Su H. Chu

4.4k total citations
41 papers, 791 citations indexed

About

Su H. Chu is a scholar working on Molecular Biology, Physiology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Su H. Chu has authored 41 papers receiving a total of 791 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 10 papers in Physiology and 9 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Su H. Chu's work include Metabolomics and Mass Spectrometry Studies (6 papers), Rheumatoid Arthritis Research and Therapies (6 papers) and Neonatal Respiratory Health Research (5 papers). Su H. Chu is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (6 papers), Rheumatoid Arthritis Research and Therapies (6 papers) and Neonatal Respiratory Health Research (5 papers). Su H. Chu collaborates with scholars based in United States, Taiwan and Denmark. Su H. Chu's co-authors include W. Allan Walker, Jessica Lasky‐Su, Yen‐Tsung Huang, Rachel S. Kelly, Karl T. Kelsey, Eric B. Loucks, Karen H. Costenbader, Stephen L. Buka, Boris V. Zemelman and Bing Lü and has published in prestigious journals such as Journal of Clinical Investigation, American Journal of Clinical Nutrition and Scientific Reports.

In The Last Decade

Su H. Chu

40 papers receiving 775 citations

Peers

Su H. Chu
Monica McGrath United States
Sukhdev Singh United Kingdom
David Herion United States
Amy Murphy United States
Mariana Gerschenson United States
Su H. Chu
Citations per year, relative to Su H. Chu Su H. Chu (= 1×) peers Alessandro Rossi

Countries citing papers authored by Su H. Chu

Since Specialization
Citations

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

Fields of papers citing papers by Su H. Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Su H. Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Su H. Chu. A scholar is included among the top collaborators of Su H. 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 Su H. Chu. Su H. 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.
Melough, Melissa M., Monica McGrath, Brent R. Collett, et al.. (2025). Gestational vitamin D concentration and child cognitive development: a longitudinal cohort study in the Environmental influences on Child Health Outcomes Program. American Journal of Clinical Nutrition. 122(2). 571–581.
2.
Braisted, John, Su H. Chu, Qingwen Chen, et al.. (2023). Nucleotide, Phospholipid, and Kynurenine Metabolites Are Robustly Associated with COVID-19 Severity and Time of Plasma Sample Collection in a Prospective Cohort Study. International Journal of Molecular Sciences. 25(1). 346–346. 1 indexed citations
3.
Kelly, Rachel S., Su H. Chu, Priyadarshini Kachroo, et al.. (2023). Elevated third trimester corticosteroid levels are associated with fewer offspring infections. Scientific Reports. 13(1). 10461–10461. 1 indexed citations
4.
Chu, Su H., Chirag M. Vyas, Olivia I. Okereke, et al.. (2023). Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study. Metabolites. 13(7). 851–851. 2 indexed citations
5.
Kelly, Rachel S., Kathleen Lee‐Sarwar, Yih‐Chieh Chen, et al.. (2022). Maternal Inflammatory Biomarkers during Pregnancy and Early Life Neurodevelopment in Offspring: Results from the VDAART Study. International Journal of Molecular Sciences. 23(23). 15249–15249. 7 indexed citations
6.
Huang, Mengna, Rachel S. Kelly, Su H. Chu, et al.. (2021). Maternal Metabolome in Pregnancy and Childhood Asthma or Recurrent Wheeze in the Vitamin D Antenatal Asthma Reduction Trial. Metabolites. 11(2). 65–65. 16 indexed citations
7.
Chu, Su H., Mengna Huang, Rachel S. Kelly, et al.. (2021). Circulating levels of maternal vitamin D and risk of ADHD in offspring: results from the Vitamin D Antenatal Asthma Reduction Trial. International Journal of Epidemiology. 51(3). 910–918. 10 indexed citations
8.
Knihtilä, Hanna, Benjamin J. Stubbs, Vincent J. Carey, et al.. (2021). Low gestational vitamin D level and childhood asthma are related to impaired lung function in high-risk children. Journal of Allergy and Clinical Immunology. 148(1). 110–119.e9. 11 indexed citations
9.
Ford, Julia A., Xinyi Liu, Su H. Chu, et al.. (2020). Asthma, Chronic Obstructive Pulmonary Disease, and Subsequent Risk for Incident Rheumatoid Arthritis Among Women: A Prospective Cohort Study. Arthritis & Rheumatology. 72(5). 704–713. 44 indexed citations
10.
Huang, Mengna, Rachel S. Kelly, Priyadarshini Kachroo, et al.. (2020). Plasma 25-Hydroxyvitamin D Concentrations are Associated with Polyunsaturated Fatty Acid Metabolites in Young Children: Results from the Vitamin D Antenatal Asthma Reduction Trial. Metabolites. 10(4). 151–151. 5 indexed citations
11.
Kelly, Rachel S., Avron Spiro, Pantel Vokonas, et al.. (2020). Metabolomic signatures of lead exposure in the VA Normative Aging Study. Environmental Research. 190. 110022–110022. 22 indexed citations
12.
Chu, Su H., Jing Cui, Jeffrey A. Sparks, et al.. (2020). Circulating plasma metabolites and risk of rheumatoid arthritis in the Nurses’ Health Study. Lara D. Veeken. 59(11). 3369–3379. 23 indexed citations
13.
Mirzakhani, Hooman, Rachel S. Kelly, Su H. Chu, et al.. (2020). Stability of developmental status and risk of impairment at 24 and 36 months in late preterm infants. Infant Behavior and Development. 60. 101462–101462. 11 indexed citations
14.
Chu, Su H., Mengna Huang, Rachel S. Kelly, et al.. (2019). Integration of Metabolomic and Other Omics Data in Population-Based Study Designs: An Epidemiological Perspective. Metabolites. 9(6). 117–117. 57 indexed citations
15.
Chu, Su H., Karl T. Kelsey, Devin C. Koestler, Eric B. Loucks, & Yen‐Tsung Huang. (2019). Leveraging cell‐specific differentially methylated regions to identify leukocyte infiltration in adipose tissue. Genetic Epidemiology. 43(8). 1018–1029. 1 indexed citations
16.
Yoshida, Kazuki, Tzu‐Chieh Lin, Melissa Y. Wei, et al.. (2019). Roles of Postdiagnosis Accumulation of Morbidities and Lifestyle Changes in Excess Total and Cause‐Specific Mortality Risk in Rheumatoid Arthritis. Arthritis Care & Research. 73(2). 188–198. 40 indexed citations
17.
Zaccardelli, Alessandra, Xinyi Liu, Julia A. Ford, et al.. (2019). Asthma and elevation of anti-citrullinated protein antibodies prior to the onset of rheumatoid arthritis. Arthritis Research & Therapy. 21(1). 246–246. 31 indexed citations
18.
Chu, Su H. & Yen‐Tsung Huang. (2017). Integrated genomic analysis of biological gene sets with applications in lung cancer prognosis. BMC Bioinformatics. 18(1). 336–336. 7 indexed citations
19.
Huang, Yen‐Tsung, Su H. Chu, Eric B. Loucks, et al.. (2016). Epigenome-wide profiling of DNA methylation in paired samples of adipose tissue and blood. Epigenetics. 11(3). 227–236. 51 indexed citations
20.
Luo, Rui, Stephan Sanders, Yuan Tian, et al.. (2012). Genome-wide Transcriptome Profiling Reveals the Functional Impact of Rare De Novo and Recurrent CNVs in Autism Spectrum Disorders. The American Journal of Human Genetics. 91(1). 38–55. 122 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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