Anjun Ma

4.0k total citations · 2 hit papers
58 papers, 2.2k citations indexed

About

Anjun Ma is a scholar working on Molecular Biology, Cancer Research and Immunology. According to data from OpenAlex, Anjun Ma has authored 58 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Molecular Biology, 10 papers in Cancer Research and 8 papers in Immunology. Recurrent topics in Anjun Ma's work include Single-cell and spatial transcriptomics (22 papers), Bioinformatics and Genomic Networks (13 papers) and Gene expression and cancer classification (12 papers). Anjun Ma is often cited by papers focused on Single-cell and spatial transcriptomics (22 papers), Bioinformatics and Genomic Networks (13 papers) and Gene expression and cancer classification (12 papers). Anjun Ma collaborates with scholars based in United States, China and Canada. Anjun Ma's co-authors include Qin Ma, Bingqiang Liu, Yuzhou Chang, Ren Qi, Bin Yu, Dong Xu, Cankun Wang, Juexin Wang, Quan Zou and Xiaoying Wang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Anjun Ma

54 papers receiving 2.1k 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.

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

2021 250 citations Juexin Wang, Anjun Ma et al. Nature Communications profile →
Microglia coordinate cellular interactions during spinal cord repair in mice

2022 176 citations Yang Li, Cankun Wang et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anjun Ma United States	24	1.6k	313	192	186	167	58	2.2k
Žiga Avsec Germany	10	2.1k 1.3×	290 0.9×	201 1.0×	147 0.8×	69 0.4×	14	2.8k
Xin Shao China	17	1.1k 0.7×	295 0.9×	76 0.4×	201 1.1×	100 0.6×	44	1.5k
Florian Wagner Germany	23	2.2k 1.4×	584 1.9×	135 0.7×	229 1.2×	50 0.3×	51	3.4k
Gökçen Eraslan United States	8	2.0k 1.2×	419 1.3×	180 0.9×	345 1.9×	43 0.3×	12	2.6k
Rubén Armañanzas Spain	17	755 0.5×	212 0.7×	308 1.6×	151 0.8×	101 0.6×	37	1.5k
Christof Angermueller United Kingdom	9	2.0k 1.3×	406 1.3×	245 1.3×	238 1.3×	142 0.9×	9	2.7k
Zhi Huang China	20	1.0k 0.6×	346 1.1×	421 2.2×	108 0.6×	49 0.3×	89	2.1k
Jiarui Ding Canada	19	1.7k 1.0×	730 2.3×	73 0.4×	194 1.0×	37 0.2×	50	2.5k
Debarka Sengupta India	18	1.0k 0.6×	537 1.7×	103 0.5×	123 0.7×	68 0.4×	57	1.6k
Yu‐Chiao Chiu United States	23	1.1k 0.6×	540 1.7×	169 0.9×	54 0.3×	142 0.9×	65	1.5k

Countries citing papers authored by Anjun Ma

Since Specialization

Citations

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

Fields of papers citing papers by Anjun Ma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anjun Ma

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

All Works

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20 of 20 papers shown

Wang, Shuang, Jinpu Li, Meichen Yu, et al.. (2025). TrimNN: characterizing cellular community motifs for studying multicellular topological organization in complex tissues. Nature Communications. 16(1). 7737–7737. 1 indexed citations

Li, Yang, Anjun Ma, Yizhong Wang, et al.. (2024). Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data. Briefings in Bioinformatics. 25(5). 5 indexed citations

Li, Jingxian, Anjun Ma, Gang Xin, et al.. (2024). MarsGT: Multi-omics analysis for rare population inference using single-cell graph transformer. Nature Communications. 15(1). 338–338. 19 indexed citations

Wang, Cankun, Diana Acosta, Jiang Bian, et al.. (2024). A single-cell and spatial RNA-seq database for Alzheimer’s disease (ssREAD). Nature Communications. 15(1). 4710–4710. 22 indexed citations

Chang, Yuzhou, Jixin Liu, Yi Jiang, et al.. (2024). Graph Fourier transform for spatial omics representation and analyses of complex organs. Nature Communications. 15(1). 7467–7467. 9 indexed citations

Liu, Zhaoqian, Qi Wang, Anjun Ma, et al.. (2023). Inference of disease-associated microbial gene modules based on metagenomic and metatranscriptomic data. Computers in Biology and Medicine. 165. 107458–107458. 2 indexed citations

Jiang, Yi, Ruheng Wang, Junru Jin, et al.. (2023). Explainable Deep Hypergraph Learning Modeling the Peptide Secondary Structure Prediction. Advanced Science. 10(11). e2206151–e2206151. 55 indexed citations

Zhao, Bao, Anjun Ma, Jianwen Chen, et al.. (2022). SUSD2 suppresses CD8+ T cell antitumor immunity by targeting IL-2 receptor signaling. Nature Immunology. 23(11). 1588–1599. 18 indexed citations

Yang, Lili, et al.. (2022). MMGraph: a multiple motif predictor based on graph neural network and coexisting probability for ATAC-seq data. Bioinformatics. 38(19). 4636–4638. 4 indexed citations

10.

Ma, Anjun, Gang Xin, & Qin Ma. (2022). The use of single-cell multi-omics in immuno-oncology. Nature Communications. 13(1). 2728–2728. 22 indexed citations

11.

Cheng, Hao, Anjun Ma, Yang Li, et al.. (2022). scGNN 2.0: a graph neural network tool for imputation and clustering of single-cell RNA-Seq data. Bioinformatics. 38(23). 5322–5325. 15 indexed citations

12.

Jerome, Andrew, Andrew Sas, Cankun Wang, et al.. (2022). Biological aging of CNS-resident cells alters the clinical course and immunopathology of autoimmune demyelinating disease. JCI Insight. 7(12). 16 indexed citations

13.

Chen, Junyi, Xiaoying Wang, Anjun Ma, et al.. (2022). Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data. Nature Communications. 13(1). 6494–6494. 100 indexed citations

14.

Zhang, Shuangquan, Anjun Ma, Jing Zhao, et al.. (2021). Assessing deep learning methods in cis -regulatory motif finding based on genomic sequencing data. Briefings in Bioinformatics. 23(1). 17 indexed citations

15.

Wang, Juexin, Anjun Ma, Yuzhou Chang, et al.. (2021). scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses. Nature Communications. 12(1). 1882–1882. 250 indexed citations breakdown →

16.

Yu, Bin, et al.. (2021). Prediction of protein–protein interactions based on elastic net and deep forest. Expert Systems with Applications. 176. 114876–114876. 59 indexed citations

17.

Qiu, Yinjie, et al.. (2020). WFhb1-1 plays an important role in resistance against Fusarium head blight in wheat. Scientific Reports. 10(1). 7794–7794. 12 indexed citations

18.

Ma, Anjun, et al.. (2020). Integrative Methods and Practical Challenges for Single-Cell Multi-omics. Trends in biotechnology. 38(9). 1007–1022. 163 indexed citations

19.

Li, Yang, Anjun Ma, Ewy A. Mathé, et al.. (2020). Elucidation of Biological Networks across Complex Diseases Using Single-Cell Omics. Trends in Genetics. 36(12). 951–966. 22 indexed citations

20.

Yang, Jinyu, Anjun Ma, Adam D. Hoppe, et al.. (2019). Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework. Nucleic Acids Research. 47(15). 7809–7824. 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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