Maya Shelly

2.0k citations
21 papers · 1.6k indexed · h-index 14

Maya Shelly

21 papers receiving 1.6k citations

Peers

Maya Shelly
Comparison fields: 5 of 95
  • Developmental Neuroscience 256
  • Cellular and Molecular Neuroscience 607
  • Cell Biology 319
  • Aging 31
  • Oncology 437
Replace Vladislav V. Kiselyov with:
Vladislav V. Kiselyov Denmark
Jean‐François Cloutier Canada
Ralf S. Schmid United States
Gerald F. Reis United States
Raffaella Scardigli Italy
Anders I. Persson Sweden
Maria A. Morabito United States
Clive Da Costa United Kingdom
Zachary P. Wills United States
Katsuhiro Kato Japan
Maya Shelly relative to Vladislav V. Kiselyov Denmark Vladislav V. Kiselyov's profile →
Citations per field
00.5×5.0×
Vladislav V. Kiselyov · 1×
Citations per year

Countries citing papers authored by Maya Shelly

Since Specialization
Citations

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

Fields of papers citing papers by Maya Shelly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 202317
3 20224
4 20221
5 20225
6 20208
7 201727
8 201615
9 201610
10 201348
11 20124
12 2011171
13 2011126
14 201147
15 2010204
16 2007286
17 200351
18 1998113
19 1998122
20 1996127

About Maya Shelly

Maya Shelly is a scholar working on Developmental Neuroscience, Cellular and Molecular Neuroscience, Aging, Immunology and Allergy and Cell Biology, having authored 21 papers that have together received 1.6k indexed citations. Recurring topics across this work include Axon Guidance and Neuronal Signaling (8 papers), Neuroscience and Neuropharmacology Research (6 papers), Neurogenesis and neuroplasticity mechanisms (6 papers), HER2/EGFR in Cancer Research (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Nerve injury and regeneration (2 papers), Luminescence Properties of Advanced Materials (2 papers) and Cell Adhesion Molecules Research (2 papers). The work is most often cited by research in Developmental Neuroscience (256 citations), Cellular and Molecular Neuroscience (607 citations), Cell Biology (319 citations), Aging (31 citations) and Oncology (437 citations). Maya Shelly has collaborated with scholars based in United States, Israel and Italy. Frequent co-authors include Mu‐ming Poo, Laura Cancedda, Sarah C. Heilshorn, Hongfeng Gao, Yosef Yarden, Byung Kook Lim, Germán Sumbre, Pei‐Lin Cheng, Ronit Pinkas‐Kramarski and Daniel Harari. Their work appears in journals such as Nature Communications, Cell Reports, Journal of Biological Chemistry, Neuron and Developmental Neurobiology.

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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