Xiaomu Cheng

807 total citations
8 papers, 269 citations indexed

About

Xiaomu Cheng is a scholar working on Molecular Biology, Surgery and Cognitive Neuroscience. According to data from OpenAlex, Xiaomu Cheng has authored 8 papers receiving a total of 269 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Surgery and 2 papers in Cognitive Neuroscience. Recurrent topics in Xiaomu Cheng's work include Single-cell and spatial transcriptomics (3 papers), Neural dynamics and brain function (2 papers) and Bladder and Urothelial Cancer Treatments (2 papers). Xiaomu Cheng is often cited by papers focused on Single-cell and spatial transcriptomics (3 papers), Neural dynamics and brain function (2 papers) and Bladder and Urothelial Cancer Treatments (2 papers). Xiaomu Cheng collaborates with scholars based in China and United States. Xiaomu Cheng's co-authors include Juju Miao, Man Zhang, Wei‐Qiang Gao, Huadong Lai, Jia Wang, Wenqin Luo, Zhongzhong Ji, Weichen Song, Bing Du and Yiping Duan and has published in prestigious journals such as Biochemical and Biophysical Research Communications, International Journal of Cancer and Cell Death and Disease.

In The Last Decade

Xiaomu Cheng

8 papers receiving 267 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaomu Cheng China	6	137	101	75	65	64	8	269
Junjie Zeng China	11	165 1.2×	72 0.7×	105 1.4×	54 0.8×	62 1.0×	36	374
Tessa P. Sandberg Netherlands	6	89 0.6×	50 0.5×	65 0.9×	44 0.7×	190 3.0×	6	310
Azusa Yamato Japan	8	207 1.5×	55 0.5×	64 0.9×	20 0.3×	73 1.1×	12	313
Brian Ko United States	7	64 0.5×	68 0.7×	38 0.5×	15 0.2×	70 1.1×	14	224
Ami Wang Canada	9	104 0.8×	60 0.6×	35 0.5×	22 0.3×	50 0.8×	17	264
Xiaoyu He China	10	148 1.1×	45 0.4×	48 0.6×	30 0.5×	40 0.6×	28	270
Yumei Zhang China	8	98 0.7×	63 0.6×	68 0.9×	26 0.4×	80 1.3×	27	283
Martina Salzmann Austria	8	99 0.7×	80 0.8×	50 0.7×	13 0.2×	79 1.2×	10	272
Wenyu Di China	13	180 1.3×	84 0.8×	122 1.6×	45 0.7×	93 1.5×	25	360
Georgia Vasileiou Germany	10	253 1.8×	41 0.4×	71 0.9×	26 0.4×	58 0.9×	16	420

Countries citing papers authored by Xiaomu Cheng

Since Specialization

Citations

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

Fields of papers citing papers by Xiaomu Cheng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaomu Cheng

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

8 of 8 papers shown

1.

Du, Bing, Xiaomu Cheng, Yiping Duan, & Huansheng Ning. (2022). fMRI Brain Decoding and Its Applications in Brain–Computer Interface: A Survey. Brain Sciences. 12(2). 228–228. 30 indexed citations

2.

Luo, Wenqin, Guan Ning Lin, Weichen Song, et al.. (2021). Single-cell spatial transcriptomic analysis reveals common and divergent features of developing postnatal granule cerebellar cells and medulloblastoma. BMC Biology. 19(1). 135–135. 26 indexed citations

3.

Cheng, Xiaomu, Huadong Lai, Wenqin Luo, et al.. (2021). Single-cell analysis reveals urothelial cell heterogeneity and regenerative cues following cyclophosphamide-induced bladder injury. Cell Death and Disease. 12(5). 446–446. 20 indexed citations

4.

Cheng, Xiaomu, Huansheng Ning, & Bing Du. (2021). A Survey: Challenges and Future Research Directions of fMRI Based Brain Activity Decoding Model. 23. 957–960. 1 indexed citations

5.

Lai, Huadong, Xiaomu Cheng, Qiang Liu, et al.. (2021). Single‐cell RNA sequencing reveals the epithelial cell heterogeneity and invasive subpopulation in human bladder cancer. International Journal of Cancer. 149(12). 2099–2115. 78 indexed citations

6.

Hui, Lanlan, Deng Wang, Zhao Liu, et al.. (2021). The Cell‐Isolation Capsules with Rod‐Like Channels Ensure the Survival and Response of Cancer Cells to Their Microenvironment. Advanced Healthcare Materials. 11(2). e2101723–e2101723. 3 indexed citations

7.

Dong, Baijun, Juju Miao, Yanqing Wang, et al.. (2020). Single-cell analysis supports a luminal-neuroendocrine transdifferentiation in human prostate cancer. Communications Biology. 3(1). 778–778. 102 indexed citations

8.

Chen, Yunfei, et al.. (2014). An ultrasensitive system for measuring the USPs and OTULIN activity using Nanoluc as a reporter. Biochemical and Biophysical Research Communications. 455(3-4). 178–183. 9 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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