Matthew Dapas

689 citations
13 papers · 386 · 1 hit paper · h-index 8

Impact in

Papers in

    • Ovarian function and disorders 5
    • Genetic Associations and Epidemiology 3
    • Nutrition, Genetics, and Disease 1
    • Genetic Syndromes and Imprinting 1

Matthew Dapas

12 papers receiving 377 citations

Matthew Dapas's Hit Papers

Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis 2020 · 181 citations
1810+2+4Years since publication50100150

Peers

Matthew Dapas
Comparison fields: 5 of 53
  • Reproductive Medicine 260
  • Public Health, Environmental and Occupational Health 145
  • Endocrinology, Diabetes and Metabolism 32
  • Genetics 49
  • Urology 6
Replace Ryan Sisk with:
Ryan Sisk United States
Angela K. Chua United States
Achamma Chandy India
Ilaria Natali Italy
Larissa Berloffa Belardin Brazil
Muhammad Jaseem Khan Pakistan
Anne-Céline Reyss France
Baoying Liao China
Laura Torchen United States
Philippe Bouchard Canada
Matthew Dapas relative to Ryan Sisk United States Ryan Sisk's profile →
Citations per field
00.5×1.5×
Ryan Sisk · 1×
Citations per year

Countries citing papers authored by Matthew Dapas

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Dapas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1
Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis
Hit paper breakdown →
2020181
2 201965
3 201953
4 202021
5 202020
6 201620
7 20198
8 20227
9 20237
10 20222
11 20231
12 19991
13 20250

About Matthew Dapas

Matthew Dapas is a scholar working on Reproductive Medicine, Genetics, Molecular Biology, Physiology and Immunology, having authored 13 papers that have together received 386 indexed citations. Recurring topics across this work include Ovarian function and disorders (5 papers), Genetic Associations and Epidemiology (3 papers), Asthma and respiratory diseases (2 papers), Folate and B Vitamins Research (1 paper), IL-33, ST2, and ILC Pathways (1 paper), Nutrition, Genetics, and Disease (1 paper), Genetic Syndromes and Imprinting (1 paper) and Atherosclerosis and Cardiovascular Diseases (1 paper). The work is most often cited by research in Reproductive Medicine (260 citations), Public Health, Environmental and Occupational Health (145 citations), Endocrinology, Diabetes and Metabolism (32 citations), Genetics (49 citations) and Urology (6 citations). Matthew Dapas has collaborated with scholars based in United States, United Kingdom and Philippines. Frequent co-authors include M. Geoffrey Hayes, Richard S. Legro, Andrea Dunaif, Ryan Sisk, Margrit Urbanek, Frederick T. J. Lin, Girish N. Nadkarni, Lidija K. Gorsic, Manoj Kandpal and Yingtao Bi. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Briefings in Bioinformatics, Human Genetics and Genomics Advances, Obesity and PLoS Medicine.

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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