Polyna Khudyakov

2.3k total citations · 1 hit paper
24 papers, 1.5k citations indexed

About

Polyna Khudyakov is a scholar working on Molecular Biology, Statistics and Probability and Pathology and Forensic Medicine. According to data from OpenAlex, Polyna Khudyakov has authored 24 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Statistics and Probability and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Polyna Khudyakov's work include Vitamin D Research Studies (4 papers), Receptor Mechanisms and Signaling (4 papers) and Meta-analysis and systematic reviews (3 papers). Polyna Khudyakov is often cited by papers focused on Vitamin D Research Studies (4 papers), Receptor Mechanisms and Signaling (4 papers) and Meta-analysis and systematic reviews (3 papers). Polyna Khudyakov collaborates with scholars based in United States, United Kingdom and Mongolia. Polyna Khudyakov's co-authors include Donna Spiegelman, Nicola Orsini, Alicja Wolk, Ruifeng Li, Bahi Takkouche, Agustín Montes, Paul D. Feigin, Avishai Mandelbaum, Molin Wang and Davaasambuu Ganmaa and has published in prestigious journals such as The Lancet, Neurology and Clinical Infectious Diseases.

In The Last Decade

Polyna Khudyakov

23 papers receiving 1.5k citations

Hit Papers

Meta-Analysis for Linear and Nonlinear Dose-Response Rela... 2011 2026 2016 2021 2011 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
Polyna Khudyakov United States 12 410 323 204 181 172 24 1.5k
Hee‐Kyung Joh South Korea 21 396 1.0× 412 1.3× 132 0.6× 167 0.9× 174 1.0× 75 1.5k
Chang Beom Lee South Korea 14 460 1.1× 395 1.2× 225 1.1× 135 0.7× 301 1.8× 56 1.7k
Tingting Geng China 21 418 1.0× 337 1.0× 158 0.8× 125 0.7× 281 1.6× 84 1.6k
Diane Bunn United Kingdom 29 342 0.8× 768 2.4× 219 1.1× 295 1.6× 223 1.3× 80 2.7k
Hee‐Taik Kang South Korea 24 478 1.2× 455 1.4× 158 0.8× 101 0.6× 355 2.1× 114 1.8k
Jaakko Nevalainen Finland 26 523 1.3× 372 1.2× 213 1.0× 281 1.6× 217 1.3× 128 2.6k
William Leung China 21 273 0.7× 266 0.8× 107 0.5× 248 1.4× 274 1.6× 77 2.0k
Sang‐Ah Lee South Korea 21 339 0.8× 139 0.4× 150 0.7× 270 1.5× 96 0.6× 59 1.4k
Kyuwoong Kim South Korea 26 402 1.0× 393 1.2× 124 0.6× 74 0.4× 305 1.8× 88 2.2k
David Wormser Switzerland 9 510 1.2× 382 1.2× 92 0.5× 128 0.7× 217 1.3× 21 1.5k

Countries citing papers authored by Polyna Khudyakov

Since Specialization
Citations

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

Fields of papers citing papers by Polyna Khudyakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Polyna Khudyakov

This figure shows the co-authorship network connecting the top 25 collaborators of Polyna Khudyakov. A scholar is included among the top collaborators of Polyna Khudyakov 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 Polyna Khudyakov. Polyna Khudyakov 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.
Shanbhag, Niraj M., Jaya Padmanabhan, Zheng Zhang, et al.. (2025). An Acetylcholine M1 Receptor–Positive Allosteric Modulator (TAK-071) in Parkinson Disease With Cognitive Impairment. JAMA Neurology. 82(2). 152–152. 5 indexed citations
2.
Martineau, Adrian R., et al.. (2025). Exploring Risk Factors for ADHD Among Children at a Mongolian Public School: A Cross-Sectional Analysis. Journal of Attention Disorders. 29(6). 458–473. 1 indexed citations
6.
Yin, Wei, David Han, Polyna Khudyakov, et al.. (2022). A phase 1 study to evaluate the safety, tolerability and pharmacokinetics of TAK‐041 in healthy participants and patients with stable schizophrenia. British Journal of Clinical Pharmacology. 88(8). 3872–3882. 10 indexed citations
8.
Yin, Wei, Fahimeh Mamashli, Derek L. Buhl, et al.. (2021). Safety, pharmacokinetics and quantitative EEG modulation of TAK‐071, a novel muscarinic M1 receptor positive allosteric modulator, in healthy subjects. British Journal of Clinical Pharmacology. 88(2). 600–612. 13 indexed citations
9.
Shrestha, Archana, Dipesh Tamrakar, Biraj Man Karmacharya, et al.. (2019). Nepal Pioneer Worksite Intervention Study to lower cardio-metabolic risk factors: design and protocol. BMC Cardiovascular Disorders. 19(1). 48–48. 9 indexed citations
10.
Ganmaa, Davaasambuu, et al.. (2019). Risk factors for active tuberculosis in 938 QuantiFERON-positive schoolchildren in Mongolia: a community-based cross-sectional study. BMC Infectious Diseases. 19(1). 532–532. 9 indexed citations
11.
Ganmaa, Davaasambuu, Polyna Khudyakov, Christopher T. Sempos, et al.. (2018). Prevalence and Determinants of QuantiFERON-Diagnosed Tuberculosis Infection in 9810 Mongolian Schoolchildren. Clinical Infectious Diseases. 69(5). 813–819. 25 indexed citations
12.
Hawkins, Claudia, Ellen Hertzmark, Donna Spiegelman, et al.. (2017). Switching to second-line ART in relation to mortality in a large Tanzanian HIV cohort. Journal of Antimicrobial Chemotherapy. 72(7). 2060–2068. 6 indexed citations
13.
Spiegelman, Donna, Polyna Khudyakov, Molin Wang, & Tyler J. VanderWeele. (2017). Evaluating Public Health Interventions: 7. Let the Subject Matter Choose the Effect Measure: Ratio, Difference, or Something Else Entirely. American Journal of Public Health. 108(1). 73–76. 11 indexed citations
14.
Crippa, Alessio, Polyna Khudyakov, Molin Wang, Nicola Orsini, & Donna Spiegelman. (2016). A new measure of between‐studies heterogeneity in meta‐analysis. Statistics in Medicine. 35(21). 3661–3675. 33 indexed citations
15.
Khudyakov, Polyna, Malka Gorfine, David M. Zucker, & Donna Spiegelman. (2015). The impact of covariate measurement error on risk prediction. Statistics in Medicine. 34(15). 2353–2367. 22 indexed citations
17.
Masanja, Honorati, Emily R. Smith, Alfa Muhihi, et al.. (2014). Effect of neonatal vitamin A supplementation on mortality in infants in Tanzania (Neovita): a randomised, double-blind, placebo-controlled trial. The Lancet. 385(9975). 1324–1332. 49 indexed citations
18.
Takkouche, Bahi, et al.. (2013). Confidence Intervals for Heterogeneity Measures in Meta-analysis. American Journal of Epidemiology. 178(6). 993–1004. 25 indexed citations
19.
Orsini, Nicola, Ruifeng Li, Alicja Wolk, Polyna Khudyakov, & Donna Spiegelman. (2011). Meta-Analysis for Linear and Nonlinear Dose-Response Relations: Examples, an Evaluation of Approximations, and Software. American Journal of Epidemiology. 175(1). 66–73. 1065 indexed citations breakdown →
20.
Khudyakov, Polyna, Malka Gorfine, & Paul D. Feigin. (2010). Test for Equality of Baseline Hazard Functions for Correlated Survival Data using Frailty Models. 4 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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