Nikhat Parveen

1.9k total citations
49 papers, 1.5k citations indexed

About

Nikhat Parveen is a scholar working on Parasitology, Infectious Diseases and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Nikhat Parveen has authored 49 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Parasitology, 26 papers in Infectious Diseases and 13 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Nikhat Parveen's work include Vector-borne infectious diseases (33 papers), Viral Infections and Vectors (23 papers) and Vector-Borne Animal Diseases (13 papers). Nikhat Parveen is often cited by papers focused on Vector-borne infectious diseases (33 papers), Viral Infections and Vectors (23 papers) and Vector-Borne Animal Diseases (13 papers). Nikhat Parveen collaborates with scholars based in United States, Peru and France. Nikhat Parveen's co-authors include John M. Leong, Ken Cornell, Lavoisier Akoolo, Loranne Magoun, Vitomir Djokić, Joshua R. Fischer, Kamfai Chan, Douglas R. Robbins, Purnima Bhanot and Salvatore A. E. Marras and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.

In The Last Decade

Nikhat Parveen

47 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nikhat Parveen United States 23 959 676 335 283 267 49 1.5k
Yi‐Pin Lin United States 26 1.2k 1.3× 891 1.3× 214 0.6× 269 1.0× 247 0.9× 69 1.7k
Xiuli Yang United States 32 1.9k 2.0× 1.3k 1.9× 501 1.5× 404 1.4× 379 1.4× 111 2.7k
Roger Pellé Kenya 24 600 0.6× 540 0.8× 606 1.8× 164 0.6× 478 1.8× 92 1.7k
Naotoshi Tsuji Japan 26 1.2k 1.3× 492 0.7× 358 1.1× 332 1.2× 472 1.8× 98 1.9k
Nathalie Boulanger France 20 729 0.8× 547 0.8× 271 0.8× 282 1.0× 159 0.6× 61 1.3k
Dawn R. Clifton United States 13 442 0.5× 353 0.5× 146 0.4× 237 0.8× 183 0.7× 13 1.0k
Naotoshi Tsuji Japan 24 869 0.9× 239 0.4× 111 0.3× 252 0.9× 406 1.5× 68 1.6k
Ana Oleaga Spain 28 1.5k 1.6× 538 0.8× 456 1.4× 211 0.7× 293 1.1× 81 2.2k
Dongmi Kwak South Korea 21 1.1k 1.1× 744 1.1× 429 1.3× 90 0.3× 172 0.6× 168 1.5k
Ik-Sang Kim South Korea 22 941 1.0× 508 0.8× 165 0.5× 244 0.9× 225 0.8× 31 1.3k

Countries citing papers authored by Nikhat Parveen

Since Specialization
Citations

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

Fields of papers citing papers by Nikhat Parveen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nikhat Parveen

This figure shows the co-authorship network connecting the top 25 collaborators of Nikhat Parveen. A scholar is included among the top collaborators of Nikhat Parveen 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 Nikhat Parveen. Nikhat Parveen 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.
Moustafa, Mohamed Abdallah Mohamed, et al.. (2025). Long-term survival of Babesia microti and Borrelia burgdorferi in C3H/HeJ mice and their effect on Lyme arthritis and babesiosis manifestations. Microbiology Spectrum. 13(9). e0025225–e0025225.
2.
Parveen, Nikhat, et al.. (2024). Current and emerging approaches for eliminating Borrelia burgdorferi and alleviating persistent Lyme disease symptoms. Frontiers in Microbiology. 15. 1459202–1459202. 3 indexed citations
3.
Moustafa, Mohamed Abdallah Mohamed, et al.. (2023). Borrelia burgdorferi colonizes the mammary glands of lactating C3H mice: does not cause congenital Lyme disease. Microbes and Infection. 26(1-2). 105241–105241. 1 indexed citations
4.
Parveen, Nikhat, et al.. (2022). Transmission Cycle of Tick-Borne Infections and Co-Infections, Animal Models and Diseases. Pathogens. 11(11). 1309–1309. 27 indexed citations
5.
Djokić, Vitomir, et al.. (2021). Lessons Learned for Pathogenesis, Immunology, and Disease of Erythrocytic Parasites: Plasmodium and Babesia. Frontiers in Cellular and Infection Microbiology. 11. 685239–685239. 20 indexed citations
6.
Cornell, Ken, et al.. (2020). Evaluation of Nucleoside Analogs as Antimicrobials Targeting Unique Enzymes in Borrelia burgdorferi. Pathogens. 9(9). 678–678. 6 indexed citations
7.
Giacani, Lorenzo, et al.. (2020). Identification and Functional Assessment of the First Placental Adhesin of Treponema pallidum That May Play Critical Role in Congenital Syphilis. Frontiers in Microbiology. 11. 621654–621654. 15 indexed citations
8.
Ehret‐Sabatier, Laurence, C. Lenormand, Cathy Barthel, et al.. (2020). Effects of topical corticosteroids and lidocaine on Borrelia burgdorferi sensu lato in mouse skin: potential impact to human clinical trials. Scientific Reports. 10(1). 10552–10552. 7 indexed citations
9.
10.
Cornell, Ken, Reece J. Knippel, Kristen A. Mitchell, et al.. (2019). Characterization of 5′-methylthioadenosine/S-adenosylhomocysteine nucleosidases from Borrelia burgdorferi: Antibiotic targets for Lyme disease. Biochimica et Biophysica Acta (BBA) - General Subjects. 1864(1). 129455–129455. 9 indexed citations
11.
Djokić, Vitomir, et al.. (2019). Protozoan Parasite Babesia microti Subverts Adaptive Immunity and Enhances Lyme Disease Severity. Frontiers in Microbiology. 10. 1596–1596. 28 indexed citations
12.
13.
Bhanot, Purnima & Nikhat Parveen. (2018). Investigating disease severity in an animal model of concurrent babesiosis and Lyme disease. International Journal for Parasitology. 49(2). 145–151. 23 indexed citations
14.
Akoolo, Lavoisier, et al.. (2018). Efficient detection of symptomatic and asymptomatic patient samples for Babesia microti and Borrelia burgdorferi infection by multiplex qPCR. PLoS ONE. 13(5). e0196748–e0196748. 23 indexed citations
15.
16.
Parveen, Nikhat & Ken Cornell. (2010). Methylthioadenosine/S‐adenosylhomocysteine nucleosidase, a critical enzyme for bacterial metabolism. Molecular Microbiology. 79(1). 7–20. 213 indexed citations
17.
Marras, Salvatore A. E., et al.. (2009). Detection and quantification of Lyme spirochetes using sensitive and specific molecular beacon probes. BMC Microbiology. 9(1). 43–43. 17 indexed citations
18.
Cornell, Ken, et al.. (2009). Assessment of methylthioadenosine/S-adenosylhomocysteine nucleosidases of Borrelia burgdorferi as targets for novel antimicrobials using a novel high-throughput method. Journal of Antimicrobial Chemotherapy. 63(6). 1163–1172. 25 indexed citations
19.
Parveen, Nikhat, Melissa J. Caimano, Justin D. Radolf, & John M. Leong. (2003). Adaptation of the Lyme disease spirochaete to the mammalian host environment results in enhanced glycosaminoglycan and host cell binding. Molecular Microbiology. 47(5). 1433–1444. 71 indexed citations
20.
Parveen, Nikhat & Dulal Borthakur. (1994). Construction of a single-transposon-insertion mutant in Rhizobium sp. strain TAL1145 from a double-insertion mutant. Letters in Applied Microbiology. 19(3). 142–145. 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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