Viswanath Devanarayan

10.9k total citations · 2 hit papers
67 papers, 5.2k citations indexed

About

Viswanath Devanarayan is a scholar working on Molecular Biology, Immunology and Physiology. According to data from OpenAlex, Viswanath Devanarayan has authored 67 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 19 papers in Immunology and 17 papers in Physiology. Recurrent topics in Viswanath Devanarayan's work include Biosimilars and Bioanalytical Methods (19 papers), Dementia and Cognitive Impairment Research (14 papers) and Alzheimer's disease research and treatments (12 papers). Viswanath Devanarayan is often cited by papers focused on Biosimilars and Bioanalytical Methods (19 papers), Dementia and Cognitive Impairment Research (14 papers) and Alzheimer's disease research and treatments (12 papers). Viswanath Devanarayan collaborates with scholars based in United States, United Kingdom and Germany. Viswanath Devanarayan's co-authors include Mark L. Heiman, P. Antonio Tataranni, Éric Ravussin, Christian Weyer, Matthias H. Tschöp, Yu Chen Barrett, Daniel A. Llano, Eugen Koren, Gopi Shankar and Linda A. Zuckerman and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Diabetes.

In The Last Decade

Viswanath Devanarayan

64 papers receiving 4.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Circulating Ghrelin Levels Are Decreased in Human Obesity

2001 1.6k citations Viswanath Devanarayan et al. profile →
Fit-for-Purpose Method Development and Validation for Successful Biomarker Measurement

2006 504 citations Jean W. Lee, Viswanath Devanarayan et al. Pharmaceutical Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Viswanath Devanarayan United States	28	1.6k	1.5k	1.4k	1.4k	1.1k	67	5.2k
Susumu Suzuki Japan	43	1.4k 0.9×	1.6k 1.1×	1.2k 0.8×	399 0.3×	385 0.3×	279	6.5k
Rakesh Datta United States	43	694 0.4×	3.4k 2.3×	1.3k 0.9×	1.2k 0.9×	146 0.1×	117	6.0k
Ronald R. Bowsher United States	29	871 0.6×	1.4k 0.9×	500 0.3×	488 0.3×	566 0.5×	95	4.2k
Bing Lam Hong Kong	37	761 0.5×	941 0.6×	3.7k 2.6×	2.0k 1.4×	232 0.2×	77	6.8k
Wolfgang Lieb Germany	44	391 0.3×	1.4k 1.0×	1.2k 0.8×	299 0.2×	370 0.3×	193	6.3k
Yoshikazu Kawakami Japan	45	809 0.5×	1.3k 0.9×	1.6k 1.1×	435 0.3×	198 0.2×	311	6.3k
Simon D Harding United Kingdom	24	701 0.4×	2.9k 2.0×	895 0.6×	270 0.2×	194 0.2×	36	6.9k
Hitoshi Ando Japan	44	1.5k 1.0×	1.8k 1.2×	1.7k 1.2×	917 0.6×	90 0.1×	255	8.1k
Robert J. Konrad United States	47	1.6k 1.0×	2.2k 1.5×	958 0.7×	212 0.1×	304 0.3×	151	6.9k
Domenico Lio Italy	48	2.4k 1.5×	1.8k 1.2×	1.6k 1.1×	129 0.1×	260 0.2×	176	7.3k

Countries citing papers authored by Viswanath Devanarayan

Since Specialization

Citations

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

Fields of papers citing papers by Viswanath Devanarayan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Viswanath Devanarayan

This figure shows the co-authorship network connecting the top 25 collaborators of Viswanath Devanarayan. A scholar is included among the top collaborators of Viswanath Devanarayan 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 Viswanath Devanarayan. Viswanath Devanarayan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Devanarayan, Viswanath, Yuanqing Ye, Lü Tian, et al.. (2025). Predicted natural progression as an Alzheimer's prognostic covariate improves the precision of lecanemab efficacy assessments and clinical trial efficiency. Alzheimer s & Dementia. 21(3). e70045–e70045. 2 indexed citations

Devanarayan, Viswanath, Michael Donohue, Reisa A. Sperling, et al.. (2025). Multimodal prognostic modeling of individual cognitive trajectories to enhance trial efficiency in preclinical Alzheimer's disease. Alzheimer s & Dementia. 21(9). e70702–e70702. 2 indexed citations

Li, Gang, Michelle M. Mielke, James E. Galvin, et al.. (2025). The impact of real-world evidence in implementing and optimizing Alzheimer’s disease care. Med. 6(5). 100695–100695. 1 indexed citations

