Mahdi Moqri

2.0k total citations · 2 hit papers
23 papers, 397 citations indexed

About

Mahdi Moqri is a scholar working on Molecular Biology, Sociology and Political Science and Physiology. According to data from OpenAlex, Mahdi Moqri has authored 23 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Sociology and Political Science and 4 papers in Physiology. Recurrent topics in Mahdi Moqri's work include Epigenetics and DNA Methylation (6 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and Open Source Software Innovations (3 papers). Mahdi Moqri is often cited by papers focused on Epigenetics and DNA Methylation (6 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and Open Source Software Innovations (3 papers). Mahdi Moqri collaborates with scholars based in United States, United Kingdom and Iran. Mahdi Moqri's co-authors include Kejun Ying, Vadim N. Gladyshev, Subhajyoti Bandyopadhyay, Liangfei Qiu, Andrei E. Tarkhov, Xiaowei Mei, Steve Horvath, M Snyder, Marie C. Sadler and Xia Shen and has published in prestigious journals such as Nature Communications, PLoS ONE and Cell Metabolism.

In The Last Decade

Mahdi Moqri

19 papers receiving 387 citations

Hit Papers

Dynamic lipidome alterati... 2023 2026 2024 2023 2024 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mahdi Moqri United States 9 186 71 45 36 32 23 397
Pankaj K. Choudhary United States 15 145 0.8× 113 1.6× 5 0.1× 9 0.3× 24 0.8× 59 701
Xuemei Liu China 15 117 0.6× 34 0.5× 5 0.1× 10 0.3× 40 1.3× 50 674
Jinglong Zhang China 12 126 0.7× 26 0.4× 2 0.0× 14 0.4× 30 0.9× 27 377
Sabreena Safuan Malaysia 11 275 1.5× 92 1.3× 27 0.6× 29 0.8× 35 1.1× 37 666
Soyoung Kim South Korea 12 137 0.7× 194 2.7× 13 0.3× 16 0.4× 126 3.9× 25 736
Dongjie Zhou China 14 217 1.2× 25 0.4× 26 0.6× 3 0.1× 36 1.1× 54 456
Ting-I Lee Taiwan 12 164 0.9× 97 1.4× 3 0.1× 33 0.9× 48 1.5× 33 547
Shuyan Wang China 18 183 1.0× 88 1.2× 4 0.1× 25 0.7× 46 1.4× 78 963
Qi Jin China 8 139 0.7× 60 0.8× 1 0.0× 26 0.7× 38 1.2× 16 548
Magdalena Zwierzyna United Kingdom 8 176 0.9× 48 0.7× 15 0.3× 4 0.1× 49 1.5× 11 522

Countries citing papers authored by Mahdi Moqri

Since Specialization
Citations

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

Fields of papers citing papers by Mahdi Moqri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mahdi Moqri

This figure shows the co-authorship network connecting the top 25 collaborators of Mahdi Moqri. A scholar is included among the top collaborators of Mahdi Moqri 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 Mahdi Moqri. Mahdi Moqri 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.
Herzog, Chiara, Jesse R. Poganik, Nir Barzilai, et al.. (2025). Biomarkers of Aging– NIA Joint Symposium 2024: New Insights Into Aging Biomarkers. Aging Cell. 24(7). e70124–e70124.
2.
Poganik, Jesse R., Mahdi Moqri, Chiara Herzog, et al.. (2025). Digital biomarkers of ageing for monitoring physiological systems in community-dwelling adults. The Lancet Healthy Longevity. 6(6). 100725–100725. 2 indexed citations
3.
Belsky, Daniel W., Kejun Ying, Mahdi Moqri, et al.. (2025). An unbiased comparison of 14 epigenetic clocks in relation to 174 incident disease outcomes. Nature Communications. 16(1). 11164–11164.
4.
Katsanos, Dimitris, et al.. (2025). Epigenetic age predictors for non-invasive assessment of human skin. PubMed. 12(1). 11–11.
5.
Cohen, Alan A., John Beard, Luigi Ferrucci, et al.. (2025). Balancing the promise and risks of geroscience interventions. Nature Aging. 5(1). 4–8. 1 indexed citations
6.
Goeminne, Ludger J.E., Anastasiya V. Vladimirova, Alexander Tyshkovskiy, et al.. (2024). Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems. Cell Metabolism. 37(1). 205–222.e6. 22 indexed citations
7.
Ying, Kejun, José Pedro Castro, Anastasia V. Shindyapina, et al.. (2024). Depletion of loss-of-function germline mutations in centenarians reveals longevity genes. Nature Communications. 15(1). 9030–9030.
8.
Tarkhov, Andrei E., Sirui Zhang, Kejun Ying, et al.. (2024). Nature of epigenetic aging from a single-cell perspective. Nature Aging. 4(6). 854–870. 28 indexed citations
9.
Ying, Kejun, Andrei E. Tarkhov, Marie C. Sadler, et al.. (2024). Causality-enriched epigenetic age uncouples damage and adaptation. Nature Aging. 4(2). 231–246. 72 indexed citations breakdown →
10.
Moqri, Mahdi, Andrea Cipriano, Daniel J. Simpson, et al.. (2024). PRC2-AgeIndex as a universal biomarker of aging and rejuvenation. Nature Communications. 15(1). 5956–5956. 22 indexed citations
11.
Cipriano, Andrea, Alessio Colantoni, Mahdi Moqri, et al.. (2024). Transcriptional and epigenetic characterization of a new in vitro platform to model the formation of human pharyngeal endoderm. Genome biology. 25(1). 211–211. 1 indexed citations
12.
Hornburg, Daniel, Si Wu, Mahdi Moqri, et al.. (2023). Dynamic lipidome alterations associated with human health, disease and ageing. Nature Metabolism. 5(9). 1578–1594. 111 indexed citations breakdown →
13.
Cipriano, Andrea, Mahdi Moqri, Sun Y. Maybury‐Lewis, et al.. (2023). Mechanisms, pathways and strategies for rejuvenation through epigenetic reprogramming. Nature Aging. 4(1). 14–26. 28 indexed citations
14.
Wang, Shaodong, et al.. (2022). E-CatBoost: An efficient machine learning framework for predicting ICU mortality using the eICU Collaborative Research Database. PLoS ONE. 17(5). e0262895–e0262895. 37 indexed citations
15.
Moqri, Mahdi, et al.. (2020). An Exploratory Analysis of Electronic Intensive Care Unit (eICU) Collaborative Research Database. Journal of the Association for Information Systems. 2 indexed citations
16.
Wang, Shaodong, et al.. (2020). In-depth Evaluation of APACHE Scoring System Using eICU Database. Journal of the Association for Information Systems. 2 indexed citations
17.
Moqri, Mahdi, et al.. (2018). A Citation Analysis of the Basket of Eight IS Journals. Journal of the Association for Information Systems. 2 indexed citations
18.
Moqri, Mahdi, et al.. (2018). Effect of "Following" on contributions to open source communities. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 6 indexed citations
19.
Moqri, Mahdi, Liangfei Qiu, Subhajyoti Bandyopadhyay, & Ira Horowitz. (2015). The Effect of 'Following' on Contributions to Open Source Communities. SSRN Electronic Journal. 1 indexed citations
20.
Moqri, Mahdi, et al.. (2010). Supplier selection and order lot sizing using dynamic programming. International Journal of Industrial Engineering Computations. 2(2). 319–328. 12 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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