James J. Cai

5.6k total citations · 1 hit paper
112 papers, 3.7k citations indexed

About

James J. Cai is a scholar working on Molecular Biology, Genetics and Epidemiology. According to data from OpenAlex, James J. Cai has authored 112 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Molecular Biology, 20 papers in Genetics and 18 papers in Epidemiology. Recurrent topics in James J. Cai's work include Single-cell and spatial transcriptomics (16 papers), Gene Regulatory Network Analysis (12 papers) and Bioinformatics and Genomic Networks (12 papers). James J. Cai is often cited by papers focused on Single-cell and spatial transcriptomics (16 papers), Gene Regulatory Network Analysis (12 papers) and Bioinformatics and Genomic Networks (12 papers). James J. Cai collaborates with scholars based in United States, China and Hong Kong. James J. Cai's co-authors include Kwok‐Yung Yuen, Patrick C. Y. Woo, Susanna K. P. Lau, Dmitri A. Petrov, Daniel Osorio, Hoi‐Wah Tsoi, Leo L. M. Poon, Chung‐Ming Chu, Kwok‐Hung Chan and Rosana Wing‐Shan Poon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

James J. Cai

104 papers receiving 3.7k citations

Hit Papers

Characterization and Complete Genome Sequence of a Novel ... 2004 2026 2011 2018 2004 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James J. Cai United States 32 1.7k 1.1k 643 463 442 112 3.7k
Qi Liu China 34 1.7k 1.0× 732 0.7× 555 0.9× 324 0.7× 241 0.5× 172 3.6k
Harm van Bakel United States 34 2.9k 1.6× 687 0.6× 705 1.1× 611 1.3× 686 1.6× 114 4.5k
Thomas G. Wood United States 44 2.3k 1.3× 1.4k 1.3× 419 0.7× 377 0.8× 514 1.2× 114 5.7k
Matthias Schweizer Switzerland 38 1.6k 0.9× 1.1k 1.0× 840 1.3× 829 1.8× 185 0.4× 123 5.3k
Apurva Narechania United States 27 2.5k 1.4× 725 0.7× 558 0.9× 794 1.7× 719 1.6× 58 4.5k
Hongbin He China 29 854 0.5× 615 0.6× 521 0.8× 324 0.7× 144 0.3× 166 2.7k
Patrick Collins United States 28 1.6k 0.9× 516 0.5× 573 0.9× 863 1.9× 300 0.7× 93 3.6k
Walter Becker Germany 46 3.2k 1.8× 1.1k 1.0× 1.0k 1.6× 949 2.0× 498 1.1× 136 6.8k
Yves Rouillé France 37 1.7k 1.0× 511 0.5× 1.3k 2.0× 516 1.1× 166 0.4× 109 5.4k
Junjie Zhang China 29 1.9k 1.1× 365 0.3× 331 0.5× 1.1k 2.3× 126 0.3× 143 3.3k

Countries citing papers authored by James J. Cai

Since Specialization
Citations

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

Fields of papers citing papers by James J. Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James J. Cai. 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 James J. Cai. The network helps show where James J. Cai may publish in the future.

