Maya Shelly

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

Impact in

Papers in

Maya Shelly

21 papers receiving 1.6k citations

Peers

Maya Shelly
Comparison fields: 5 of 91
  • Developmental Neuroscience 248
  • Cellular and Molecular Neuroscience 594
  • Cell Biology 308
  • Aging 31
  • Oncology 413
Replace Vladislav V. Kiselyov with:
Vladislav V. Kiselyov Denmark
Jean‐François Cloutier Canada
Weichun Lin United States
Gerald F. Reis United States
Raffaella Scardigli Italy
Ralf S. Schmid United States
Maria A. Morabito United States
Zachary P. Wills United States
Katsuhiro Kato Japan
Shuji Wakatsuki Japan
Maya Shelly relative to Vladislav V. Kiselyov Denmark Vladislav V. Kiselyov's profile →
Citations per field
00.5×5.3×
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-authors

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

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007286
2 1999247
3 2010204
4 2011173
5 1996127
6 2011126
7 1998122
8 1998113
9 200352
10 201350
11 201147
12 201727
13 202320
14 201615
15 201611
16 20208
17 20225
18 20224
19 20124
20 20241

About Maya Shelly

Maya Shelly is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Developmental Neuroscience, Oncology 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), Neurogenesis and neuroplasticity mechanisms (6 papers), Neuroscience and Neuropharmacology Research (6 papers), HER2/EGFR in Cancer Research (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Luminescence Properties of Advanced Materials (2 papers), Nerve injury and regeneration (2 papers) and Cell Adhesion Molecules Research (2 papers). The work is most often cited by research in Developmental Neuroscience (248 citations), Cellular and Molecular Neuroscience (594 citations), Cell Biology (308 citations), Aging (31 citations) and Oncology (413 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, Yosef Yarden, Hongfeng Gao, 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 Cell.

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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