Ju Xiang

2.0k citations
96 papers · 1.3k · h-index 22

Impact in

Papers in

    • Bioinformatics and Genomic Networks 36
    • Machine Learning in Bioinformatics 17
    • Gene expression and cancer classification 15
    • Gene Regulatory Network Analysis 7
    • Circular RNAs in diseases 6
    • Complex Network Analysis Techniques 22
    • Opinion Dynamics and Social Influence 14

Ju Xiang

90 papers receiving 1.3k citations

Peers

Ju Xiang
Comparison fields: 5 of 143
  • Statistical and Nonlinear Physics 214
  • Cancer Research 131
  • Computational Theory and Mathematics 167
  • Finance 86
  • Molecular Biology 528
Replace Chen Jia with:
Chen Jia China
Won‐Min Song United States
Tianxiao Wang China
Hani Doss United States
Jerome T. Mettetal United States
Amitabh Sharma United States
Jean Clairambault France
Jörg Menche Austria
Wenyuan Li China
Ju Xiang relative to Chen Jia China Chen Jia's profile →
Citations per field
00.5×5.6×
Chen Jia · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Ju Xiang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ju Xiang Line = papers co-authored together Ju Xiang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 96 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202086
2 201956
3 202353
4 201152
5 201650
6 201547
7 200647
8 202041
9 202138
10 202029
11 201728
12 201627
13 202027
14 201527
15 202126
16 201326
17 201225
18 202025
19 202223
20 202123

About Ju Xiang

Ju Xiang is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Computational Theory and Mathematics, Finance and Artificial Intelligence, having authored 96 papers that have together received 1.3k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (36 papers), Complex Network Analysis Techniques (22 papers), Machine Learning in Bioinformatics (17 papers), Gene expression and cancer classification (15 papers), Opinion Dynamics and Social Influence (14 papers), Computational Drug Discovery Methods (13 papers), Gene Regulatory Network Analysis (7 papers) and Circular RNAs in diseases (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (214 citations), Cancer Research (131 citations), Computational Theory and Mathematics (167 citations), Finance (86 citations) and Molecular Biology (528 citations). Ju Xiang has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Jianming Li, Liang Tang, Min Li, Ke Hu, Meihua Bao, Xiang Qin, Yiuman Tse, Jialiang Yang, Geng Tian and Fang‐Xiang Wu. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Frontiers in Genetics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Briefings in Bioinformatics and IEEE Access.

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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