Anukriti Mathur

936 total citations
9 papers, 583 citations indexed

About

Anukriti Mathur is a scholar working on Molecular Biology, Nephrology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Anukriti Mathur has authored 9 papers receiving a total of 583 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Nephrology and 2 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Anukriti Mathur's work include Inflammasome and immune disorders (7 papers), Heme Oxygenase-1 and Carbon Monoxide (3 papers) and Streptococcal Infections and Treatments (2 papers). Anukriti Mathur is often cited by papers focused on Inflammasome and immune disorders (7 papers), Heme Oxygenase-1 and Carbon Monoxide (3 papers) and Streptococcal Infections and Treatments (2 papers). Anukriti Mathur collaborates with scholars based in Australia, Germany and United States. Anukriti Mathur's co-authors include Si Ming Man, Jenni A. Hayward, Chinh Ngo, Daniel Enosi Tuipulotu, Gaétan Burgio, Shouya Feng, Avril A. B. Robertson, Daniel Fox, Nadeem O. Kaakoush and Erwin Märtlbauer and has published in prestigious journals such as Nature Communications, PLoS ONE and Microbiology and Molecular Biology Reviews.

In The Last Decade

Anukriti Mathur

9 papers receiving 577 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anukriti Mathur Australia	7	450	158	52	51	50	9	583
Chenlu Zhang China	9	502 1.1×	329 2.1×	32 0.6×	47 0.9×	64 1.3×	10	833
Nura Schürmann Switzerland	6	500 1.1×	267 1.7×	54 1.0×	94 1.8×	48 1.0×	7	926
Lupeng Li United States	11	524 1.2×	300 1.9×	63 1.2×	95 1.9×	44 0.9×	24	777
Meghan A. Wynosky-Dolfi United States	12	646 1.4×	422 2.7×	66 1.3×	70 1.4×	20 0.4×	16	967
Boas Felmy Switzerland	8	331 0.7×	243 1.5×	31 0.6×	126 2.5×	49 1.0×	8	599
Banglao Xu China	16	299 0.7×	57 0.4×	31 0.6×	105 2.1×	59 1.2×	43	711
P. Hima Kumari United States	12	358 0.8×	162 1.0×	31 0.6×	19 0.4×	30 0.6×	23	621
Mena Abdel‐Nour Canada	11	311 0.7×	223 1.4×	30 0.6×	61 1.2×	34 0.7×	12	613
William Singleton Australia	9	322 0.7×	110 0.7×	111 2.1×	25 0.5×	26 0.5×	11	659
Charles V. Rosadini United States	11	323 0.7×	326 2.1×	31 0.6×	39 0.8×	35 0.7×	11	788

Countries citing papers authored by Anukriti Mathur

Since Specialization

Citations

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

Fields of papers citing papers by Anukriti Mathur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anukriti Mathur

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

All Works

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9 of 9 papers shown

Starrs, Lora, et al.. (2024). Interferon signalling and non-canonical inflammasome activation promote host protection against multidrug-resistant Acinetobacter baumannii. Communications Biology. 7(1). 1494–1494. 4 indexed citations

Pandey, Abhimanu, Cheng Shen, Shouya Feng, et al.. (2024). Ku70 senses cytosolic DNA and assembles a tumor-suppressive signalosome. Science Advances. 10(4). eadh3409–eadh3409. 6 indexed citations

Kay, Callum, Shouya Feng, Daniel Enosi Tuipulotu, et al.. (2022). Clostridium septicum α-toxin activates the NLRP3 inflammasome by engaging GPI-anchored proteins. Science Immunology. 7(71). eabm1803–eabm1803. 25 indexed citations

Feng, Shouya, Daniel Enosi Tuipulotu, Abhimanu Pandey, et al.. (2022). Pathogen-selective killing by guanylate-binding proteins as a molecular mechanism leading to inflammasome signaling. Nature Communications. 13(1). 4395–4395. 33 indexed citations

Starrs, Lora, et al.. (2022). Differential activation of NLRP3 inflammasome by Acinetobacter baumannii strains. PLoS ONE. 17(11). e0277019–e0277019. 8 indexed citations

Tuipulotu, Daniel Enosi, Anukriti Mathur, Chinh Ngo, & Si Ming Man. (2020). Bacillus cereus: Epidemiology, Virulence Factors, and Host–Pathogen Interactions. Trends in Microbiology. 29(5). 458–471. 141 indexed citations

Mathur, Anukriti, Shouya Feng, Jenni A. Hayward, et al.. (2018). A multicomponent toxin from Bacillus cereus incites inflammation and shapes host outcome via the NLRP3 inflammasome. Nature Microbiology. 4(2). 362–374. 94 indexed citations

Hayward, Jenni A., Anukriti Mathur, Chinh Ngo, & Si Ming Man. (2018). Cytosolic Recognition of Microbes and Pathogens: Inflammasomes in Action. Microbiology and Molecular Biology Reviews. 82(4). 123 indexed citations

Mathur, Anukriti, Jenni A. Hayward, & Si Ming Man. (2017). Molecular mechanisms of inflammasome signaling. Journal of Leukocyte Biology. 103(2). 233–257. 149 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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