Niyanta Kumar

535 total citations
10 papers, 374 citations indexed

About

Niyanta Kumar is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Niyanta Kumar has authored 10 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Neurology and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Niyanta Kumar's work include Barrier Structure and Function Studies (3 papers), Advanced Drug Delivery Systems (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). Niyanta Kumar is often cited by papers focused on Barrier Structure and Function Studies (3 papers), Advanced Drug Delivery Systems (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). Niyanta Kumar collaborates with scholars based in United States, Germany and United Kingdom. Niyanta Kumar's co-authors include Robert G. Thorne, Michelle E. Pizzo, Danica Stanimirovic, Christina L. Brunnquell, Lydia Sorokin, Eric Brunette, N. Joan Abbott, M. Elizabeth Meyerand, Jeffrey J. Lochhead and Melanie‐Jane Hannocks and has published in prestigious journals such as The Journal of Physiology, Cancer Research and Scientific Reports.

In The Last Decade

Niyanta Kumar

9 papers receiving 373 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Niyanta Kumar United States 5 165 98 93 68 56 10 374
Andreas von Ameln-Mayerhofer Germany 10 268 1.6× 212 2.2× 96 1.0× 97 1.4× 49 0.9× 15 666
Alemeh Zamani Czechia 6 107 0.6× 85 0.9× 87 0.9× 101 1.5× 27 0.5× 9 346
Cathleen V. Allen United States 6 114 0.7× 79 0.8× 77 0.8× 30 0.4× 32 0.6× 9 345
Ryan G. Soderquist United States 7 173 1.0× 86 0.9× 46 0.5× 40 0.6× 28 0.5× 7 379
Hongmei Meng China 15 101 0.6× 121 1.2× 54 0.6× 37 0.5× 165 2.9× 33 501
Marc‐André Bellavance Canada 8 72 0.4× 123 1.3× 39 0.4× 259 3.8× 23 0.4× 9 534
Linda Franic United States 6 176 1.1× 157 1.6× 55 0.6× 172 2.5× 102 1.8× 10 546
Ilana Agranovich Russia 10 159 1.0× 88 0.9× 53 0.6× 29 0.4× 7 0.1× 29 352
Amirah E.-E. Aly United States 10 133 0.8× 166 1.7× 58 0.6× 29 0.4× 6 0.1× 14 288
Lixiong Gao China 14 100 0.6× 307 3.1× 15 0.2× 99 1.5× 29 0.5× 32 549

Countries citing papers authored by Niyanta Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Niyanta Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niyanta Kumar

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

All Works

10 of 10 papers shown
1.
Kumar, Niyanta, Vaishali Dixit, Howard Burt, et al.. (2025). PBPK Modeling to Predict Clinical Drug–Drug Interaction and Impact of Hepatic Impairment for an ADC With the Payload Auristatin F‐Hydroxypropylamide. CPT Pharmacometrics & Systems Pharmacology. 14(10). 1661–1672.
2.
Collins, Scott D., Natalie Keirstead, Marc Damelin, et al.. (2024). Abstract 5810: The impact of scaffold, linker, homogeneity and payload selection on the efficacy and tolerability of anti-tubulin ADCs. Cancer Research. 84(6_Supplement). 5810–5810. 1 indexed citations
3.
Bardehle, Sophia, Choya Yoon, Niyanta Kumar, et al.. (2023). Microglial roles in Alzheimer's disease: An agent‐based model to elucidate microglial spatiotemporal response to beta‐amyloid. CPT Pharmacometrics & Systems Pharmacology. 13(3). 449–463. 4 indexed citations
4.
Kumar, Niyanta, Jindřich Soukup, Tomoko Freshwater, et al.. (2022). High-Resolution Ex Vivo Tissue Clearing, Lightsheet Imaging, and Data Analysis to Support Macromolecular Drug and Biomarker Distribution in Whole Organs and Tumors. Microscopy and Microanalysis. 28(S1). 1436–1437. 1 indexed citations
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Kumar, Niyanta, et al.. (2018). Passive Immunotherapies for Central Nervous System Disorders: Current Delivery Challenges and New Approaches. Bioconjugate Chemistry. 29(12). 3937–3966. 23 indexed citations
8.
Cheloha, Ross W., Bingming Chen, Niyanta Kumar, et al.. (2017). Development of Potent, Protease-Resistant Agonists of the Parathyroid Hormone Receptor with Broad β Residue Distribution. Journal of Medicinal Chemistry. 60(21). 8816–8833. 19 indexed citations
9.
Pizzo, Michelle E., Niyanta Kumar, Eric Brunette, et al.. (2017). Intrathecal antibody distribution in the rat brain: surface diffusion, perivascular transport and osmotic enhancement of delivery. The Journal of Physiology. 596(3). 445–475. 202 indexed citations
10.

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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2026