Maya Donyo

713 citations
9 papers · 490 · h-index 8

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • RNA Research and Splicing
    • RNA modifications and cancer
    • RNA and protein synthesis mechanisms
    • Epigenetics and DNA Methylation
    • Genomics and Chromatin Dynamics

Papers in

    • Signaling Pathways in Disease 4
    • RNA modifications and cancer 3
    • RNA regulation and disease 2
    • RNA Research and Splicing 2
    • RNA and protein synthesis mechanisms 2
    • Hereditary Neurological Disorders 5
    • Axon Guidance and Neuronal Signaling 1

Maya Donyo

9 papers receiving 489 citations

Peers

Maya Donyo
Comparison fields: 5 of 65
  • Cancer Research 98
  • Molecular Biology 368
  • Cellular and Molecular Neuroscience 75
  • Cell Biology 41
  • Neurology 11
Replace Nathalie Escalas with:
Nathalie Escalas France
Violetta Soura United Kingdom
Nader Ezzeddine United States
Malcolm Cook United States
Xianyao Zhou China
Joaquina Farías Uruguay
Florian Beaumatin France
Wei-Hua Wu United States
Vipin T. Sreedharan Germany
Weijin Xu China
Maya Donyo relative to Nathalie Escalas France Nathalie Escalas's profile →
Citations per field
00.5×3.4×
Nathalie Escalas · 1×
Citations per year

Countries citing papers authored by Maya Donyo

Since Specialization
Citations

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

Fields of papers citing papers by Maya Donyo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2012220
2 201994
3 201650
4 201037
5 201329
6 201627
7 201818
8 201611
9 20194

About Maya Donyo

Maya Donyo is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Cell Biology, Endocrinology, Diabetes and Metabolism and Spectroscopy, having authored 9 papers that have together received 490 indexed citations. Recurring topics across this work include Hereditary Neurological Disorders (5 papers), Signaling Pathways in Disease (4 papers), RNA modifications and cancer (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers), RNA regulation and disease (2 papers), RNA Research and Splicing (2 papers), RNA and protein synthesis mechanisms (2 papers) and Axon Guidance and Neuronal Signaling (1 paper). The work is most often cited by research in Cancer Research (98 citations), Molecular Biology (368 citations), Cellular and Molecular Neuroscience (75 citations), Cell Biology (41 citations) and Neurology (11 citations). Maya Donyo has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Dror Hollander, Galit Lev-Maor, Tal Pupko, Gil Ast, Schraga Schwartz, Maayan Amit, Sahar Gelfman, David Burstein, Eddo Kim and Amir Goren. Their work appears in journals such as Human Molecular Genetics, PLoS ONE, Nature Communications, Oncotarget and Cell Reports.

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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