Mona Khan

1.7k citations
23 papers · 703 · h-index 14

Impact in

Papers in

Mona Khan

23 papers receiving 673 citations

Peers

Mona Khan
Comparison fields: 5 of 76
  • Sensory Systems 481
  • Nutrition and Dietetics 357
  • Cellular and Molecular Neuroscience 362
  • Developmental Neuroscience 12
  • Neurology 22
Replace Ai Nakashima with:
Ai Nakashima Japan
Conor M. Stack United States
K Imamura Japan
Jessica H. Brann United States
Qiang Qiu United States
Fritz W. Lischka United States
Gaëlle Guiraudie-Capraz France
Sidonie Conzelmann Germany
Shuitsu Harada Japan
A. Beck Germany
Mona Khan relative to Ai Nakashima Japan Ai Nakashima's profile →
Citations per field
00.5×3.4×
Ai Nakashima · 1×
Citations per year

Countries citing papers authored by Mona Khan

Since Specialization
Citations

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

Fields of papers citing papers by Mona Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015128
2 2011117
3 201959
4 201558
5 201457
6 200753
7 201344
8 202030
9 201427
10 201626
11 201522
12 201616
13 202115
14 201615
15 201911
16 20205
17 20144
18 20243
19 20243
20 20243

About Mona Khan

Mona Khan is a scholar working on Sensory Systems, Nutrition and Dietetics, Cellular and Molecular Neuroscience, Molecular Biology and Biomedical Engineering, having authored 23 papers that have together received 703 indexed citations. Recurring topics across this work include Olfactory and Sensory Function Studies (14 papers), Biochemical Analysis and Sensing Techniques (9 papers), Neurobiology and Insect Physiology Research (7 papers), Advanced Chemical Sensor Technologies (4 papers), CRISPR and Genetic Engineering (3 papers), Animal Genetics and Reproduction (2 papers), Pluripotent Stem Cells Research (2 papers) and Cerebrospinal fluid and hydrocephalus (1 paper). The work is most often cited by research in Sensory Systems (481 citations), Nutrition and Dietetics (357 citations), Cellular and Molecular Neuroscience (362 citations), Developmental Neuroscience (12 citations) and Neurology (22 citations). Mona Khan has collaborated with scholars based in United States, Belgium and United Kingdom. Frequent co-authors include Peter Mombaerts, Evelien Vaes, Ximena Ibarra-Soria, Darren W. Logan, Luís R. Saraiva, John C. Marioni, Masayo Omura, Antonio Scialdone, Andreas Walz and Paul Feinstein. Their work appears in journals such as genesis, Scientific Reports, Nature Communications, eNeuro and 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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