Matthew Dapas

663 total citations · 1 hit paper
13 papers, 374 citations indexed

About

Matthew Dapas is a scholar working on Genetics, Reproductive Medicine and Immunology. According to data from OpenAlex, Matthew Dapas has authored 13 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Genetics, 5 papers in Reproductive Medicine and 3 papers in Immunology. Recurrent topics in Matthew Dapas's work include Genetic Associations and Epidemiology (5 papers), Ovarian function and disorders (5 papers) and Reproductive Biology and Fertility (2 papers). Matthew Dapas is often cited by papers focused on Genetic Associations and Epidemiology (5 papers), Ovarian function and disorders (5 papers) and Reproductive Biology and Fertility (2 papers). Matthew Dapas collaborates with scholars based in United States, United Kingdom and Australia. Matthew Dapas's co-authors include Margrit Urbanek, M. Geoffrey Hayes, Richard S. Legro, Andrea Dunaif, Ryan Sisk, Frederick T. J. Lin, Girish N. Nadkarni, Lidija K. Gorsic, Ramana V. Davuluri and Yingtao Bi and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, Gut and Journal of Allergy and Clinical Immunology.

In The Last Decade

Matthew Dapas

12 papers receiving 365 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.

Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis

2020 174 citations Matthew Dapas, Frederick T. J. Lin et al. PLoS Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew Dapas United States	8	267	197	81	65	49	13	374
Angela K. Chua United States	8	305 1.1×	241 1.2×	88 1.1×	62 1.0×	48 1.0×	8	389
Sheena L.P. Regan Australia	11	235 0.9×	318 1.6×	61 0.8×	133 2.0×	53 1.1×	13	469
Muhammad Fatum United Kingdom	13	346 1.3×	328 1.7×	35 0.4×	85 1.3×	44 0.9×	24	522
Ryan Sisk United States	9	339 1.3×	252 1.3×	77 1.0×	66 1.0×	76 1.6×	16	411
Arnaud Leclerc France	5	281 1.1×	269 1.4×	61 0.8×	68 1.0×	30 0.6×	5	383
Achamma Chandy India	9	286 1.1×	205 1.0×	46 0.6×	102 1.6×	70 1.4×	19	397
Volkan Emirdar Türkiye	8	142 0.5×	159 0.8×	38 0.5×	60 0.9×	19 0.4×	18	281
Lejun Li China	12	158 0.6×	95 0.5×	78 1.0×	134 2.1×	21 0.4×	36	368
Karolina Kowalczyk Poland	7	140 0.5×	100 0.5×	20 0.2×	41 0.6×	78 1.6×	30	285
Philippe Bouchard Canada	12	226 0.8×	212 1.1×	56 0.7×	59 0.9×	43 0.9×	23	501

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-authorship network of co-authors of Matthew Dapas

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

All Works

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13 of 13 papers shown

Steininger, Holly, Kathryn McCauley, Kristine Lee, et al.. (2025). Upper Airway Microbiome Interactions with GSDMB and ORMDL3 Asthma Risk Genes Influence Early Life Wheeze Outcomes. Journal of Allergy and Clinical Immunology. 155(2). AB303–AB303.

Brewer, Kelly, Ryan Sisk, Hyejin Lee, et al.. (2023). OR20-02 Trans-Ethnic Analysis Of PCOS Subtype Genomewide Association Signals Reveals 3 Shared Subtype-Specific Loci. Journal of the Endocrine Society. 7(Supplement_1). 1 indexed citations

Dapas, Matthew, et al.. (2023). Revealing polygenic pleiotropy using genetic risk scores for asthma. Human Genetics and Genomics Advances. 4(4). 100233–100233. 7 indexed citations

Schoettler, Nathan, Peter Carbonetto, Matthew Dapas, et al.. (2022). Fine-mapping studies distinguish genetic risks for childhood- and adult-onset asthma in the HLA region. Genome Medicine. 14(1). 55–55. 6 indexed citations

Dapas, Matthew, Evanthia Diamanti‐Kandarakis, Andrea Dunaif, et al.. (2022). RF10 | PMON217 Replication of PCOS Reproductive and Metabolic Subtypes in Diverse Cohorts – Towards a Rationale Approach to PCOS Classification. Journal of the Endocrine Society. 6(Supplement_1). A711–A711. 2 indexed citations

Dapas, Matthew & Andrea Dunaif. (2020). The contribution of rare genetic variants to the pathogenesis of polycystic ovary syndrome. Current Opinion in Endocrine and Metabolic Research. 12. 26–32. 20 indexed citations

Lu, Thomas X., et al.. (2020). The influence of proton pump inhibitor therapy on the outcome of infliximab therapy in inflammatory bowel disease: a patient-level meta-analysis of randomised controlled studies. Gut. 70(11). 2076–2084. 20 indexed citations

Dapas, Matthew, Frederick T. J. Lin, Girish N. Nadkarni, et al.. (2020). Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis. PLoS Medicine. 17(6). e1003132–e1003132. 174 indexed citations breakdown →

Dapas, Matthew, Ryan Sisk, Richard S. Legro, et al.. (2019). Family-Based Quantitative Trait Meta-Analysis Implicates Rare Noncoding Variants in DENND1A in Polycystic Ovary Syndrome. The Journal of Clinical Endocrinology & Metabolism. 104(9). 3835–3850. 51 indexed citations

10.

Gorsic, Lidija K., Matthew Dapas, Richard S. Legro, M. Geoffrey Hayes, & Margrit Urbanek. (2019). Functional Genetic Variation in the Anti-Müllerian Hormone Pathway in Women With Polycystic Ovary Syndrome. The Journal of Clinical Endocrinology & Metabolism. 104(7). 2855–2874. 64 indexed citations

11.

Torchen, Laura, Joy N. Tsai, Ryan Sisk, et al.. (2019). Hyperandrogenemia is Common in Asymptomatic Women and is Associated with Increased Metabolic Risk. Obesity. 28(1). 106–113. 8 indexed citations

12.

Dapas, Matthew, Manoj Kandpal, Yingtao Bi, & Ramana V. Davuluri. (2016). Comparative evaluation of isoform-level gene expression estimation algorithms for RNA-seq and exon-array platforms. Briefings in Bioinformatics. 18(2). bbw016–bbw016. 20 indexed citations

13.

Dapas, Matthew, et al.. (1999). P15 Small LDL pattern B trait in normal subjects. Atherosclerosis. 145. S15–S15. 1 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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