Ming-X Tang

1.8k total citations
10 papers, 1.3k citations indexed

About

Ming-X Tang is a scholar working on Psychiatry and Mental health, Neurology and Physiology. According to data from OpenAlex, Ming-X Tang has authored 10 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Psychiatry and Mental health, 4 papers in Neurology and 4 papers in Physiology. Recurrent topics in Ming-X Tang's work include Dementia and Cognitive Impairment Research (6 papers), Alzheimer's disease research and treatments (4 papers) and Amyotrophic Lateral Sclerosis Research (4 papers). Ming-X Tang is often cited by papers focused on Dementia and Cognitive Impairment Research (6 papers), Alzheimer's disease research and treatments (4 papers) and Amyotrophic Lateral Sclerosis Research (4 papers). Ming-X Tang collaborates with scholars based in United States, India and United Kingdom. Ming-X Tang's co-authors include Nicole Schupf, Yaakov Stern, Jennifer J. Manly, Lawrence S. Honig, R. Mayeux, Pankaj Mehta, Richard Mayeux, Elizabeth Helzner, Stephanie Cosentino and Lewis P. Rowland and has published in prestigious journals such as Neurology, Dementia and Geriatric Cognitive Disorders and Journal of Geriatric Psychiatry and Neurology.

In The Last Decade

Ming-X Tang

10 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ming-X Tang United States	9	609	492	267	165	140	10	1.3k
Soo Jin Yoon South Korea	20	466 0.8×	345 0.7×	278 1.0×	176 1.1×	109 0.8×	45	1.3k
Willa D. Brenowitz United States	23	615 1.0×	666 1.4×	213 0.8×	201 1.2×	138 1.0×	65	1.6k
Yasuyo Mimori Japan	24	422 0.7×	287 0.6×	492 1.8×	187 1.1×	237 1.7×	67	1.6k
A. Kazis Greece	17	411 0.7×	197 0.4×	259 1.0×	304 1.8×	141 1.0×	47	1.7k
Irma M. Parhad United States	18	403 0.7×	319 0.6×	355 1.3×	161 1.0×	281 2.0×	25	1.4k
Alberto Villarejo‐Galende Spain	26	570 0.9×	435 0.9×	599 2.2×	166 1.0×	266 1.9×	110	1.9k
Leonel Tadao Takada Brazil	21	563 0.9×	384 0.8×	489 1.8×	266 1.6×	352 2.5×	46	1.4k
Brandy R. Matthews United States	16	623 1.0×	534 1.1×	217 0.8×	203 1.2×	183 1.3×	36	1.6k
Merilee Teylan United States	23	771 1.3×	717 1.5×	256 1.0×	183 1.1×	179 1.3×	50	1.8k
K Kondo Japan	15	521 0.9×	590 1.2×	429 1.6×	205 1.2×	414 3.0×	31	1.7k

Countries citing papers authored by Ming-X Tang

Since Specialization

Citations

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

Fields of papers citing papers by Ming-X Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming-X Tang. 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 Ming-X Tang. The network helps show where Ming-X Tang may publish in the future.

Co-authorship network of co-authors of Ming-X Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Ming-X Tang. A scholar is included among the top collaborators of Ming-X Tang 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 Ming-X Tang. Ming-X Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Manly, Jennifer J., Nicole Schupf, Yaakov Stern, et al.. (2011). Telephone-Based Identification of Mild Cognitive Impairment and Dementia in a Multicultural Cohort. Archives of Neurology. 68(5). 607–14. 79 indexed citations

Gooch, Clifton L., Seth L. Pullman, Dikoma C. Shungu, et al.. (2009). Motor unit number estimation (MUNE) in diseases of the motor neuron: utility and comparative analysis in a multimodal biomarker study1. Supplements to Clinical neurophysiology. 60. 153–162. 9 indexed citations

Floyd, A, Qin Yu, Panida Piboolnurak, et al.. (2009). Transcranial magnetic stimulation in ALS. Neurology. 72(6). 498–504. 62 indexed citations

Helzner, Elizabeth, et al.. (2008). Survival in Alzheimer disease. Neurology. 71(19). 1489–1495. 155 indexed citations

Schupf, Nicole, et al.. (2007). The Heritability of Abstract Reasoning in Caribbean Latinos with Familial Alzheimer Disease. Dementia and Geriatric Cognitive Disorders. 24(6). 411–417. 10 indexed citations

Mitsumoto, Hiroshi, Aziz M. Uluğ, Seth L. Pullman, et al.. (2007). Quantitative objective markers for upper and lower motor neuron dysfunction in ALS. Neurology. 68(17). 1402–1410. 167 indexed citations

Mitsumoto, Hiroshi, A Floyd, Ming-X Tang, et al.. (2006). Chapter 44 Transcranial magnetic stimulation for upper motor neuron involvement in amyotrophic lateral sclerosis (ALS). Supplements to Clinical neurophysiology. 59. 327–332. 4 indexed citations

Manly, Jennifer J., et al.. (2005). Implementing Diagnostic Criteria and Estimating Frequency of Mild Cognitive Impairment in an Urban Community. Archives of Neurology. 62(11). 1739–1739. 208 indexed citations

Manly, Jennifer J., Nicole Schupf, Ming-X Tang, & Yaakov Stern. (2005). Cognitive Decline and Literacy Among Ethnically Diverse Elders. Journal of Geriatric Psychiatry and Neurology. 18(4). 213–217. 207 indexed citations

10.

Mayeux, R., Lawrence S. Honig, Ming-X Tang, et al.. (2003). Plasma Aβ40 and Aβ42 and Alzheimer’s disease. Neurology. 61(9). 1185–1190. 370 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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