Xianyang Zhang
- Molecular Biology
- Statistics and Probability top 1%
- Endocrinology, Diabetes and Metabolism top 10%
- Finance top 5%
- Artificial Intelligence top 10%
- Topics
- Statistical Methods and Inference (21 papers)Gene expression and cancer classification (11 papers)Growth Hormone and Insulin-like Growth Factors (9 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Statistical AssociationBioinformatics
- Partner nations
- United StatesChinaItaly
In The Last Decade
Xianyang Zhang
65 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Molecular Biology 362
- Statistics and Probability 325
- Endocrinology, Diabetes and Metabolism 161
- Finance 134
- Artificial Intelligence 114
Countries citing papers authored by Xianyang Zhang
This map shows the geographic impact of Xianyang Zhang'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 Xianyang Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xianyang Zhang more than expected).
Fields of papers citing papers by Xianyang Zhang
This network shows the impact of papers produced by Xianyang Zhang. 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 Xianyang Zhang. The network helps show where Xianyang Zhang may publish in the future.
Co-authorship network of co-authors of Xianyang Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Xianyang Zhang. A scholar is included among the top collaborators of Xianyang Zhang 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 Xianyang Zhang. Xianyang Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 13 | |
| 8 | 1 | |
| 9 | 16 | |
| 10 | 4 | |
| 11 | 2 | |
| 12 | LinDA: linear models for differential abundance analysis of microbiome compositional databreakdown → | 181 |
| 13 | 4 | |
| 14 | 21 | |
| 15 | 6 | |
| 16 | 5 | |
| 17 | 27 | |
| 18 | 1 | |
| 19 | 17 | |
| 20 | Experimental Study on the Effect of High Temperature on the Strength of High-strength Cement Mortar | 1 |
About Xianyang Zhang
Xianyang Zhang is a scholar working on Statistics and Probability, Finance and Endocrinology, Diabetes and Metabolism, having authored 70 papers that have together received 1.2k indexed citations. Recurring topics across this work include Statistical Methods and Inference (21 papers), Gene expression and cancer classification (11 papers) and Growth Hormone and Insulin-like Growth Factors (9 papers). The work is most often cited by research in Statistics and Probability (325 citations), Finance (134 citations) and Endocrinology, Diabetes and Metabolism (161 citations). Xianyang Zhang has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Xiaofeng Shao, Jun Chen, Guang Cheng, Kejun He, Huijuan Zhou, Andrew V. Schally, Renzhi Cai, Wei Sha, Irving Vidaurre and Joshua M. Hare. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and Bioinformatics.
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.