Won Mah

2.4k total citations · 1 hit paper
16 papers, 1.3k citations indexed

About

Won Mah is a scholar working on Cellular and Molecular Neuroscience, Genetics and Molecular Biology. According to data from OpenAlex, Won Mah has authored 16 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cellular and Molecular Neuroscience, 8 papers in Genetics and 7 papers in Molecular Biology. Recurrent topics in Won Mah's work include Neuroscience and Neuropharmacology Research (9 papers), Genetics and Neurodevelopmental Disorders (6 papers) and Pain Mechanisms and Treatments (3 papers). Won Mah is often cited by papers focused on Neuroscience and Neuropharmacology Research (9 papers), Genetics and Neurodevelopmental Disorders (6 papers) and Pain Mechanisms and Treatments (3 papers). Won Mah collaborates with scholars based in South Korea, United States and United Kingdom. Won Mah's co-authors include Hyejung Won, Eunjoon Kim, Eunjoon Kim, Yong Chul Bae, Yi Sul Cho, Daesoo Kim, Jungyong Nam, Jiseok Lee, Changuk Chung and Hye‐Ryeon Lee and has published in prestigious journals such as Nature, Nature Medicine and Journal of Neuroscience.

In The Last Decade

Won Mah

16 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Autistic-like social behaviour in Shank2-mutant mice improved by restoring NMDA receptor function

2012 535 citations Hyejung Won, Hye‐Ryeon Lee et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Won Mah South Korea	12	635	551	463	428	166	16	1.3k
Giovanni Provenzano Italy	17	381 0.6×	423 0.8×	518 1.1×	333 0.8×	115 0.7×	43	1.1k
Eleonora Calcagno Italy	21	649 1.0×	446 0.8×	270 0.6×	702 1.6×	79 0.5×	25	1.4k
Yi Sul Cho South Korea	17	556 0.9×	484 0.9×	463 1.0×	548 1.3×	149 0.9×	29	1.3k
Cory A. Blaiss United States	10	519 0.8×	449 0.8×	605 1.3×	589 1.4×	125 0.8×	11	1.3k
Ioanna Konidari United States	17	625 1.0×	618 1.1×	500 1.1×	329 0.8×	153 0.9×	26	1.6k
Amos Gdalyahu Israel	7	398 0.6×	469 0.9×	622 1.3×	379 0.9×	113 0.7×	7	1.1k
Michael Schoen Germany	18	524 0.8×	512 0.9×	396 0.9×	366 0.9×	143 0.9×	24	1.2k
Jiseok Lee South Korea	11	489 0.8×	645 1.2×	708 1.5×	393 0.9×	98 0.6×	15	1.2k
Carrie Shilyansky United States	7	622 1.0×	360 0.7×	633 1.4×	630 1.5×	85 0.5×	8	1.7k
J. Lloyd Holder United States	20	530 0.8×	715 1.3×	532 1.1×	246 0.6×	141 0.8×	40	1.5k

Countries citing papers authored by Won Mah

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Won Mah

This figure shows the co-authorship network connecting the top 25 collaborators of Won Mah. A scholar is included among the top collaborators of Won Mah based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Won Mah. Won Mah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

Cho, Yi Sul, Won Mah, Dong Ho Youn, et al.. (2023). Increase of glutamate in satellite glial cells of the trigeminal ganglion in a rat model of craniofacial neuropathic pain. Frontiers in Neuroanatomy. 17. 1302373–1302373. 5 indexed citations

Sey, Nancy Y. A., Benxia Hu, Won Mah, et al.. (2020). A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nature Neuroscience. 23(4). 583–593. 155 indexed citations

Mah, Won & Hyejung Won. (2019). The three-dimensional landscape of the genome in human brain tissue unveils regulatory mechanisms leading to schizophrenia risk. Schizophrenia Research. 217. 17–25. 23 indexed citations

Mah, Won, Jaekwang Lee, Jin Young Bae, et al.. (2017). A role for the purinergic receptor P2X3 in astrocytes in the mechanism of craniofacial neuropathic pain. Scientific Reports. 7(1). 13627–13627. 22 indexed citations

Bae, Jin Young, et al.. (2016). Expression of glycine receptor alpha 3 in the rat trigeminal neurons and central boutons in the brainstem. Brain Structure and Function. 221(9). 4601–4613. 10 indexed citations

Choi, Yeonsoo, Jungyong Nam, Daniel J. Whitcomb, et al.. (2016). SALM5 trans-synaptically interacts with LAR-RPTPs in a splicing-dependent manner to regulate synapse development. Scientific Reports. 6(1). 26676–26676. 51 indexed citations

Li, Yan, Peng Zhang, Hanwool Park, et al.. (2015). Splicing-Dependent Trans-synaptic SALM3–LAR-RPTP Interactions Regulate Excitatory Synapse Development and Locomotion. Cell Reports. 12(10). 1618–1630. 61 indexed citations

Mah, Won, et al.. (2015). Abnormal Astrocytosis in the Basal Ganglia Pathway of Git1−/− Mice. Molecules and Cells. 38(6). 540–547. 6 indexed citations

Mah, Won. (2015). Aberrant Thalamocortical Synchrony Associated with Behavioral Manifestations in Git1^−/− Mice. Experimental Neurobiology. 24(2). 126–132. 1 indexed citations

10.

Hong, Sung-Tae & Won Mah. (2015). A Critical Role of GIT1 in Vertebrate and Invertebrate Brain Development. Experimental Neurobiology. 24(1). 8–16. 24 indexed citations

11.

Bae, Jin Young, Jae Hyun Kim, Yi Sul Cho, Won Mah, & Yong Chul Bae. (2014). Quantitative analysis of afferents expressing substance P, calcitonin gene‐related peptide, isolectin B4, neurofilament 200, and Peripherin in the sensory root of the rat trigeminal ganglion. The Journal of Comparative Neurology. 523(1). 126–138. 50 indexed citations

12.

Won, Hyejung, Won Mah, & Eunjoon Kim. (2013). Autism spectrum disorder causes, mechanisms, and treatments: focus on neuronal synapses. Frontiers in Molecular Neuroscience. 6. 19–19. 155 indexed citations

13.

Won, Hyejung, Hye‐Ryeon Lee, Heon Yung Gee, et al.. (2012). Autistic-like social behaviour in Shank2-mutant mice improved by restoring NMDA receptor function. Nature. 486(7402). 261–265. 535 indexed citations breakdown →

14.

Won, Hyejung, Won Mah, Eunjin Kim, et al.. (2011). GIT1 is associated with ADHD in humans and ADHD-like behaviors in mice. Nature Medicine. 17(5). 566–572. 115 indexed citations

15.

Nam, Jungyong, Won Mah, & Eunjoon Kim. (2011). The SALM/Lrfn family of leucine-rich repeat-containing cell adhesion molecules. Seminars in Cell and Developmental Biology. 22(5). 492–498. 47 indexed citations

16.

Mah, Won, Jaewon Ko, Jungyong Nam, et al.. (2010). Selected SALM (Synaptic Adhesion-Like Molecule) Family Proteins Regulate Synapse Formation. Journal of Neuroscience. 30(16). 5559–5568. 71 indexed citations

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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