Qingqin Gao

1.1k total citations · 1 hit paper
7 papers, 609 citations indexed

About

Qingqin Gao is a scholar working on Molecular Biology, Genetics and Ophthalmology. According to data from OpenAlex, Qingqin Gao has authored 7 papers receiving a total of 609 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Genetics and 1 paper in Ophthalmology. Recurrent topics in Qingqin Gao's work include CRISPR and Genetic Engineering (5 papers), RNA regulation and disease (2 papers) and Virus-based gene therapy research (1 paper). Qingqin Gao is often cited by papers focused on CRISPR and Genetic Engineering (5 papers), RNA regulation and disease (2 papers) and Virus-based gene therapy research (1 paper). Qingqin Gao collaborates with scholars based in China, India and Poland. Qingqin Gao's co-authors include Qi Zhou, Tongtong Cui, Fei Teng, Lu Guo, Kai Xu, Wei Li, Guihai Feng, Jing Li, Wei Li and Tianda Li and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Genome biology and Advanced Science.

In The Last Decade

Qingqin Gao

7 papers receiving 597 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.

CDetection: CRISPR-Cas12b-based DNA detection with sub-attomolar sensitivity and single-base specificity

2019 275 citations Fei Teng, Lu Guo 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
Qingqin Gao China	6	567	109	91	70	67	7	609
Sae Okazaki Japan	8	470 0.8×	75 0.7×	47 0.5×	61 0.9×	30 0.4×	10	502
Nicole L. Welch United States	6	386 0.7×	102 0.9×	36 0.4×	41 0.6×	59 0.9×	11	482
Lu Dang China	9	501 0.9×	139 1.3×	32 0.4×	61 0.9×	72 1.1×	11	603
Greta Bigelyte Lithuania	5	657 1.2×	41 0.4×	110 1.2×	114 1.6×	47 0.7×	5	686
Rimantė Žedaveinytė United States	5	511 0.9×	39 0.4×	81 0.9×	87 1.2×	35 0.5×	7	545
Shuhan Lu China	5	374 0.7×	126 1.2×	44 0.5×	23 0.3×	35 0.5×	9	428
Tinna-Sólveig F. Kosoko-Thoroddsen United States	2	488 0.9×	252 2.3×	30 0.3×	15 0.2×	73 1.1×	3	597
Dana Štveráková Czechia	7	565 1.0×	48 0.4×	74 0.8×	371 5.3×	30 0.4×	12	697
Nora C. Pyenson United States	6	776 1.4×	33 0.3×	41 0.5×	174 2.5×	25 0.4×	8	806
Siyuan Liu China	6	365 0.6×	73 0.7×	20 0.2×	44 0.6×	49 0.7×	10	440

Countries citing papers authored by Qingqin Gao

Since Specialization

Citations

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

Fields of papers citing papers by Qingqin Gao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingqin Gao

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

7 of 7 papers shown

1.

Cui, Tongtong, Bingyu Cai, Xin Liu, et al.. (2024). Therapeutic In Vivo Gene Editing Achieved by a Hypercompact CRISPR‐Cas12f1 System Delivered with All‐in‐One Adeno‐Associated Virus. Advanced Science. 11(19). e2308095–e2308095. 9 indexed citations

2.

Teng, Fei, Tongtong Cui, Li Zhou, et al.. (2024). Programmable synthetic receptors: the next-generation of cell and gene therapies. Signal Transduction and Targeted Therapy. 9(1). 7–7. 26 indexed citations

3.

Jiang, Haiping, Yuning Chen, Zhengquan He, et al.. (2023). Targeting non-muscle myosin II inhibits proliferative vitreoretinopathy through regulating epithelial-mesenchymal transition. Biochemical and Biophysical Research Communications. 686. 149149–149149. 1 indexed citations

4.

Teng, Fei, Tongtong Cui, Qingqin Gao, et al.. (2019). Artificial sgRNAs engineered for genome editing with new Cas12b orthologs. Cell Discovery. 5(1). 23–23. 16 indexed citations

5.

Teng, Fei, Lu Guo, Tongtong Cui, et al.. (2019). CDetection: CRISPR-Cas12b-based DNA detection with sub-attomolar sensitivity and single-base specificity. Genome biology. 20(1). 132–132. 275 indexed citations breakdown →

6.

Teng, Fei, Jing Li, Tongtong Cui, et al.. (2019). Enhanced mammalian genome editing by new Cas12a orthologs with optimized crRNA scaffolds. Genome biology. 20(1). 15–15. 82 indexed citations

7.

Teng, Fei, Tongtong Cui, Guihai Feng, et al.. (2018). Repurposing CRISPR-Cas12b for mammalian genome engineering. Cell Discovery. 4(1). 63–63. 200 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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