Bin Duan

1.0k total citations · 1 hit paper
19 papers, 631 citations indexed

About

Bin Duan is a scholar working on Molecular Biology, Artificial Intelligence and Cancer Research. According to data from OpenAlex, Bin Duan has authored 19 papers receiving a total of 631 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 5 papers in Artificial Intelligence and 5 papers in Cancer Research. Recurrent topics in Bin Duan's work include Single-cell and spatial transcriptomics (10 papers), Cancer Genomics and Diagnostics (5 papers) and Gene expression and cancer classification (3 papers). Bin Duan is often cited by papers focused on Single-cell and spatial transcriptomics (10 papers), Cancer Genomics and Diagnostics (5 papers) and Gene expression and cancer classification (3 papers). Bin Duan collaborates with scholars based in China, United States and Denmark. Bin Duan's co-authors include Qi Liu, Chenyu Zhu, Guohui Chuai, Hanhui Ma, Chi Zhou, Nanfang Hong, Jia Wei, De-Shuang Huang, Dongyu Xue and Ming Chen and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Science Advances.

In The Last Decade

Bin Duan

18 papers receiving 627 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.

DeepCRISPR: optimized CRISPR guide RNA design by deep learning

2018 356 citations Guohui Chuai, Hanhui Ma et al. Genome biology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bin Duan China	11	534	52	51	42	40	19	631
Reza Mirzazadeh Sweden	11	658 1.2×	95 1.8×	100 2.0×	42 1.0×	16 0.4×	15	755
Chenyu Zhu China	14	644 1.2×	54 1.0×	61 1.2×	30 0.7×	45 1.1×	36	865
Jiecong Lin Hong Kong	10	405 0.8×	32 0.6×	42 0.8×	9 0.2×	39 1.0×	21	478
Esha T. Shah Australia	13	216 0.4×	47 0.9×	39 0.8×	17 0.4×	11 0.3×	32	457
Xianhua Dai China	16	381 0.7×	60 1.2×	58 1.1×	3 0.1×	17 0.4×	87	700
Jia Wei China	6	679 1.3×	176 3.4×	56 1.1×	8 0.2×	46 1.1×	12	725
Norbert Dojer Poland	11	824 1.5×	71 1.4×	104 2.0×	7 0.2×	63 1.6×	17	927
Alexander Schmidt Germany	5	409 0.8×	27 0.5×	33 0.6×	11 0.3×	12 0.3×	21	502
Shengquan Chen China	12	489 0.9×	89 1.7×	22 0.4×	74 1.8×	46 1.1×	49	578
Juexiao Zhou Saudi Arabia	13	288 0.5×	57 1.1×	33 0.6×	29 0.7×	131 3.3×	25	588

Countries citing papers authored by Bin Duan

Since Specialization

Citations

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

Fields of papers citing papers by Bin Duan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bin Duan

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

19 of 19 papers shown

1.

Wang, Pengxiang, Bin Duan, Jianwen Cheng, et al.. (2025). Exploring morphological heterogeneity of circulating tumor cells: machine learning-based approach for cell identification and prognostic implications. Science Bulletin. 70(13). 2070–2074.

2.

Cheng, Xiaojie, Chen Tang, Xueying Zhao, et al.. (2025). SpaLinker identifies phenotype-associated spatial tumor microenvironment features by integrating bulk and spatial sequencing data. Cell Genomics. 5(7). 100893–100893. 2 indexed citations

3.

Wei, Zhiting, et al.. (2024). PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization. Nucleic Acids Research. 53(D1). D1099–D1111. 7 indexed citations

4.

Duan, Bin, Shaoqi Chen, Xiaojie Cheng, & Qi Liu. (2024). Multi-slice spatial transcriptome domain analysis with SpaDo. Genome biology. 25(1). 73–73. 11 indexed citations

5.

Sun, Fengying, Haoyan Li, Dongqing Sun, et al.. (2024). Single-cell omics: experimental workflow, data analyses and applications. Science China Life Sciences. 68(1). 5–102. 31 indexed citations

6.

Tang, Chen, Shaliu Fu, Bin Duan, et al.. (2023). Personalized tumor combination therapy optimization using the single-cell transcriptome. Genome Medicine. 15(1). 105–105. 12 indexed citations

7.

Chen, Shaoqi, Bin Duan, Chenyu Zhu, et al.. (2022). Privacy-preserving integration of multiple institutional data for single-cell type identification with scPrivacy. Science China Life Sciences. 66(5). 1183–1195. 9 indexed citations

8.

Li, Gaoyang, Shaliu Fu, Shuguang Wang, et al.. (2022). A deep generative model for multi-view profiling of single-cell RNA-seq and ATAC-seq data. Genome biology. 23(1). 20–20. 55 indexed citations

9.

Wei, Zhiting, et al.. (2022). DrSim: Similarity Learning for Transcriptional Phenotypic Drug Discovery. Genomics Proteomics & Bioinformatics. 20(5). 1028–1036. 5 indexed citations

10.

Duan, Bin, Shaoqi Chen, Xiaohan Chen, et al.. (2021). Integrating multiple references for single-cell assignment. Nucleic Acids Research. 49(14). e80–e80. 14 indexed citations

11.

Duan, Bin, Chenyu Zhu, Guohui Chuai, et al.. (2020). Learning for single-cell assignment. Science Advances. 6(44). 20 indexed citations

12.

Li, Zihan, et al.. (2020). Data Mining and Feature Analysis of College Students’ Campus Network Behavior. 231–237. 11 indexed citations

13.

Duan, Bin, Chi Zhou, Chengyu Zhu, et al.. (2019). Model-based understanding of single-cell CRISPR screening. Nature Communications. 10(1). 2233–2233. 67 indexed citations

14.

Chuai, Guohui, Hanhui Ma, Jifang Yan, et al.. (2018). DeepCRISPR: optimized CRISPR guide RNA design by deep learning. Genome biology. 19(1). 80–80. 356 indexed citations breakdown →

15.

Song, Mengxuan, Wen Yi, Bin Duan, Jun Wang, & Qi Gong. (2017). Micro-siting optimization of a wind farm built in multiple phases. Energy. 137. 95–103. 15 indexed citations

16.

Duan, Bin, et al.. (2017). Fault detection and location of microgrid based on distributed decision. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. 5054–5059. 2 indexed citations

17.

Gang, Zhou, et al.. (2015). Simulation and analysis on handling stability of tractor-semitrailer. 7. 94–101. 1 indexed citations

18.

Duan, Bin, Jun Wang, & Huajie Gu. (2014). Modified genetic algorithm for layout optimization of multi-type wind turbines. 3633–3638. 12 indexed citations

19.

Duan, Bin. (2010). Control strategy improved fault ride-through for doubly-fed wind-power generation system. Dianji yu kongzhi xuebao. 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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