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.
Countries citing papers authored by Yaron S. Rabinowitz
Since
Specialization
Citations
This map shows the geographic impact of Yaron S. Rabinowitz'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 Yaron S. Rabinowitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaron S. Rabinowitz more than expected).
Fields of papers citing papers by Yaron S. Rabinowitz
This network shows the impact of papers produced by Yaron S. Rabinowitz. 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 Yaron S. Rabinowitz. The network helps show where Yaron S. Rabinowitz may publish in the future.
Co-authorship network of co-authors of Yaron S. Rabinowitz
This figure shows the co-authorship network connecting the top 25 collaborators of Yaron S. Rabinowitz.
A scholar is included among the top collaborators of Yaron S. Rabinowitz 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 Yaron S. Rabinowitz. Yaron S. Rabinowitz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ornelas, Loren, Yelena Bykhovskaya, Dhruv Sareen, & Yaron S. Rabinowitz. (2014). Derivation and Characterization of Human Induced Pluripotent Stem Cells from Stromal Keratocytes of Patients with Keratoconus. Investigative Ophthalmology & Visual Science. 55(13). 4201–4201.2 indexed citations
5.
Liu, Yutao, Khaled K. Abu‐Amero, Yelena Bykhovskaya, et al.. (2014). Genomic Deletions of RXRA-COL5A1, FAM46A-IBTK, HS3ST3B1-PMP22, and GRIA4 in Familial Keratoconus Patients. Investigative Ophthalmology & Visual Science. 55(13). 2986–2986.1 indexed citations
6.
Canedo, Ana Laura, Ronald N. Gaster, & Yaron S. Rabinowitz. (2013). Comparison of Laser-Assisted Removal of Epithelium to Mechanical Debridement in Corneal Cross-Linking for Progressive Keratoconus: 12-Months Results. Investigative Ophthalmology & Visual Science. 54(15). 3112–3112.1 indexed citations
Li, Xiaohui, Yelena Bykhovskaya, Talin Haritunians, et al.. (2011). Several Susceptible Regions Are Associated With Keratoconus Using Genome-wide Association And Confirmation Panels. Investigative Ophthalmology & Visual Science. 52(14). 4385–4385.1 indexed citations
Rabinowitz, Yaron S., et al.. (2009). A Case of Keratoconus in 3 Siblings From Different Mothers but the Same Father. Investigative Ophthalmology & Visual Science. 50(13). 3546–3546.1 indexed citations
Tang, Yun, et al.. (2006). VSX1 Gene: Three Single Nucleotide Polymorphisms (L159M, R166W and H244R) Are Not Associated With Keratoconus. Investigative Ophthalmology & Visual Science. 47(13). 5555–5555.1 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.