Eva Sujansky

3.0k citations
30 papers · 2.0k indexed · 1 hit paper · h-index 19
Topics
Genomic variations and chromosomal abnormalities (10 papers)Prenatal Screening and Diagnostics (7 papers)Chromosomal and Genetic Variations (5 papers)

In The Last Decade

Eva Sujansky

30 papers receiving 1.9k citations

Hit Papers

Chromosomal Imbalance in the Aniridia-Wilms' Tumor Associ...19782026199420101978100200300400500

Peers

Eva Sujansky
Comparison fields: 5 of 81
  • Molecular Biology 969
  • Genetics 781
  • Surgery 447
  • Pediatrics, Perinatology and Child Health 342
  • Pathology and Forensic Medicine 269
Replace R. Neil Schimke with:
R. Neil Schimke United States
Boris G. Kousseff United States
Helga Rehder Germany
R Rappaport France
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Eberhard Passarge Germany
Lester Weiss United States
Jean‐Pierre Fryns Belgium
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Citations per field
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Citations per year

Countries citing papers authored by Eva Sujansky

Since Specialization
Citations

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

Fields of papers citing papers by Eva Sujansky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eva Sujansky

This figure shows the co-authorship network connecting the top 25 collaborators of Eva Sujansky. A scholar is included among the top collaborators of Eva Sujansky 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 Eva Sujansky. Eva Sujansky 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
#WorkIndexed citations
1 174
2 2
3 36
4 113
5 149
6 7
7 28
8 25
9 17
10 44
11 4
12 32
13 50
14 162
15 97
16 16
17
Heterogeneity in the trichorhinophalangeal syndromes.
1
18
The familial occurrence of Poland syndrome.
18
19 9
20 16

About Eva Sujansky

Eva Sujansky is a scholar working on Anatomy, Genetics and Developmental Biology, having authored 30 papers that have together received 2.0k indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (10 papers), Prenatal Screening and Diagnostics (7 papers) and Chromosomal and Genetic Variations (5 papers). The work is most often cited by research in Genetics (781 citations), Developmental Biology (44 citations) and Pediatrics, Perinatology and Child Health (342 citations). Eva Sujansky has collaborated with scholars based in United States, Austria and Netherlands. Frequent co-authors include Ann C. M. Smith, Vincent M. Riccardi, Uta Francke, Lorraine Dugoff, Patricia A. Gabow, David E. Goldgar, William J. Kimberling, Judith B. Kenyon, Pamela R. Fain and Jerry N. Thompson. Their work appears in journals such as New England Journal of Medicine, Circulation and Neurology.

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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