Co-authorship network of co-authors of James J. Cai

This figure shows the co-authorship network connecting the top 25 collaborators of James J. Cai. A scholar is included among the top collaborators of James J. Cai 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 James J. Cai. James J. Cai 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
2.
Sarkar, Mrinmoy, James Sampson, Yava Jones‐Hall, et al.. (2025). LILRB4 regulates circadian disruption-induced mammary tumorigenesis via non-canonical WNT signaling pathway. Oncogene. 44(46). 4491–4504. 1 indexed citations
4.
Gomès, Bruno, et al.. (2025). Machine learning identifies clinical tumor mutation landscape pathways of resistance to checkpoint inhibitor therapy in NSCLC. Journal for ImmunoTherapy of Cancer. 13(3). e009092–e009092. 4 indexed citations
5.
Ahmad, Irshad, Patricia Faulkner, Ivan Ivanov, et al.. (2024). Single-nucleus transcriptomics of epicardial adipose tissue from female pigs reveals effects of exercise training on resident innate and adaptive immune cells. Cell Communication and Signaling. 22(1). 243–243. 4 indexed citations
6.
Zhong, Yan, et al.. (2024). Controlled noise: evidence of epigenetic regulation of single-cell expression variability. Bioinformatics. 40(7). 1 indexed citations
7.
Yan, Xingxing, Kaiye Liu, Qian Xu, et al.. (2024). Parallel degradome-seq and DMS-MaPseq substantially revise the miRNA biogenesis atlas in Arabidopsis. Nature Plants. 10(7). 1126–1143. 7 indexed citations
8.
Li, Honggui, Xiaoxiao Wang, Qian Xu, et al.. (2024). HFD feeding for seven months abolishes STING disruption-driven but not female sex-based protection against hepatic steatosis and inflammation in mice. The Journal of Nutritional Biochemistry. 135. 109770–109770. 2 indexed citations
9.
Cai, James J., et al.. (2023). Quantum gene regulatory networks. npj Quantum Information. 9(1). 7 indexed citations
10.
Yang, Wanbao, Da Mi Kim, Wen G. Jiang, et al.. (2023). Suppression of FOXO1 attenuates inflamm‐aging and improves liver function during aging. Aging Cell. 22(10). e13968–e13968. 20 indexed citations
11.
Pinson, Marisa R., Amanda H. Mahnke, Daniel Osorio, et al.. (2022). Gag‐like proteins: Novel mediators of prenatal alcohol exposure in neural development. Alcoholism Clinical and Experimental Research. 46(4). 556–569. 7 indexed citations
12.
Osorio, Daniel, Marieke L. Kuijjer, & James J. Cai. (2021). rPanglaoDB: an R package to download and merge labeled single-cell RNA-seq data from the PanglaoDB database. Bioinformatics. 38(2). 580–582. 3 indexed citations
13.
Yang, Yongjian, Daniel Osorio, Laurie A. Davidson, et al.. (2021). Single-cell RNA Sequencing Reveals How the Aryl Hydrocarbon Receptor Shapes Cellular Differentiation Potency in the Mouse Colon. Cancer Prevention Research. 15(1). 17–28. 9 indexed citations
14.
Osorio, Daniel & James J. Cai. (2020). Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control. Bioinformatics. 37(7). 963–967. 113 indexed citations
16.
Yang, Ence, Franklin Wang‐Ngai Chow, Gang Wang, et al.. (2014). Signature Gene Expression Reveals Novel Clues to the Molecular Mechanisms of Dimorphic Transition in Penicillium marneffei. PLoS Genetics. 10(10). e1004662–e1004662. 28 indexed citations
17.
Chang, Chia Lin, et al.. (2010). Adaptive selection of an incretin gene in Eurasian populations. Genome Research. 21(1). 21–32. 12 indexed citations
18.
Luistro, Leopoldo, Wei He, Melissa Smith, et al.. (2009). Preclinical Profile of a Potent γ-Secretase Inhibitor Targeting Notch Signaling with In vivo Efficacy and Pharmacodynamic Properties. Cancer Research. 69(19). 7672–7680. 154 indexed citations
19.
Woo, Patrick C. Y., Susanna K. P. Lau, Herman Tse, et al.. (2009). The Complete Genome and Proteome of Laribacter hongkongensis Reveal Potential Mechanisms for Adaptations to Different Temperatures and Habitats. PLoS Genetics. 5(3). e1000416–e1000416. 49 indexed citations
20.
Lu, Stephen C.-Y., et al.. (2002). Conflict Management in Collaborative Engineering Design: Basic Research in Fundamental Theory, Modeling Framework, and Computer Support for Collaborative Engineering Activities. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core).

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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