Devanarayan, Viswanath, T. Doherty, Arnaud Charil, et al.. (2024). Plasma pTau217 predicts continuous brain amyloid levels in preclinical and early Alzheimer's disease. Alzheimer s & Dementia. 20(8). 5617–5628. 21 indexed citations

Devanarayan, Viswanath, Daniel A. Llano, Yan Hu, et al.. (2024). Plasma pTau181 enhances the prediction of future clinical decline in amyloid‐positive mild cognitive impairment. Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring. 16(3). e12621–e12621. 3 indexed citations

Li, Gang, Nicola Toschi, Viswanath Devanarayan, et al.. (2023). The age-specific comorbidity burden of mild cognitive impairment: a US claims database study. Alzheimer s Research & Therapy. 15(1). 211–211. 11 indexed citations

Tian, Lü, et al.. (2023). Improving the Robustness of Variable Selection and Predictive Performance of Regularized Generalized Linear Models and Cox Proportional Hazard Models. Mathematics. 11(3). 557–557. 5 indexed citations

Llano, Daniel A., et al.. (2022). CSF peptides from VGF and other markers enhance prediction of MCI to AD progression using the ATN framework. Neurobiology of Aging. 121. 15–27. 11 indexed citations

Hassanein, Mohamed, Michael A. Partridge, Vibha Jawa, et al.. (2022). Comparison of Titer and Signal to Noise (S/N) for Determination of Anti-drug Antibody Magnitude Using Clinical Data from an Industry Consortium. The AAPS Journal. 24(4). 81–81. 17 indexed citations

10.

Llano, Daniel A., et al.. (2021). Reported Hearing Loss in Alzheimer’s Disease Is Associated With Loss of Brainstem and Cerebellar Volume. Frontiers in Human Neuroscience. 15. 739754–739754. 11 indexed citations

11.

Llano, Daniel A., et al.. (2019). VGF in Cerebrospinal Fluid Combined With Conventional Biomarkers Enhances Prediction of Conversion From MCI to AD. Alzheimer Disease & Associated Disorders. 33(4). 307–314. 27 indexed citations

12.

Myler, Heather, Boris Gorovits, Viswanath Devanarayan, et al.. (2019). Report on the AAPS Immunogenicity Guidance Forum. The AAPS Journal. 21(4). 55–55. 14 indexed citations

13.

Jani, Darshana, John Allinson, Flora Berisha, et al.. (2015). Recommendations for Use and Fit-for-Purpose Validation of Biomarker Multiplex Ligand Binding Assays in Drug Development. The AAPS Journal. 18(1). 1–14. 54 indexed citations

14.

Llano, Daniel A., Viswanath Devanarayan, & Adam J. Simon. (2012). Evaluation of Plasma Proteomic Data for Alzheimer Disease State Classification and for the Prediction of Progression From Mild Cognitive Impairment to Alzheimer Disease. Alzheimer Disease & Associated Disorders. 27(3). 233–243. 58 indexed citations

15.

Öhrfelt, Annika, Ulf Andréasson, Adam J. Simon, et al.. (2011). Screening for New Biomarkers for Subcortical Vascular Dementia and Alzheimer’s Disease. Dementia and Geriatric Cognitive Disorders Extra. 1(1). 31–42. 32 indexed citations

16.

Zhang, Ke, et al.. (2011). A hidden Markov model-based algorithm for identifying tumour subtype using array CGH data. BMC Genomics. 12(Suppl 5). S10–S10. 4 indexed citations

17.

Tahir, Stephen K., John Wass, Mary K. Joseph, et al.. (2010). Identification of Expression Signatures Predictive of Sensitivity to the Bcl-2 Family Member Inhibitor ABT-263 in Small Cell Lung Carcinoma and Leukemia/Lymphoma Cell Lines. Molecular Cancer Therapeutics. 9(3). 545–557. 59 indexed citations

18.

Lee, Jean W., Viswanath Devanarayan, Yu Chen Barrett, et al.. (2006). Fit-for-Purpose Method Development and Validation for Successful Biomarker Measurement. Pharmaceutical Research. 23(2). 312–328. 504 indexed citations breakdown →

19.

Ray, Chad, Carmen M. Dumaual, Peter J. O’Brien, et al.. (2005). Optimization of analytical and pre-analytical variables associated with an ex vivo cytokine secretion assay. Journal of Pharmaceutical and Biomedical Analysis. 41(1). 189–195. 13 indexed citations

20.

Ray, Chad, Ronald R. Bowsher, Wendell C. Smith, et al.. (2004). Development, validation, and implementation of a multiplex immunoassay for the simultaneous determination of five cytokines in human serum. Journal of Pharmaceutical and Biomedical Analysis. 36(5). 1037–1044. 110 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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