Changxin Wan

3.2k total citations · 2 hit papers
18 papers, 1.6k citations indexed

About

Changxin Wan is a scholar working on Molecular Biology, Automotive Engineering and Control and Systems Engineering. According to data from OpenAlex, Changxin Wan has authored 18 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 4 papers in Automotive Engineering and 3 papers in Control and Systems Engineering. Recurrent topics in Changxin Wan's work include Genomics and Chromatin Dynamics (6 papers), Vehicle emissions and performance (4 papers) and Single-cell and spatial transcriptomics (3 papers). Changxin Wan is often cited by papers focused on Genomics and Chromatin Dynamics (6 papers), Vehicle emissions and performance (4 papers) and Single-cell and spatial transcriptomics (3 papers). Changxin Wan collaborates with scholars based in United States, China and Taiwan. Changxin Wan's co-authors include X. Shirley Liu, Wubing Zhang, Jing Zhang, Jingxin Fu, Karen Li, Peng Jiang, Clifford A. Meyer, Rongbin Zheng, Myles Brown and Qian Qin and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Genome biology.

In The Last Decade

Changxin Wan

16 papers receiving 1.6k 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.

Large-scale public data reuse to model immunotherapy response and resistance

2020 697 citations Jingxin Fu, Karen Li et al. Genome Medicine profile →
Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis

2018 524 citations Rongbin Zheng, Changxin Wan et al. Nucleic Acids Research profile →

Peers

Changxin Wan

PRM

ONCOL

IMMUN

Aiai Shi China

Ya‐Ru Miao China

Rongbin Zheng China

Gui‐Yan Xie China

Kenneth Aldape United States

Jackeline Agorreta Spain

Ziyu Dai China

Diego M. Marzese United States

Kenan Zhang China

Aiai Shi China

Changxin Wan

1.1k ×1.0

433 ×0.8

PRM

521 ×1.1

315 ×0.8

ONCOL

401 ×1.3

IMMUN

Citations per year, relative to Changxin Wan Changxin Wan (= 1×) peers Aiai Shi

Countries citing papers authored by Changxin Wan

Since Specialization

Citations

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

Fields of papers citing papers by Changxin Wan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changxin Wan

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

18 of 18 papers shown

Wan, Changxin, et al.. (2025). Comparative analysis of gene regulation in single cells using Compass. Cell Reports Methods. 5(5). 101035–101035.

Wan, Changxin, et al.. (2024). Developing a Novel Eco-Driving Strategy for Connected and Automated Vehicle at Isolated Signalized Intersection. 1–6.

Wan, Changxin, et al.. (2024). Multi-objective coordinated control strategy for mixed traffic with partially connected and automated vehicles in urban corridors. Physica A Statistical Mechanics and its Applications. 635. 129485–129485. 7 indexed citations

Wan, Changxin, et al.. (2024). Developing A Novel Dynamic Bus Lane Control Strategy With Eco-Driving Under Partially Connected Vehicle Environment. IEEE Transactions on Intelligent Transportation Systems. 25(6). 5919–5934. 5 indexed citations

Wan, Changxin, Dan Jia, Jian Li, et al.. (2023). Synergism Lubrication of Graphene and Carbon Nanotube in Polymeric Composites Under Drying Sliding Condition. SSRN Electronic Journal. 1 indexed citations

Wang, Mu‐En, et al.. (2023). Nuclear PTEN Regulates Thymidylate Biosynthesis in Human Prostate Cancer Cell Lines. Metabolites. 13(8). 939–939. 2 indexed citations

Zhang, Yi, Guanjue Xiang, Zexian Zeng, et al.. (2023). MetaTiME integrates single-cell gene expression to characterize the meta-components of the tumor immune microenvironment. Nature Communications. 14(1). 2634–2634. 11 indexed citations

Chiu, Shao‐Chih, et al.. (2023). The crescent-like Golgi ribbon is shaped by the Ajuba/PRMT5/Aurora-A complex-modified HURP. Cell Communication and Signaling. 21(1). 156–156. 1 indexed citations

Wan, Changxin, et al.. (2022). Connected eco‐driving for electric buses along signalized arterials with bus stops. IET Intelligent Transport Systems. 17(3). 579–591. 8 indexed citations

10.

Qin, Qian, Jing‐Yu Fan, Rongbin Zheng, et al.. (2020). Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data. Genome biology. 21(1). 168 indexed citations

11.

Fu, Jingxin, Karen Li, Wubing Zhang, et al.. (2020). Large-scale public data reuse to model immunotherapy response and resistance. Genome Medicine. 12(1). 21–21. 697 indexed citations breakdown →

12.

Wang, Chenfei, Dongqing Sun, Xin Huang, et al.. (2020). Integrative analyses of single-cell transcriptome and regulome using MAESTRO. Genome biology. 21(1). 198–198. 122 indexed citations

13.

Chen, Chen-Hao, Rongbin Zheng, Collin Tokheim, et al.. (2020). Determinants of transcription factor regulatory range. Nature Communications. 11(1). 2472–2472. 39 indexed citations

14.

Zheng, Rongbin, Xin Dong, Changxin Wan, et al.. (2020). Cistrome Data Browser and Toolkit: analyzing human and mouse genomic data using compendia of ChIP‐seq and chromatin accessibility data. Quantitative Biology. 8(3). 267–276. 8 indexed citations

15.

Li, Shaojuan, Changxin Wan, Rongbin Zheng, et al.. (2019). Cistrome-GO: a web server for functional enrichment analysis of transcription factor ChIP-seq peaks. Nucleic Acids Research. 47(W1). W206–W211. 52 indexed citations

16.

Chiu, Shao‐Chih, Kun‐Chieh Chen, Jiun‐Yi Hsia, et al.. (2019). Overexpression of Aurora-A bypasses cytokinesis through phosphorylation of suppressed in lung cancer. American Journal of Physiology-Cell Physiology. 317(3). C600–C612. 2 indexed citations

17.

Qin, Qian, Jing‐Yu Fan, Rongbin Zheng, et al.. (2019). Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

18.

Zheng, Rongbin, Changxin Wan, Shenglin Mei, et al.. (2018). Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis. Nucleic Acids Research. 47(D1). D729–D735. 524 indexed citations breakdown →

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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