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.
Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis
2020494 citationsAshish Kumar, Anil Arora et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Anil Arora'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 Anil Arora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anil Arora more than expected).
This network shows the impact of papers produced by Anil Arora. 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 Anil Arora. The network helps show where Anil Arora may publish in the future.
Co-authorship network of co-authors of Anil Arora
This figure shows the co-authorship network connecting the top 25 collaborators of Anil Arora.
A scholar is included among the top collaborators of Anil Arora 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 Anil Arora. Anil Arora 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.
Parikh, Purvish M., Anil Arora, Mandhir Kumar, et al.. (2024). Familial Polyposis and Colon Cancer. SHILAP Revista de lepidopterología. 13(4). 305–308.
Chandra, Mudit, et al.. (2017). Prevalence of mastitis causing organism and their antibiotic resistance pattern in dairy farms. Indian Journal of Dairy Science. 70(5).3 indexed citations
Arora, Anil, et al.. (2013). Isolation, biotyping and antibiogram evaluation of Brucella abortus in cattle and buffaloes from Punjab (India). Applied Biological Research. 15(1). 27–31.
14.
Arora, Anil, et al.. (2010). Response of intrauterine infusion of Lugol's iodine in infectious repeat breeding cattle.. 31(2). 40–42.2 indexed citations
15.
Pant, B. D., et al.. (2007). Fabrication of MEMS composite-polymer gas sensor arrays for electronic nose. Indian Journal of Pure & Applied Physics. 45(4). 321–325.4 indexed citations
16.
Kumar, Mahesh, et al.. (2007). Deposition of low stress polysilicon thin films using low-pressure chemical vapour deposition. Indian Journal of Pure & Applied Physics. 45(4). 400–402.1 indexed citations
17.
Arora, Anil, et al.. (2007). Outer membrane protein profiles of Pasteurella multocida isolates of bovine origin. The Indian Journal of Animal Sciences. 77(8).1 indexed citations
18.
Dhaliwal, G. S., et al.. (2001). Dynamics of uterine microflora in cows suffering from endometritis following intrauterine administration of Escherichia coli lipopolysaccharide. The Indian Journal of Animal Sciences. 71(12). 1156–1158.1 indexed citations
19.
Arora, Anil, et al.. (1998). Bacteriological studies on the genital tract infections in repeat breeding thoroughbred mares. The Indian Journal of Animal Sciences. 68(1). 58–59.1 indexed citations
20.
Arora, Anil, D. N. Tripathy, A. H. Killinger, & William G. Myers. (1980). Characterization and appearance of immunoglobulins in bovine lacrimal secretions.. 3(2). 123–130.1 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.