Xingya Chang

457 total citations
8 papers, 345 citations indexed

About

Xingya Chang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xingya Chang has authored 8 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Cellular and Molecular Neuroscience and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xingya Chang's work include RNA modifications and cancer (2 papers), Visual Attention and Saliency Detection (2 papers) and RNA Research and Splicing (2 papers). Xingya Chang is often cited by papers focused on RNA modifications and cancer (2 papers), Visual Attention and Saliency Detection (2 papers) and RNA Research and Splicing (2 papers). Xingya Chang collaborates with scholars based in China and United States. Xingya Chang's co-authors include Liang Wang, Mu‐ming Poo, Liang She, Weitong Huang, Duo Xu, Hong Cheng, Min Shi, Guifen Wu, Lantian Wang and Qingliang Wang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Neuroscience.

In The Last Decade

Xingya Chang

8 papers receiving 344 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xingya Chang China	6	200	91	83	33	29	8	345
Raphael M. Bendriem United States	8	201 1.0×	74 0.8×	53 0.6×	14 0.4×	26 0.9×	10	309
Ariana Gatt United Kingdom	11	255 1.3×	113 1.2×	33 0.4×	26 0.8×	91 3.1×	15	423
Annamária Téglási Hungary	5	207 1.0×	100 1.1×	65 0.8×	22 0.7×	125 4.3×	6	335
Natsumi Ageta‐Ishihara Japan	9	310 1.6×	214 2.4×	42 0.5×	118 3.6×	63 2.2×	20	496
Ana Luisa Piña Germany	11	243 1.2×	77 0.8×	28 0.3×	26 0.8×	28 1.0×	20	412
Hiroko Nomaru Japan	9	219 1.1×	70 0.8×	28 0.3×	13 0.4×	43 1.5×	12	349
Durga Praveen Meka Germany	10	178 0.9×	171 1.9×	59 0.7×	70 2.1×	42 1.4×	13	374
Shabana Khan United Kingdom	5	157 0.8×	86 0.9×	40 0.5×	33 1.0×	39 1.3×	7	305
Ruomu Gong China	6	219 1.1×	161 1.8×	24 0.3×	32 1.0×	41 1.4×	9	345
Patrik Hollós Finland	8	169 0.8×	86 0.9×	45 0.5×	87 2.6×	27 0.9×	9	339

Countries citing papers authored by Xingya Chang

Since Specialization

Citations

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

Fields of papers citing papers by Xingya Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingya Chang

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

All Works

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8 of 8 papers shown

Jia, Tong, et al.. (2024). RGB-T Saliency Detection Based on Multiscale Modal Reasoning Interaction. IEEE Transactions on Instrumentation and Measurement. 73. 1–15. 2 indexed citations

Chang, Xingya, et al.. (2022). Two-stage salient object detection based on prior distribution learning and saliency consistency optimization. The Visual Computer. 39(11). 5729–5745. 4 indexed citations

Chen, Suli, Ruijia Wang, Dinghai Zheng, et al.. (2019). The mRNA Export Receptor NXF1 Coordinates Transcriptional Dynamics, Alternative Polyadenylation, and mRNA Export. Molecular Cell. 74(1). 118–131.e7. 39 indexed citations

Wang, Liang, Xingya Chang, Liang She, et al.. (2015). Autocrine Action of BDNF on Dendrite Development of Adult-Born Hippocampal Neurons. Journal of Neuroscience. 35(22). 8384–8393. 116 indexed citations

Huang, Weitong, Liang She, Xingya Chang, et al.. (2013). Protein kinase LKB1 regulates polarized dendrite formation of adult hippocampal newborn neurons. Proceedings of the National Academy of Sciences. 111(1). 469–474. 29 indexed citations

Chi, Binkai, Qingliang Wang, Guifen Wu, et al.. (2012). Aly and THO are required for assembly of the human TREX complex and association of TREX components with the spliced mRNA. Nucleic Acids Research. 41(2). 1294–1306. 98 indexed citations

Xiao, Jing, Qi Rui, Yuling Guo, Xingya Chang, & Dayong Wang. (2009). Prolonged manganese exposure induces severe deficits in lifespan, development and reproduction possibly by altering oxidative stress response in Caenorhabditis elegans. Journal of Environmental Sciences. 21(6). 842–848. 33 indexed citations

Dou, Fei, Xingya Chang, & Da Ma. (2007). Hsp90 Maintains the Stability and Function of the Tau Phosphorylating Kinase GSK3β. International Journal of Molecular Sciences. 8(1). 51–60. 24 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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