Ren Qi

1.1k total citations · 1 hit paper
14 papers, 638 citations indexed

About

Ren Qi is a scholar working on Molecular Biology, Cancer Research and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ren Qi has authored 14 papers receiving a total of 638 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ren Qi's work include Single-cell and spatial transcriptomics (8 papers), Gene expression and cancer classification (5 papers) and Cancer-related molecular mechanisms research (4 papers). Ren Qi is often cited by papers focused on Single-cell and spatial transcriptomics (8 papers), Gene expression and cancer classification (5 papers) and Cancer-related molecular mechanisms research (4 papers). Ren Qi collaborates with scholars based in China, United States and Saudi Arabia. Ren Qi's co-authors include Quan Zou, Qin Ma, Anjun Ma, Cankun Wang, Hongjun Fu, Juexin Wang, Yuexu Jiang, Jianting Gong, Yuzhou Chang and Dong Xu and has published in prestigious journals such as Nature Communications, Genome Research and Briefings in Bioinformatics.

In The Last Decade

Ren Qi

13 papers receiving 634 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

2021 250 citations Juexin Wang, Anjun Ma et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ren Qi China	8	527	132	101	76	47	14	638
Yungang Xu China	14	477 0.9×	128 1.0×	37 0.4×	48 0.6×	15 0.3×	29	638
Christina V. Theodoris United States	9	654 1.2×	69 0.5×	84 0.8×	54 0.7×	10 0.2×	14	912
Haoyang Li China	15	323 0.6×	73 0.6×	31 0.3×	134 1.8×	25 0.5×	38	720
Daniel Sumner Magruder Germany	5	251 0.5×	97 0.7×	52 0.5×	38 0.5×	19 0.4×	7	359
Alberto Valdeolivas Germany	7	476 0.9×	64 0.5×	54 0.5×	39 0.5×	22 0.5×	13	679
Jiaqiang Zhu China	9	612 1.2×	101 0.8×	95 0.9×	26 0.3×	10 0.2×	16	729
Peter Berube United States	2	383 0.7×	45 0.3×	80 0.8×	17 0.2×	108 2.3×	2	542
Paolo Inglese United Kingdom	11	287 0.5×	63 0.5×	31 0.3×	25 0.3×	26 0.6×	21	482
Laura Cantini France	12	447 0.8×	127 1.0×	30 0.3×	44 0.6×	9 0.2×	27	589

Countries citing papers authored by Ren Qi

Since Specialization

Citations

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

Fields of papers citing papers by Ren Qi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ren Qi

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

14 of 14 papers shown

1.

Qi, Ren, et al.. (2025). A novel multislice framework for precision 3D spatial domain reconstruction and disease pathology analysis. Genome Research. 35(8). 1794–1808. 1 indexed citations

2.

Qi, Ren, et al.. (2025). AI in drug development: advances in response, combination therapy, repositioning, and molecular design. Science China Information Sciences. 68(7).

3.

Zou, Quan, et al.. (2024). PseU-KeMRF: A novel method for identifying RNA pseudouridine sites. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(5). 1–14. 1 indexed citations

4.

Qi, Ren, et al.. (2024). A new method for handling heterogeneous data in bioinformatics. Computers in Biology and Medicine. 170. 107937–107937. 1 indexed citations

5.

Qi, Ren & Quan Zou. (2023). Trends and Potential of Machine Learning and Deep Learning in Drug Study at Single-Cell Level. Research. 6. 50–50. 50 indexed citations

6.

Qi, Ren, Fei Guo, & Quan Zou. (2022). String kernels construction and fusion: a survey with bioinformatics application. Frontiers of Computer Science. 16(6). 18 indexed citations

7.

Gao, Hongli, et al.. (2022). scBKAP: A Clustering Model for Single-Cell RNA-Seq Data Based on Bisecting K-Means. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(3). 2007–2015. 6 indexed citations

8.

Wang, Juexin, Anjun Ma, Yuzhou Chang, et al.. (2021). scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses. Nature Communications. 12(1). 1882–1882. 250 indexed citations breakdown →

9.

Jiang, Jing, Cankun Wang, Ren Qi, Hongjun Fu, & Qin Ma. (2020). scREAD: A Single-Cell RNA-Seq Database for Alzheimer's Disease. iScience. 23(11). 101769–101769. 71 indexed citations

10.

Yu, Bin, et al.. (2020). scGMAI: a Gaussian mixture model for clustering single-cell RNA-Seq data based on deep autoencoder. Briefings in Bioinformatics. 22(4). 50 indexed citations

11.

Qi, Ren, Jin Wu, Fei Guo, Lei Xu, & Quan Zou. (2020). A spectral clustering with self-weighted multiple kernel learning method for single-cell RNA-seq data. Briefings in Bioinformatics. 22(4). 38 indexed citations

12.

Qi, Ren, Anjun Ma, Qin Ma, & Quan Zou. (2019). Clustering and classification methods for single-cell RNA-sequencing data. Briefings in Bioinformatics. 21(4). 1196–1208. 141 indexed citations

13.

Zhu, Pengfei, Ren Qi, Qinghua Hu, et al.. (2018). Beyond Similar and Dissimilar Relations : A Kernel Regression Formulation for Metric Learning. 3242–3248. 10 indexed citations

14.

Qi, Ren, Pengfei Zhu, & Jianqing Liang. (2017). Multiple Kernel Geometric Mean Metric Learning for Heterogeneous Data. 28(11). 2992–3001. 1 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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