Xingxin Pan

453 total citations
13 papers, 276 citations indexed

About

Xingxin Pan is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Xingxin Pan has authored 13 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Immunology and 4 papers in Cancer Research. Recurrent topics in Xingxin Pan's work include Glioma Diagnosis and Treatment (3 papers), Bioinformatics and Genomic Networks (3 papers) and Epigenetics and DNA Methylation (2 papers). Xingxin Pan is often cited by papers focused on Glioma Diagnosis and Treatment (3 papers), Bioinformatics and Genomic Networks (3 papers) and Epigenetics and DNA Methylation (2 papers). Xingxin Pan collaborates with scholars based in United States, China and Hong Kong. Xingxin Pan's co-authors include S. Stephen Yi, Yulu Liu, Shuai Cheng Li, Shuang Yang, Nidhi Sahni, Yi Lu, Weijie Guo, Whitney Lewis, Zhenglin Yang and Quanbing Mou and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nature Biotechnology and Cancer Research.

In The Last Decade

Xingxin Pan

12 papers receiving 275 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xingxin Pan United States 7 207 53 31 23 20 13 276
Antonio Mora China 10 296 1.4× 50 0.9× 29 0.9× 22 1.0× 9 0.5× 21 405
Stephanie Dorman United States 6 173 0.8× 74 1.4× 23 0.7× 16 0.7× 9 0.5× 13 282
Chaochao Wu China 11 256 1.2× 34 0.6× 17 0.5× 8 0.3× 5 0.3× 22 371
Emily R. Gordon United States 10 141 0.7× 59 1.1× 22 0.7× 5 0.2× 39 1.9× 42 289
Enio Gjerga Germany 7 215 1.0× 30 0.6× 11 0.4× 41 1.8× 5 0.3× 17 274
Zhi Cao China 11 260 1.3× 59 1.1× 31 1.0× 7 0.3× 34 1.7× 32 384
Yubo Fan United States 6 206 1.0× 57 1.1× 24 0.8× 29 1.3× 10 0.5× 9 309
Tzu-Hsien Yang Taiwan 12 324 1.6× 56 1.1× 22 0.7× 16 0.7× 8 0.4× 32 445
Andreas Digre Sweden 7 153 0.7× 41 0.8× 45 1.5× 13 0.6× 6 0.3× 8 260
Stefanie Friedrich Sweden 5 380 1.8× 138 2.6× 69 2.2× 19 0.8× 14 0.7× 6 472

Countries citing papers authored by Xingxin Pan

Since Specialization
Citations

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

Fields of papers citing papers by Xingxin Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingxin Pan

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

All Works

13 of 13 papers shown
1.
2.
Collins, Meghan, Ruggiero Gorgoglione, Xingxin Pan, et al.. (2024). Exploration of the intracellular chiral metabolome in pediatric BCP-ALL: a pilot study investigating the metabolic phenotype of IgH locus aberrations. Frontiers in Oncology. 14. 1413264–1413264. 1 indexed citations
3.
Kong, Qing, Shiyu Xia, Xingxin Pan, et al.. (2023). Alternative splicing of GSDMB modulates killer lymphocyte–triggered pyroptosis. Science Immunology. 8(82). eadg3196–eadg3196. 57 indexed citations
4.
Sun, Qi, et al.. (2023). The Development of Immunotherapy for the Treatment of Recurrent Glioblastoma. Cancers. 15(17). 4308–4308. 4 indexed citations
5.
Guo, Weijie, Quanbing Mou, Xiangli Shao, et al.. (2023). Spatial imaging of glycoRNA in single cells with ARPLA. Nature Biotechnology. 42(4). 608–616. 87 indexed citations
6.
Pan, Xingxin, Jun Yun, Zeynep H. Coban Akdemir, et al.. (2023). AI-DrugNet: A network-based deep learning model for drug repurposing and combination therapy in neurological disorders. Computational and Structural Biotechnology Journal. 21. 1533–1542. 18 indexed citations
7.
Pan, Xingxin, Zeynep H. Coban Akdemir, Ruixuan Gao, et al.. (2023). AD-Syn-Net: systematic identification of Alzheimer’s disease-associated mutation and co-mutation vulnerabilities via deep learning. Briefings in Bioinformatics. 24(2). 1 indexed citations
8.
Lodi, Alessia, Renu Pandey, Ayon Bhattacharya, et al.. (2022). Circulating metabolites associated with tumor hypoxia and early response to treatment in bevacizumab-refractory glioblastoma after combined bevacizumab and evofosfamide. Frontiers in Oncology. 12. 900082–900082. 7 indexed citations
9.
Pan, Xingxin, et al.. (2022). i-Modern: Integrated multi-omics network model identifies potential therapeutic targets in glioma by deep learning with interpretability. Computational and Structural Biotechnology Journal. 20. 3511–3521. 21 indexed citations
10.
11.
Zhang, Chuang, Suolin Li, Chi Sun, et al.. (2021). Vitexin ameliorates glycochenodeoxycholate-induced hepatocyte injury through SIRT6 and JAK2/STAT3 pathways.. SHILAP Revista de lepidopterología. 24(12). 1717–1725. 5 indexed citations
12.
Pan, Xingxin, Xingzhao Wen, Yulu Liu, et al.. (2019). D-GPM: A Deep Learning Method for Gene Promoter Methylation Inference. Genes. 10(10). 807–807. 10 indexed citations
13.
Liu, Yulu, et al.. (2019). DNA Methylation Markers for Pan-Cancer Prediction by Deep Learning. Genes. 10(10). 778–778. 59 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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