-Chun Ju

Since Specialization

Citations

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

Fields of papers citing papers by Xiang-Chun Ju

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiang-Chun Ju. 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 Xiang-Chun Ju. The network helps show where Xiang-Chun Ju may publish in the future.

Co-authorship network of co-authors of Xiang-Chun Ju

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

All Works

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17 of 17 papers shown

Ju, Xiang-Chun, Shin‐Yu Lee, Laís Ceschini Machado, et al.. (2025). The activity and expression of adenylosuccinate lyase were reduced during modern human evolution, affecting brain and behavior. Proceedings of the National Academy of Sciences. 122(32). e2508540122–e2508540122. 1 indexed citations

Zeng, Peng-Ming, Xin-Yao Sun, Yang Li, et al.. (2025). Thymosin beta 4 as an Alzheimer disease intervention target identified using human brain organoids. Stem Cell Reports. 20(9). 102601–102601. 1 indexed citations

Sun, Xin-Yao, Xiang-Chun Ju, Yang Li, et al.. (2022). Generation of vascularized brain organoids to study neurovascular interactions. eLife. 11. 222 indexed citations breakdown →

Xiao, Qi, et al.. (2021). The CTNNBIP1-CLSTN1 fusion transcript regulates human neocortical development. Cell Reports. 35(13). 109290–109290. 10 indexed citations

Ju, Xiang-Chun, Anne Weigert, Sabina Kanton, et al.. (2021). Comparison of induced neurons reveals slower structural and functional maturation in humans than in apes. eLife. 10. 38 indexed citations

Xiao, Qi, et al.. (2021). TBC1D3 promotes neural progenitor proliferation by suppressing the histone methyltransferase G9a. Science Advances. 7(3). 26 indexed citations

Ju, Xiang-Chun, Yijun Cai, Xin-Yao Sun, et al.. (2020). Heterogeneous nuclear ribonucleoprotein A3a controls mitotic progression of neural progenitors via interaction with cohesin. Development. 147(10). 12 indexed citations

Peng, Jian, Xiao Qi, Libing Shen, et al.. (2018). Single-cell transcriptomes reveal molecular specializations of neuronal cell types in the developing cerebellum. Journal of Molecular Cell Biology. 11(8). 636–648. 26 indexed citations

Jin, Mingzhu, et al.. (2017). Organoids: An intermediate modeling platform in precision oncology. Cancer Letters. 414. 174–180. 66 indexed citations

10.

Ju, Xiang-Chun, et al.. (2017). [Molecular and cellular mechanisms of cortical expansion and folding in brain development and evolution].. PubMed. 69(4). 485–497. 1 indexed citations

11.

Ju, Xiang-Chun, Kong-Yan Wu, Yang Zhou, et al.. (2016). The hominoid-specific gene TBC1D3 promotes generation of basal neural progenitors and induces cortical folding in mice. eLife. 5. 107 indexed citations

12.

Deng, Cai-Yun, Wenliang Lei, Xiaohui Xu, et al.. (2014). JIP1 Mediates Anterograde Transport of Rab10 Cargos during Neuronal Polarization. Journal of Neuroscience. 34(5). 1710–1723. 50 indexed citations

13.

Lei, Wenliang, et al.. (2012). Laminin/β1 integrin signal triggers axon formation by promoting microtubule assembly and stabilization. Cell Research. 22(6). 954–972. 68 indexed citations

14.

Zhang, Luwen, Xiang-Chun Ju, Yumin Cheng, Xiuyun Guo, & Tieqiao Wen. (2011). Identifying Tmem59 related gene regulatory network of mouse neural stem cell from a compendium of expression profiles. BMC Systems Biology. 5(1). 152–152. 25 indexed citations

15.

Wei, Xiaoming, Fan Jin, Yinghui Ye, et al.. (2011). A novel mutation of IDS gene in a Chinese patient with mucopolysaccharidosis II by next-generation sequencing. Clinica Chimica Acta. 412(23-24). 2340–2342. 8 indexed citations

16.

Wei, Xiaoming, Xiang-Chun Ju, Xin Yi, et al.. (2011). Identification of Sequence Variants in Genetic Disease-Causing Genes Using Targeted Next-Generation Sequencing. PLoS ONE. 6(12). e29500–e29500. 134 indexed citations

17.

Zhao, Xing‐Ming, et al.. (2009). Understanding the Biological Functions of DCF1 Based on Molecular Interaction Network. 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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