Won Mah
Impact in
- Cognitive Neuroscience top 5%
- Autism Spectrum Disorder Research
-
- Neuroscience and Neuropharmacology Research
Papers in
-
- Neuroscience and Neuropharmacology Research 9
- Neuroscience and Neural Engineering 3
- Genetics 8
- Genetics and Neurodevelopmental Disorders 6
- Genetic Associations and Epidemiology 2
- Co-authors
- Hyejung Won (5 shared papers)Eunjoon Kim (6 shared papers)Eunjoon Kim (1 shared paper)Yong Chul Bae (6 shared papers)Yi Sul Cho (3 shared papers)Daesoo Kim (2 shared papers)Jungyong Nam (3 shared papers)Bong‐Kiun Kaang (1 shared paper)
- Journals
- Scientific Reports (2 papers)Experimental Neurobiology (2 papers)Nature Medicine (1 paper)Molecules and Cells (1 paper)Seminars in Cell and Developmental Biology (1 paper)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Won Mah
16 papers receiving 1.3k citations
Won Mah's Hit Papers
Peers
Comparison fields: 5 of 90
- Cognitive Neuroscience 463
- Cellular and Molecular Neuroscience 428
- Genetics 551
- Developmental Neuroscience 67
- Biological Psychiatry 33
Countries citing papers authored by Won Mah
This map shows the geographic impact of Won Mah'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 Won Mah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Won Mah more than expected).
Fields of papers citing papers by Won Mah
This network shows the impact of papers produced by Won Mah. 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 Won Mah. The network helps show where Won Mah may publish in the future.
Co-authors
The 25 scholars most cited alongside Won Mah, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Autistic-like social behaviour in Shank2-mutant mice improved by restoring NMDA receptor function Hit paper breakdown → | 2012 | 535 |
| 2 | 2013 | 155 | |
| 3 | 2020 | 155 | |
| 4 | 2011 | 115 | |
| 5 | 2010 | 71 | |
| 6 | 2015 | 61 | |
| 7 | 2016 | 51 | |
| 8 | 2014 | 50 | |
| 9 | 2011 | 47 | |
| 10 | 2015 | 24 | |
| 11 | 2019 | 23 | |
| 12 | 2017 | 22 | |
| 13 | 2016 | 10 | |
| 14 | 2015 | 6 | |
| 15 | 2023 | 5 | |
| 16 | 2015 | 1 |
About Won Mah
Won Mah is a scholar working on Cellular and Molecular Neuroscience, Genetics, Molecular Biology, Cognitive Neuroscience and Cell Biology, having authored 16 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (9 papers), Genetics and Neurodevelopmental Disorders (6 papers), Pain Mechanisms and Treatments (3 papers), Neuroscience and Neural Engineering (3 papers), Cellular transport and secretion (3 papers), Attention Deficit Hyperactivity Disorder (2 papers), Genetic Associations and Epidemiology (2 papers) and Autism Spectrum Disorder Research (2 papers). The work is most often cited by research in Cognitive Neuroscience (463 citations), Cellular and Molecular Neuroscience (428 citations), Genetics (551 citations), Developmental Neuroscience (67 citations) and Biological Psychiatry (33 citations). Won Mah has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Hyejung Won, Eunjoon Kim, Eunjoon Kim, Yong Chul Bae, Yi Sul Cho, Daesoo Kim, Jungyong Nam, Bong‐Kiun Kaang, Seungmin Ha and Eun Suk Jung. Their work appears in journals such as Scientific Reports, Experimental Neurobiology, Nature Medicine, Molecules and Cells and Seminars in Cell and Developmental Biology.
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.