Connie Jiang

1.2k total citations
20 papers, 741 citations indexed

About

Connie Jiang is a scholar working on Molecular Biology, Genetics and Biophysics. According to data from OpenAlex, Connie Jiang has authored 20 papers receiving a total of 741 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 6 papers in Genetics and 3 papers in Biophysics. Recurrent topics in Connie Jiang's work include Genetic Syndromes and Imprinting (3 papers), Single-cell and spatial transcriptomics (3 papers) and Epigenetics and DNA Methylation (3 papers). Connie Jiang is often cited by papers focused on Genetic Syndromes and Imprinting (3 papers), Single-cell and spatial transcriptomics (3 papers) and Epigenetics and DNA Methylation (3 papers). Connie Jiang collaborates with scholars based in United States, China and Australia. Connie Jiang's co-authors include Jennifer M. Kalish, Marisa S. Bartolomei, Arjun Raj, Benjamin Emert, Ian Dardani, Eduardo A. Torre, Meng Deng, Steve C. Danzer, Andreas W. Loepke and Elizabeth Hughes and has published in prestigious journals such as Journal of Clinical Investigation, Neuron and Nature Genetics.

In The Last Decade

Connie Jiang

19 papers receiving 734 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Connie Jiang United States 14 448 155 120 112 104 20 741
Darko Bogdanović Sweden 4 311 0.7× 60 0.4× 97 0.8× 29 0.3× 30 0.3× 9 576
Myung Ae Lee South Korea 14 281 0.6× 64 0.4× 68 0.6× 9 0.1× 15 0.1× 36 530
Laura Gritti Italy 6 214 0.5× 158 1.0× 53 0.4× 7 0.1× 6 0.1× 6 512
Justin T. Lee United States 7 213 0.5× 48 0.3× 51 0.4× 8 0.1× 45 0.4× 9 535
Edith M. Schneider Gasser Switzerland 11 184 0.4× 42 0.3× 102 0.8× 21 0.2× 2 0.0× 20 631
Mary Herman United States 7 180 0.4× 59 0.4× 50 0.4× 4 0.0× 12 0.1× 12 626
Suhail Asrar Canada 10 313 0.7× 79 0.5× 108 0.9× 7 0.1× 2 0.0× 12 634
Jonathan A. Fidler United States 14 230 0.5× 31 0.2× 108 0.9× 9 0.1× 21 0.2× 15 651
Yanjie Fan China 15 394 0.9× 48 0.3× 304 2.5× 6 0.1× 1 0.0× 48 792

Countries citing papers authored by Connie Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Connie Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Connie Jiang

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

All Works

20 of 20 papers shown
1.
Lam, Michael T., Connie Jiang, & Pui Y. Lee. (2025). T-ing up the storm: pathogenic cycling lymphocytes in the biology of macrophage activation syndrome. Pediatric Rheumatology. 23(1). 29–29. 1 indexed citations
2.
Thomson, Kate, Connie Jiang, Ebony Richardson, et al.. (2024). Clinical interpretation of KCNH2 variants using a robust PS3/BS3 functional patch-clamp assay. Human Genetics and Genomics Advances. 5(2). 100270–100270. 5 indexed citations
3.
Jain, Naveen, Yogesh Goyal, Margaret C. Dunagin, et al.. (2024). Retrospective identification of cell-intrinsic factors that mark pluripotency potential in rare somatic cells. Cell Systems. 15(2). 109–133.e10. 13 indexed citations
4.
Richman, Lee P., Yogesh Goyal, Connie Jiang, & Arjun Raj. (2023). ClonoCluster: A method for using clonal origin to inform transcriptome clustering. Cell Genomics. 3(2). 100247–100247. 9 indexed citations
5.
Dardani, Ian, Benjamin Emert, Yogesh Goyal, et al.. (2022). ClampFISH 2.0 enables rapid, scalable amplified RNA detection in situ. Nature Methods. 19(11). 1403–1410. 23 indexed citations
6.
Jiang, Connie, Ebony Richardson, Adam P. Hill, et al.. (2022). A calibrated functional patch-clamp assay to enhance clinical variant interpretation in KCNH2-related long QT syndrome. The American Journal of Human Genetics. 109(7). 1199–1207. 17 indexed citations
7.
Jiang, Connie, Yogesh Goyal, Naveen Jain, et al.. (2022). Cell type determination for cardiac differentiation occurs soon after seeding of human-induced pluripotent stem cells. Genome biology. 23(1). 90–90. 11 indexed citations
8.
Torre, Eduardo A., Eri Arai, Connie Jiang, et al.. (2021). Genetic screening for single-cell variability modulators driving therapy resistance. Nature Genetics. 53(1). 76–85. 36 indexed citations
9.
Deng, Xin, George D. Thurston, Wangjian Zhang, et al.. (2021). Application of data science methods to identify school and home risk factors for asthma and allergy-related symptoms among children in New York. The Science of The Total Environment. 770. 144746–144746. 15 indexed citations
10.
Emert, Benjamin, Christopher Coté, Eduardo A. Torre, et al.. (2021). Variability within rare cell states enables multiple paths toward drug resistance. Nature Biotechnology. 39(7). 865–876. 81 indexed citations
11.
Lewis, Eastman M., Genevieve Stein-O’Brien, Romain Nardou, et al.. (2020). Parallel Social Information Processing Circuits Are Differentially Impacted in Autism. Neuron. 108(4). 659–675.e6. 52 indexed citations
12.
Rouhanifard, Sara H., Ian A. Mellis, Margaret C. Dunagin, et al.. (2019). Correction: Amendments: Author Correction: ClampFISH detects individual nucleic acid molecules using click chemistry–based amplification. Nature Biotechnology. 37(1). 102–102. 16 indexed citations
13.
Ou, Kristy, Ming Yu, Nicholas Moss, et al.. (2018). Targeted demethylation at the CDKN1C/p57 locus induces human β cell replication. Journal of Clinical Investigation. 129(1). 209–214. 48 indexed citations
14.
Rouhanifard, Sara H., Ian A. Mellis, Margaret C. Dunagin, et al.. (2018). ClampFISH detects individual nucleic acid molecules using click chemistry–based amplification. Nature Biotechnology. 37(1). 84–89. 106 indexed citations
15.
16.
Kalish, Jennifer M., et al.. (2016). Visualizing allele-specific expression in single cells reveals epigenetic mosaicism in an H19 loss-of-imprinting mutant. Genes & Development. 30(5). 567–578. 29 indexed citations
17.
Deng, Meng, Rylon D. Hofacer, Connie Jiang, et al.. (2014). Brain regional vulnerability to anaesthesia-induced neuroapoptosis shifts with age at exposure and extends into adulthood for some regions. British Journal of Anaesthesia. 113(3). 443–451. 75 indexed citations
18.
Kalish, Jennifer M., Connie Jiang, & Marisa S. Bartolomei. (2014). Epigenetics and imprinting in human disease. The International Journal of Developmental Biology. 58(2-3-4). 291–298. 90 indexed citations
19.
Hofacer, Rylon D., Meng Deng, Christopher G. Ward, et al.. (2013). Cell age–specific vulnerability of neurons to anesthetic toxicity. Annals of Neurology. 73(6). 695–704. 90 indexed citations
20.
Zhou, Jingjing, et al.. (2003). Rapid nongenomic effects of glucocorticoids on allergic asthma reaction in the guinea pig. Journal of Endocrinology. 177(1). R1–R4. 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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