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.
Complement Factor H Variant Increases the Risk of Age-Related Macular Degeneration
20051.9k citationsJonathan L. Haines, Michael A. Hauser et al.Scienceprofile →
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 Anita Agarwal'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 Anita Agarwal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anita Agarwal more than expected).
This network shows the impact of papers produced by Anita Agarwal. 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 Anita Agarwal. The network helps show where Anita Agarwal may publish in the future.
Co-authorship network of co-authors of Anita Agarwal
This figure shows the co-authorship network connecting the top 25 collaborators of Anita Agarwal.
A scholar is included among the top collaborators of Anita Agarwal 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 Anita Agarwal. Anita Agarwal 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.
Agarwal, Anita, et al.. (2022). Late-onset Stargardt disease. American Journal of Ophthalmology Case Reports. 26. 101429–101429.2 indexed citations
Wang, Gaofeng, William H. Cade, William K. Scott, et al.. (2012). Coding Variants In The ARMS2 Gene And The Risk Of Age-related Macular Degeneration. Investigative Ophthalmology & Visual Science. 53(14). 3311–3311.2 indexed citations
8.
Kovach, Jaclyn L., Anita Agarwal, William H. Cade, et al.. (2011). The Role of Genetics and Smoking in Response to Anti-VEGF Therapy for Wet AMD. Investigative Ophthalmology & Visual Science. 52(14). 5231–5231.2 indexed citations
9.
Agarwal, Anita, et al.. (2010). Antibacterial and antitubercular activities of some diphenyl hydrazones and semicarbazones. Indian Journal of Chemistry Section B-organic Chemistry Including Medicinal Chemistry. 49(10). 1384–1388.7 indexed citations
Olson, Lana M., Paul J. Gallins, William K. Scott, et al.. (2008). C3 R102G Polymorphism Is Associated With Increased Risk of Age-Related Macular Degeneration. Investigative Ophthalmology & Visual Science. 49(13). 2655–2655.1 indexed citations
Haines, Jonathan L., Michael A. Hauser, Silke Schmidt, et al.. (2005). Complement Factor H Variant Increases the Risk of Age-Related Macular Degeneration. Science. 308(5720). 419–421.1898 indexed citations breakdown →
Schmidt, Silke, et al.. (2002). Follow-up of Genomic Screen Regions in Age-Related Macular Degeneration. Investigative Ophthalmology & Visual Science. 43(13). 1846–1846.1 indexed citations
18.
Agarwal, Anita, et al.. (2002). Clinical Characteristics and Correlation of Stage of Disease to Visual Acuity in Type II Idiopathic Juxtafoveal Telangiectasia. Investigative Ophthalmology & Visual Science. 43(13). 511–511.
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.