Stephen Laderman

1.1k citations
4 papers · 809 · h-index 4

Impact in

  • Genetics top 5%
    • Genomic variations and chromosomal abnormalities
    • Genomics and Rare Diseases
    • Cancer Genomics and Diagnostics

Papers in

    • Genomic variations and chromosomal abnormalities 3
    • Genomics and Rare Diseases 2
    • Genetic Associations and Epidemiology 1
    • Gene expression and cancer classification 1
    • CRISPR and Genetic Engineering 1
    • RNA Research and Splicing 1
    • RNA and protein synthesis mechanisms 1

Stephen Laderman

4 papers receiving 787 citations

Peers

Stephen Laderman
Comparison fields: 5 of 64
  • Genetics 512
  • Cancer Research 80
  • Pediatrics, Perinatology and Child Health 99
  • Molecular Biology 382
  • Plant Science 175
Replace D. C. Burford with:
D. C. Burford United Kingdom
A. Behmel Austria
Christa M. Lese United States
Jiangzhen Li United States
Andrea Corsinotti Switzerland
Jörg Seidel Germany
James Tepperberg United States
Patricia Emmerich Germany
Judith Dagan Israel
Helen Heath Netherlands
Stephen Laderman relative to D. C. Burford United Kingdom D. C. Burford's profile →
Citations per field
00.5×10×
D. C. Burford · 1×
Citations per year

Countries citing papers authored by Stephen Laderman

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Laderman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stephen Laderman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stephen Laderman Line = papers co-authored together Stephen Laderman links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown

About Stephen Laderman

Stephen Laderman is a scholar working on Genetics, Molecular Biology, Plant Science, Infectious Diseases and Organic Chemistry, having authored 4 papers that have together received 809 indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (3 papers), Genomics and Rare Diseases (2 papers), Chromosomal and Genetic Variations (2 papers), Gene expression and cancer classification (1 paper), CRISPR and Genetic Engineering (1 paper), Genetic Associations and Epidemiology (1 paper), RNA Research and Splicing (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Genetics (512 citations), Cancer Research (80 citations), Pediatrics, Perinatology and Child Health (99 citations), Molecular Biology (382 citations) and Plant Science (175 citations). Stephen Laderman has collaborated with scholars based in United States, France and South Korea. Frequent co-authors include Laurakay Bruhn, Amir Ben‐Dor, Peter Tsang, Nick Sampas, Zohar Yakhini, N. Alice Yamada, Anya Tsalenko, Robert Kincaid, Kristin Baird and Doron Lipson. Their work appears in journals such as Proceedings of the National Academy of Sciences, Human Molecular Genetics and The American Journal of Human Genetics.

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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