Jeffrey Chu

1.7k total citations
32 papers, 1.1k citations indexed

About

Jeffrey Chu is a scholar working on Molecular Biology, Aging and Ophthalmology. According to data from OpenAlex, Jeffrey Chu has authored 32 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 8 papers in Aging and 5 papers in Ophthalmology. Recurrent topics in Jeffrey Chu's work include Genetics, Aging, and Longevity in Model Organisms (8 papers), CRISPR and Genetic Engineering (4 papers) and Machine Learning in Bioinformatics (3 papers). Jeffrey Chu is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (8 papers), CRISPR and Genetic Engineering (4 papers) and Machine Learning in Bioinformatics (3 papers). Jeffrey Chu collaborates with scholars based in Canada, United States and China. Jeffrey Chu's co-authors include Nansheng Chen, Ke Wang, Rong She, Jian Pei, Guanyi Kong, Lucie Semenec, Xiaolan Jiang, Christian Frech, Chuan‐Fan Ding and Huabang Zhou and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Jeffrey Chu

27 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeffrey Chu Canada 14 560 271 220 199 143 32 1.1k
Daniel A. Skelly United States 16 1.2k 2.1× 154 0.6× 248 1.1× 191 1.0× 92 0.6× 34 1.7k
Richard P. Metz United States 23 571 1.0× 71 0.3× 249 1.1× 165 0.8× 299 2.1× 56 1.4k
Vlatka Zoldoš Croatia 21 1.5k 2.6× 80 0.3× 347 1.6× 408 2.1× 71 0.5× 50 1.9k
Frédéric Biemar Belgium 16 985 1.8× 321 1.2× 274 1.2× 87 0.4× 41 0.3× 18 1.3k
Jarod Rollins United States 17 539 1.0× 99 0.4× 287 1.3× 341 1.7× 43 0.3× 24 1.2k
Tohru Komiya Japan 25 1.7k 3.0× 91 0.3× 535 2.4× 127 0.6× 78 0.5× 49 2.3k
Parthive H. Patel United States 9 966 1.7× 492 1.8× 130 0.6× 42 0.2× 268 1.9× 11 2.0k
Dori C. Woods United States 28 1.3k 2.3× 120 0.4× 456 2.1× 38 0.2× 90 0.6× 63 2.4k
Marine Jeanmougin Norway 12 808 1.4× 70 0.3× 119 0.5× 106 0.5× 147 1.0× 29 1.3k
Dileepa Diyagama Australia 7 760 1.4× 58 0.2× 164 0.7× 73 0.4× 140 1.0× 7 1.2k

