Ju Xiang

1.9k total citations
91 papers, 1.2k citations indexed

About

Ju Xiang is a scholar working on Molecular Biology, Statistical and Nonlinear Physics and Computational Theory and Mathematics. According to data from OpenAlex, Ju Xiang has authored 91 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 23 papers in Statistical and Nonlinear Physics and 11 papers in Computational Theory and Mathematics. Recurrent topics in Ju Xiang's work include Bioinformatics and Genomic Networks (34 papers), Complex Network Analysis Techniques (22 papers) and Machine Learning in Bioinformatics (16 papers). Ju Xiang is often cited by papers focused on Bioinformatics and Genomic Networks (34 papers), Complex Network Analysis Techniques (22 papers) and Machine Learning in Bioinformatics (16 papers). Ju Xiang collaborates with scholars based in China, Canada and United States. Ju Xiang's co-authors include Liang Tang, Jianming Li, Min Li, Ke Hu, Meihua Bao, Yiuman Tse, Xiang Qin, Fang‐Xiang Wu, Jialiang Yang and Geng Tian and has published in prestigious journals such as Bioinformatics, PLoS ONE and The Astrophysical Journal.

In The Last Decade

Ju Xiang

86 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ju Xiang China	21	543	198	152	151	84	91	1.2k
Chen Jia China	26	1.1k 2.1×	172 0.9×	118 0.8×	30 0.2×	68 0.8×	126	2.0k
Won‐Min Song United States	17	540 1.0×	58 0.3×	129 0.8×	56 0.4×	12 0.1×	34	1.1k
Jerome T. Mettetal United States	18	1.6k 2.9×	62 0.3×	76 0.5×	213 1.4×	4 0.0×	48	2.5k
Tianxiao Wang China	27	956 1.8×	17 0.1×	365 2.4×	29 0.2×	326 3.9×	162	2.4k
Beatrix Jones New Zealand	11	511 0.9×	8 0.0×	95 0.6×	38 0.3×	23 0.3×	16	997
Amitabh Sharma United States	22	1.9k 3.5×	165 0.8×	185 1.2×	546 3.6×	3 0.0×	38	3.0k
Jörg Menche Austria	24	2.3k 4.1×	170 0.9×	146 1.0×	759 5.0×	3 0.0×	53	3.2k
Jean Clairambault France	24	585 1.1×	27 0.1×	204 1.3×	54 0.4×	6 0.1×	71	1.9k
Angela Serra Finland	21	550 1.0×	7 0.0×	62 0.4×	354 2.3×	11 0.1×	55	1.1k

Countries citing papers authored by Ju Xiang

Since Specialization

Citations

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

Fields of papers citing papers by Ju Xiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ju Xiang

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

20 of 20 papers shown

Xiang, Ju, et al.. (2025). DyNDG: Identifying Leukemia-related Genes Based on Time-series Dynamic Network by Integrating Differential Genes. Genomics Proteomics & Bioinformatics. 23(2).

Dai, Yu, Ju Xiang, & M. D. Ding. (2024). Generalized Coronal Loop Scaling Laws and Their Implication for Turbulence in Solar Active Region Loops. The Astrophysical Journal. 965(1). 2–2. 2 indexed citations

Xiang, Ju, et al.. (2024). Dopcc: Detecting Overlapping Protein Complexes via Multi-Metrics and Co-Core Attachment Method. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(6). 2000–2010. 2 indexed citations

Xiang, Ju, et al.. (2024). MDDOmics: multi-omics resource of major depressive disorder. Database. 2024. 1 indexed citations

Zhang, Yan, Ju Xiang, Liang Tang, Jialiang Yang, & Jianming Li. (2023). PGAGP: Predicting pathogenic genes based on adaptive network embedding algorithm. Frontiers in Genetics. 13. 1087784–1087784. 2 indexed citations

Xiang, Ju, et al.. (2023). Analysis of Potential Mechanism of Herbal Formula Taohong Siwu Decoction against Vascular Dementia Based on Network Pharmacology and Molecular Docking. BioMed Research International. 2023(1). 1235552–1235552. 7 indexed citations

Xiang, Ju, et al.. (2023). CACO: A Core-Attachment Method With Cross-Species Functional Ortholog Information to Detect Human Protein Complexes. IEEE Journal of Biomedical and Health Informatics. 27(9). 4569–4578. 6 indexed citations

Ma, Jinlong, et al.. (2023). Disease-gene prediction based on preserving structure network embedding. Frontiers in Aging Neuroscience. 15. 1061892–1061892. 2 indexed citations

Xiang, Ju, et al.. (2022). HyMM: hybrid method for disease-gene prediction by integrating multiscale module structure. Briefings in Bioinformatics. 23(3). 10 indexed citations

10.

Li, Wen-Kai, et al.. (2022). Temporal-Spatial Analysis of the Essentiality of Hub Proteins in Protein-Protein Interaction Networks. IEEE Transactions on Network Science and Engineering. 9(5). 3504–3514. 11 indexed citations

11.

Xiang, Ju, et al.. (2021). DPCMNE: Detecting Protein Complexes From Protein-Protein Interaction Networks Via Multi-Level Network Embedding. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(3). 1592–1602. 32 indexed citations

12.

Qin, Xiang, Hongbo Xu, Zhijian Yang, et al.. (2021). Novel MFSD8 Variants in a Chinese Family with Nonsyndromic Macular Dystrophy. Journal of Ophthalmology. 2021. 1–5. 12 indexed citations

13.

Hu, Ke, Ju Xiang, Liang Tang, et al.. (2020). Significance-based multi-scale method for network community detection and its application in disease-gene prediction. PLoS ONE. 15(3). e0227244–e0227244. 5 indexed citations

14.

Tang, Liang, Yongjun Chen, Xiang Qin, et al.. (2020). The GCAG Haplotype of the CRHBP Gene May Decrease the Risk for Robbery Behavior Among the Han Chinese. Genetic Testing and Molecular Biomarkers. 24(7). 436–442. 4 indexed citations

15.

Liu, Chuanying, Wei Dong, Ju Xiang, et al.. (2020). An Improved Anticancer Drug-Response Prediction Based on an Ensemble Method Integrating Matrix Completion and Ridge Regression. Molecular Therapy — Nucleic Acids. 21. 676–686. 76 indexed citations

16.

Luo, Huimin, et al.. (2020). NEDD: a network embedding based method for predicting drug-disease associations. BMC Bioinformatics. 21(S13). 387–387. 32 indexed citations

17.

Li, Manzhi, Hongtao Wang, Haixia Long, et al.. (2019). Community Detection and Visualization in Complex Network by the Density-Canopy-Kmeans Algorithm and MDS Embedding. IEEE Access. 7. 120616–120625. 7 indexed citations

18.

Xiang, Ju, Hui‐Jia Li, Zhan Bu, et al.. (2018). Critical analysis of (Quasi-)Surprise for community detection in complex networks. Scientific Reports. 8(1). 14459–14459. 8 indexed citations

19.

Li, Jianming, Liang Tang, Yan Wang, et al.. (2017). Genetic Associations and Interactions Between the NR3C1 ( GR ) and NR3C2 ( MR ) Genes and Aggressive Behavior in a Central South Chinese Han Population. Genetic Testing and Molecular Biomarkers. 21(8). 497–505. 5 indexed citations

20.

Li, Hui‐Jia & Ju Xiang. (2017). Explore of the fuzzy community structure integrating the directed line graph and likelihood optimization. Journal of Intelligent & Fuzzy Systems. 32(6). 4503–4511. 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.

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