Mary Dang

937 citations
25 papers · 314 · h-index 10

Impact in

Papers in

Mary Dang

22 papers receiving 308 citations

Peers

Mary Dang
Comparison fields: 5 of 66
  • Endocrinology, Diabetes and Metabolism 121
  • Genetics 46
  • Genetics 89
  • Surgery 120
  • Geriatrics and Gerontology 8
Replace Itahisa Marcelino-Rodríguez with:
Itahisa Marcelino-Rodríguez Spain
Diana Ly United States
Nazlı Gönç Türkiye
Élise Bismuth France
Guanping Dong China
Pınar İşgüven Türkiye
Johnnie Oli Nigeria
Joanna Yuet‐ling Tung China
Ioannis Kosmas Greece
Shubhada Jagasia United States
Mary Dang relative to Itahisa Marcelino-Rodríguez Spain Itahisa Marcelino-Rodríguez's profile →
Citations per field
00.5×
Itahisa Marcelino-Rodríguez · 1×
Citations per year

Countries citing papers authored by Mary Dang

Since Specialization
Citations

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

Fields of papers citing papers by Mary Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201772
2 201259
3 201737
4 201827
5 202125
6 201513
7 201811
8 201810
9 201710
10 20209
11 20027
12 20206
13 20176
14 20186
15 20155
16 20153
17 20163
18 20201
19 20201
20 20161

About Mary Dang

Mary Dang is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Molecular Biology, Epidemiology and Genetics, having authored 25 papers that have together received 314 indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (8 papers), Pancreatic function and diabetes (3 papers), Epigenetics and DNA Methylation (3 papers), Diabetes and associated disorders (3 papers), Growth Hormone and Insulin-like Growth Factors (3 papers), Neuroendocrine Tumor Research Advances (3 papers), Adrenal and Paraganglionic Tumors (3 papers) and Glioma Diagnosis and Treatment (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (121 citations), Genetics (46 citations), Genetics (89 citations), Surgery (120 citations) and Geriatrics and Gerontology (8 citations). Mary Dang has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Richard David Leslie, Raffaella Buzzetti, Paolo Pozzilli, Márta Korbonits, Donato Iacovazzo, Michael Powell, Francisca Caimari, Plamena Gabrovska, Pedro Marques and Federico Roncaroli. Their work appears in journals such as Plastic & Reconstructive Surgery, Diabetes/Metabolism Research and Reviews, Journal of Medical Genetics, BJPsych Open and Open Forum Infectious Diseases.

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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