Countries citing papers authored by Jeffrey Chu

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeffrey Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey Chu. A scholar is included among the top collaborators of Jeffrey Chu 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 Jeffrey Chu. Jeffrey Chu 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.
Shaia, Jacqueline K., et al.. (2025). Prediction of Poor Visual Outcomes at Idiopathic Intracranial Hypertension Diagnosis Using a Supervised Machine Learning Algorithm. Journal of Neuro-Ophthalmology. 45(4). 440–446.
2.
Chu, Jeffrey, et al.. (2025). Risk of retinal disease and visual impairment in individuals with psychiatric disorders. Eye. 39(11). 2269–2276.
3.
Shaia, Jacqueline K., et al.. (2024). Changes in Prevalence of Idiopathic Intracranial Hypertension in the United States Between 2015 and 2022, Stratified by Sex, Race, and Ethnicity. Neurology. 102(3). e208036–e208036. 17 indexed citations
4.
Chu, Jeffrey, Jacqueline K. Shaia, Matthew W. Russell, et al.. (2024). Characterization and prevalence of ocular comorbidities and risk of legal blindness across the United States. Eye. 38(16). 3118–3124. 3 indexed citations
5.
Chu, Jeffrey, et al.. (2024). Prevalence and diversity of retinal disease in adults with Down syndrome. Eye. 39(3). 505–515.
6.
Chu, Jeffrey, et al.. (2024). AMD Versal™ AI Edge Series Gen 2 for Vision and Automotive. 1–28. 1 indexed citations
7.
Yu, Shicheng, Chaoran Zheng, & Jeffrey Chu. (2021). Identification of Essential Genes in Caenorhabditis elegans with Lethal Mutations Maintained by Genetic Balancers. Methods in molecular biology. 2377. 345–362. 1 indexed citations
8.
Chu, Jeffrey, Bo Peng, Kuanqiang Tang, et al.. (2021). Eight soybean reference genome resources from varying latitudes and agronomic traits. Scientific Data. 8(1). 164–164. 18 indexed citations
9.
Qin, Zhaozhao, Robert Johnsen, Shicheng Yu, et al.. (2018). Genomic Identification and Functional Characterization of Essential Genes in Caenorhabditis elegans. G3 Genes Genomes Genetics. 8(3). 981–997. 15 indexed citations
10.
Chu, Jeffrey, et al.. (2016). The impact of a preloaded intraocular lens delivery system on operating room efficiency in routine cataract surgery. Clinical ophthalmology. 10. 1123–1123. 26 indexed citations
11.
Dong, Lingli, Hongfang Liu, Juncheng Zhang, et al.. (2015). Single-molecule real-time transcript sequencing facilitates common wheat genome annotation and grain transcriptome research. BMC Genomics. 16(1). 1039–1039. 102 indexed citations
12.
Zou, Shan–Shan, Jiarui Li, Huabang Zhou, et al.. (2014). Mutational landscape of intrahepatic cholangiocarcinoma. Nature Communications. 5(1). 5696–5696. 290 indexed citations
13.
Uyar, Bora, Jeffrey Chu, Ismael A. Vergara, et al.. (2012). RNA-seq analysis of the C. briggsae transcriptome. Genome Research. 22(8). 1567–1580. 23 indexed citations
14.
Chu, Jeffrey, Maja Tarailo‐Graovac, Di Zhang, et al.. (2011). Fine tuning of RFX/DAF-19-regulated target gene expression through binding to multiple sites in Caenorhabditis elegans. Nucleic Acids Research. 40(1). 53–64. 8 indexed citations
15.
Çolak, Recep, et al.. (2010). Module Discovery by Exhaustive Search for Densely Connected, Co-Expressed Regions in Biomolecular Interaction Networks. PLoS ONE. 5(10). e13348–e13348. 18 indexed citations
16.
Mah, Allan K., Domena Tu, Robert Johnsen, et al.. (2010). Characterization of the octamer, a cis-regulatory element that modulates excretory cell gene-expression in Caenorhabditis elegans. BMC Molecular Biology. 11(1). 19–19. 3 indexed citations
17.
She, Rong, Jeffrey Chu, Ke Wang, Jian Pei, & Nansheng Chen. (2008). genBlastA: Enabling BLAST to identify homologous gene sequences. Genome Research. 19(1). 143–149. 204 indexed citations
18.
Semenec, Lucie, et al.. (2008). Identification and characterization of novel human tissue-specific RFX transcription factors. BMC Evolutionary Biology. 8(1). 226–226. 99 indexed citations
19.
Mah, Allan K., Derek S. Chew, Jeffrey Chu, et al.. (2007). Transcriptional Regulation of AQP-8, a Caenorhabditis elegans Aquaporin Exclusively Expressed in the Excretory System, by the POU Homeobox Transcription Factor CEH-6. Journal of Biological Chemistry. 282(38). 28074–28086. 23 indexed citations
20.
Chen, Nansheng, Allan K. Mah, Oliver E. Blacque, et al.. (2006). Identification of ciliary and ciliopathy genes in Caenorhabditis elegansthrough comparative genomics. Genome biology. 7(12). R126–R126. 73 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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