Moran Gal

832 citations
9 papers · 439 · h-index 7

Impact in

  • Genetics top 10%
    • BRCA gene mutations in cancer
    • Genomics and Rare Diseases
    • Genomic variations and chromosomal abnormalities
    • Cancer Genomics and Diagnostics

Papers in

    • CRISPR and Genetic Engineering 1
    • Ion channel regulation and function 1
    • Wnt/β-catenin signaling in development and cancer 1

Moran Gal

9 papers receiving 435 citations

Peers

Moran Gal
Comparison fields: 5 of 62
  • Genetics 251
  • Cancer Research 73
  • Reproductive Medicine 36
  • Molecular Biology 188
  • Pediatrics, Perinatology and Child Health 50
Replace Ruen Yao with:
Ruen Yao China
Yael Laitman Israel
J. Couturier France
Gayle Patel United States
Angelo Molinaro Italy
Bartłomiej Budny Poland
Ender Karaca Türkiye
Sutapa Banerjee United States
Diane Allingham‐Hawkins Canada
A. Kuechler Germany
Moran Gal relative to Ruen Yao China Ruen Yao's profile →
Citations per field
00.5×3.3×
Ruen Yao · 1×
Citations per year

Countries citing papers authored by Moran Gal

Since Specialization
Citations

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

Fields of papers citing papers by Moran Gal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Moran Gal, 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 Moran Gal Line = papers co-authored together Moran Gal links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2014234
2 201851
3 201143
4 200342
5 201625
6 201620
7 201419
8 20163
9 20162

About Moran Gal

Moran Gal is a scholar working on Genetics, Molecular Biology, Pediatrics, Perinatology and Child Health, Surgery and Pharmacology, having authored 9 papers that have together received 439 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (1 paper), Ion channel regulation and function (1 paper), Cholinesterase and Neurodegenerative Diseases (1 paper), Alzheimer's disease research and treatments (1 paper), Cystic Fibrosis Research Advances (1 paper), Gestational Diabetes Research and Management (1 paper), Wnt/β-catenin signaling in development and cancer (1 paper) and Inflammatory Biomarkers in Disease Prognosis (1 paper). The work is most often cited by research in Genetics (251 citations), Cancer Research (73 citations), Reproductive Medicine (36 citations), Molecular Biology (188 citations) and Pediatrics, Perinatology and Child Health (50 citations). Moran Gal has collaborated with scholars based in Israel, Switzerland and Canada. Frequent co-authors include Paul Renbaum, Rachel Beeri, Ephrat Levy‐Lahad, Shlomo Segev, Jessica B. Mandell, Raphael Catane, Ming K. Lee, Uziel Beller, Mary‐Claire King and Amnon Lahad. Their work appears in journals such as BMC Medical Genomics, Gene, Cell Research, American Journal of Perinatology and European Journal of Medical 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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