Arjun P. Athreya

1.1k total citations
67 papers, 634 citations indexed

About

Arjun P. Athreya is a scholar working on Pharmacology, Molecular Biology and Clinical Psychology. According to data from OpenAlex, Arjun P. Athreya has authored 67 papers receiving a total of 634 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Pharmacology, 12 papers in Molecular Biology and 12 papers in Clinical Psychology. Recurrent topics in Arjun P. Athreya's work include Mental Health Research Topics (10 papers), Treatment of Major Depression (10 papers) and Tryptophan and brain disorders (9 papers). Arjun P. Athreya is often cited by papers focused on Mental Health Research Topics (10 papers), Treatment of Major Depression (10 papers) and Tryptophan and brain disorders (9 papers). Arjun P. Athreya collaborates with scholars based in United States, Singapore and United Kingdom. Arjun P. Athreya's co-authors include Patrick Tague, Richard M. Weinshilboum, William V. Bobo, Liewei Wang, Paul E. Croarkin, Ravishankar K. Iyer, Mark A. Frye, A. John Rush, Drew Neavin and Michelle Skime and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and Hepatology.

In The Last Decade

Arjun P. Athreya

57 papers receiving 620 citations

Peers

Arjun P. Athreya
Hans Mulder Netherlands
Sam Miller United Kingdom
Ling Liu China
Muhammad Siddiqi United States
Andraž Stožer Slovenia
David Herbert Australia
Sang Hyun Kim South Korea
Majaz Moonis United States
Jen‐Yeu Chen Taiwan
Hans Mulder Netherlands
Arjun P. Athreya
Citations per year, relative to Arjun P. Athreya Arjun P. Athreya (= 1×) peers Hans Mulder

Countries citing papers authored by Arjun P. Athreya

Since Specialization
Citations

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

Fields of papers citing papers by Arjun P. Athreya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arjun P. Athreya. 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 Arjun P. Athreya. The network helps show where Arjun P. Athreya may publish in the future.

Co-authorship network of co-authors of Arjun P. Athreya

This figure shows the co-authorship network connecting the top 25 collaborators of Arjun P. Athreya. A scholar is included among the top collaborators of Arjun P. Athreya 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 Arjun P. Athreya. Arjun P. Athreya 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.
Lazaridis, Konstantinos N., Eric W. Klee, Timothy B. Curry, et al.. (2025). Individualized Medicine in the Era of Artificial Intelligence. Mayo Clinic Proceedings. 100(11). 1965–1975.
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Barreto, Erin F., Jack Chang, Andrew D. Rule, et al.. (2025). Piperacillin/tazobactam clearance predicted by non-creatinine based estimates of GFR in critically ill adults. International Journal of Antimicrobial Agents. 66(5). 107586–107586.
4.
Curtis, Susan, et al.. (2025). Physician Perspectives on the Potential Benefits and Risks of Applying Artificial Intelligence in Psychiatric Medicine: Qualitative Study. JMIR Mental Health. 12. e64414–e64414. 9 indexed citations
5.
Comba, Işın Y., Ruben A. Mars, Lu Yang, et al.. (2024). 309 THE BASELINE GUT MICROBIOME OFFERS INSIGHTS INTO PREDICTING AND UNDERSTANDING THE HETEROGENEOUS NATURE OF LONG COVID. Gastroenterology. 166(5). S–66. 1 indexed citations
6.
Hassett, Leslie C., Paul E. Croarkin, Mohit Chauhan, et al.. (2024). Wearable Technologies for Detecting Burnout and Well-Being in Health Care Professionals: Scoping Review. Journal of Medical Internet Research. 26. e50253–e50253. 12 indexed citations
7.
Barry, Barbara, Karsten Krüger, Richard D. White, et al.. (2024). Pharmacogenomic augmented machine learning in electronic health record alerts: A health system‐wide usability survey of clinicians. Clinical and Translational Science. 17(10). e70044–e70044. 2 indexed citations
8.
Bobo, William V., Katherine M. Moore, Hannah K. Betcher, et al.. (2024). The Association of Antidepressants in Late Pregnancy with Postpartum Hemorrhage: Systematic Review of Controlled Observational Studies. Journal of Child and Adolescent Psychopharmacology. 34(10). 428–446.
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Juran, Brian D., Ahmad H. Ali, Erik M. Schlicht, et al.. (2023). Environmental chemicals and endogenous metabolites in bile of USA and Norway patients with primary sclerosing cholangitis. PubMed. 3(1). osac011–osac011. 2 indexed citations
12.
Conte, Gian Marco, et al.. (2023). In Situ Physiologic and Behavioral Monitoring With Digital Sensors for Cerebrovascular Disease: A Scoping Review. SHILAP Revista de lepidopterología. 1(2). 139–160. 4 indexed citations
13.
Romanowicz, Magdalena, Michelle Skime, Paul E. Croarkin, et al.. (2023). Machine Learning Identifies Smartwatch-Based Physiological Biomarker for Predicting Disruptive Behavior in Children: A Feasibility Study. Journal of Child and Adolescent Psychopharmacology. 33(9). 387–392. 3 indexed citations
14.
Sarangi, Vivekananda, Duan Liu, Ming‐Fen Ho, et al.. (2022). ACE2 and TMPRSS2 SARS-CoV-2 infectivity genes: deep mutational scanning and characterization of missense variants. Human Molecular Genetics. 31(24). 4183–4192. 9 indexed citations
15.
Duong, Stephanie Q., Cynthia S. Crowson, Arjun P. Athreya, et al.. (2022). Clinical predictors of response to methotrexate in patients with rheumatoid arthritis: a machine learning approach using clinical trial data. Arthritis Research & Therapy. 24(1). 162–162. 35 indexed citations
16.
Virani, Sanya, Taryn L. Mayes, Thomas Carmody, et al.. (2022). Toward a Definition of “No Meaningful Benefit” From Antidepressant Treatment. The Journal of Clinical Psychiatry. 83(4). 3 indexed citations
17.
Voort, Jennifer L. Vande, Jeffrey A. Mills, Graham J. Emslie, et al.. (2022). A Characterization of the Clinical Global Impression Scale Thresholds in the Treatment of Adolescent Depression Across Multiple Rating Scales. Journal of Child and Adolescent Psychopharmacology. 32(5). 278–287. 2 indexed citations
18.
Myasoedova, Elena, Arjun P. Athreya, Cynthia S. Crowson, et al.. (2021). Toward Individualized Prediction of Response to Methotrexate in Early Rheumatoid Arthritis: A Pharmacogenomics‐Driven Machine Learning Approach. Arthritis Care & Research. 74(6). 879–888. 33 indexed citations
19.
Athreya, Arjun P. & Konstantinos N. Lazaridis. (2021). Discovery and Opportunities With Integrative Analytics Using Multiple‐Omics Data. Hepatology. 74(2). 1081–1087. 4 indexed citations
20.
Sonmez, Ayse Irem, Charles P. Lewis, John D. Port, et al.. (2021). A pilot spectroscopy study of adversity in adolescents. SHILAP Revista de lepidopterología. 5. 100043–100043. 3 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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