Ramya Nandakumar

1.1k total citations
8 papers, 655 citations indexed

About

Ramya Nandakumar is a scholar working on Immunology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Ramya Nandakumar has authored 8 papers receiving a total of 655 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Immunology, 4 papers in Infectious Diseases and 3 papers in Epidemiology. Recurrent topics in Ramya Nandakumar's work include interferon and immune responses (6 papers), Viral Infections and Vectors (4 papers) and Immune Response and Inflammation (2 papers). Ramya Nandakumar is often cited by papers focused on interferon and immune responses (6 papers), Viral Infections and Vectors (4 papers) and Immune Response and Inflammation (2 papers). Ramya Nandakumar collaborates with scholars based in Germany, Denmark and Austria. Ramya Nandakumar's co-authors include Søren R. Paludan, Martin K. Thomsen, Line S. Reinert, Katherine A. Fitzgerald, Katarína Lopušná, Morten Meyer, Christian Bjerggaard Vægter, Jens Randel Nyengaard, Chenglong Sun and Trine H. Mogensen and has published in prestigious journals such as Nature Communications, Gastroenterology and Hepatology.

In The Last Decade

Ramya Nandakumar

8 papers receiving 652 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ramya Nandakumar Germany	7	459	291	180	177	80	8	655
Christina Ochsenbauer United States	2	408 0.9×	318 1.1×	192 1.1×	135 0.8×	26 0.3×	2	845
Nicolas Ruffin Sweden	16	396 0.9×	218 0.7×	143 0.8×	130 0.7×	68 0.8×	33	803
Anneline Nansen Denmark	19	690 1.5×	126 0.4×	198 1.1×	148 0.8×	83 1.0×	29	962
Jean Marc Jacqué United States	9	442 1.0×	247 0.8×	179 1.0×	256 1.4×	29 0.4×	9	889
Albert C. Huang United States	5	338 0.7×	198 0.7×	77 0.4×	84 0.5×	67 0.8×	6	579
Joschka Willemsen Germany	10	444 1.0×	318 1.1×	122 0.7×	109 0.6×	23 0.3×	13	615
Elena Grabski Germany	10	277 0.6×	117 0.4×	139 0.8×	101 0.6×	41 0.5×	14	425
Jaime L. Wetzel United States	7	347 0.8×	213 0.7×	100 0.6×	112 0.6×	32 0.4×	7	501
Katja Blume Germany	10	254 0.6×	265 0.9×	66 0.4×	136 0.8×	36 0.5×	11	575
Gabriele Blahnik United States	8	342 0.7×	157 0.5×	62 0.3×	179 1.0×	176 2.2×	10	601

Countries citing papers authored by Ramya Nandakumar

Since Specialization

Citations

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

Fields of papers citing papers by Ramya Nandakumar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ramya Nandakumar

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

All Works

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8 of 8 papers shown

1.

Prabakaran, Thaneas, Anne Troldborg, Emilija Marinković, et al.. (2021). A STING antagonist modulating the interaction with STIM1 blocks ER-to-Golgi trafficking and inhibits lupus pathology. EBioMedicine. 66. 103314–103314. 58 indexed citations

2.

Nandakumar, Ramya, Roland Tschismarov, Felix Meissner, et al.. (2019). Intracellular bacteria engage a STING–TBK1–MVB12b pathway to enable paracrine cGAS–STING signalling. Nature Microbiology. 4(4). 701–713. 97 indexed citations

3.

Nandakumar, Ramya, et al.. (2019). Intercellular communication in the innate immune system through the cGAS-STING pathway. Methods in enzymology on CD-ROM/Methods in enzymology. 625. 1–11. 5 indexed citations

4.

Reinert, Line S., Katarína Lopušná, Chenglong Sun, et al.. (2016). Sensing of HSV-1 by the cGAS–STING pathway in microglia orchestrates antiviral defence in the CNS. Nature Communications. 7(1). 13348–13348. 280 indexed citations

5.

Thomsen, Martin K., Ramya Nandakumar, Daniela Stadler, et al.. (2016). Lack of immunological DNA sensing in hepatocytes facilitates hepatitis B virus infection. Hepatology. 64(3). 746–759. 150 indexed citations

6.

Nandakumar, Ramya, Katja Finsterbusch, Christoph Lipps, et al.. (2013). Hepatitis C Virus Replication in Mouse Cells Is Restricted by IFN-Dependent and -Independent Mechanisms. Gastroenterology. 145(6). 1414–1423.e1. 30 indexed citations

7.

Kaur, Gurvinder, Neeraj Kumar, Ramya Nandakumar, et al.. (2012). Utility of saliva and hair follicles in donor selection for hematopoietic stem cell transplantation and chimerism monitoring. PubMed. 3(1). 9–17. 9 indexed citations

8.

Nandakumar, Ramya, Katja Finsterbusch, Rainer Zawatzky, et al.. (2011). IRF-1 Expression Is Essential for Natural Killer Cells to Suppress Metastasis. Cancer Research. 71(20). 6410–6418. 26 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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