Carla Márquez‐Luna

2.9k total citations · 1 hit paper
14 papers, 680 citations indexed

About

Carla Márquez‐Luna is a scholar working on Genetics, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Carla Márquez‐Luna has authored 14 papers receiving a total of 680 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Genetics, 4 papers in Molecular Biology and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Carla Márquez‐Luna's work include Genetic Associations and Epidemiology (9 papers), Genomics and Rare Diseases (3 papers) and BRCA gene mutations in cancer (2 papers). Carla Márquez‐Luna is often cited by papers focused on Genetic Associations and Epidemiology (9 papers), Genomics and Rare Diseases (3 papers) and BRCA gene mutations in cancer (2 papers). Carla Márquez‐Luna collaborates with scholars based in United States, France and Mexico. Carla Márquez‐Luna's co-authors include Alkes L. Price, Po‐Ru Loh, Scott M. Damrauer, Sridharan Raghavan, Pradeep Natarajan, Cristen J. Willer, Euan A. Ashley, Jack W. O’Sullivan, Christopher J. O’Donnell and Jasmine A. Luzum and has published in prestigious journals such as The Lancet, Circulation and Nature Communications.

In The Last Decade

Carla Márquez‐Luna

14 papers receiving 670 citations

Hit Papers

align trajectories sort by overperformance

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.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

2022 207 citations Jack W. O’Sullivan, Sridharan Raghavan et al. Circulation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Carla Márquez‐Luna United States	10	350	167	132	69	69	14	680
Lisa A. Bastarache United States	9	461 1.3×	309 1.9×	79 0.6×	92 1.3×	120 1.7×	11	954
Robert Goodloe United States	15	240 0.7×	182 1.1×	46 0.3×	48 0.7×	32 0.5×	41	684
Akl C. Fahed United States	15	374 1.1×	177 1.1×	181 1.4×	204 3.0×	111 1.6×	43	935
Åsa K. Hedman Sweden	13	265 0.8×	555 3.3×	125 0.9×	67 1.0×	68 1.0×	19	891
Ajay Yesupriya United States	18	197 0.6×	135 0.8×	69 0.5×	69 1.0×	75 1.1×	29	705
Toomas Haller Estonia	9	253 0.7×	280 1.7×	41 0.3×	47 0.7×	93 1.3×	21	712
Teresa Kruisselbrink United States	11	214 0.6×	252 1.5×	366 2.8×	71 1.0×	66 1.0×	23	744
Johanne Marie Justesen Denmark	14	240 0.7×	162 1.0×	83 0.6×	68 1.0×	84 1.2×	20	531
Pietari Ripatti Finland	8	255 0.7×	112 0.7×	117 0.9×	92 1.3×	109 1.6×	14	514
Helen R. Warren United Kingdom	15	254 0.7×	226 1.4×	279 2.1×	59 0.9×	45 0.7×	40	806

Countries citing papers authored by Carla Márquez‐Luna

Since Specialization

Citations

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

Fields of papers citing papers by Carla Márquez‐Luna

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carla Márquez‐Luna. 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 Carla Márquez‐Luna. The network helps show where Carla Márquez‐Luna may publish in the future.

Co-authorship network of co-authors of Carla Márquez‐Luna

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

All Works

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14 of 14 papers shown

Duffy, Áine, Ben Omega Petrazzini, David Stein, et al.. (2024). Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications. Nature Genetics. 56(1). 51–59. 11 indexed citations

Petrazzini, Ben Omega, Iain S. Forrest, Ghislain Rocheleau, et al.. (2024). Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease. Nature Genetics. 56(7). 1412–1419. 9 indexed citations

Park, Joshua K., Ben Omega Petrazzini, Áine Duffy, et al.. (2024). Muesli Intake May Protect Against Coronary Artery Disease. JACC Advances. 3(4). 100888–100888. 1 indexed citations

Park, Joshua K., Iain S. Forrest, Áine Duffy, et al.. (2023). Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2600 disease traits. eLife. 12. 4 indexed citations

Márquez‐Luna, Carla, et al.. (2022). Online Education in Times of COVID: Adapting and Deploying a Data Science Program in Mexico. SHILAP Revista de lepidopterología. 1 indexed citations

Petrazzini, Ben Omega, Kumardeep Chaudhary, Carla Márquez‐Luna, et al.. (2022). Coronary Risk Estimation Based on Clinical Data in Electronic Health Records. Journal of the American College of Cardiology. 79(12). 1155–1166. 22 indexed citations

O’Sullivan, Jack W., Sridharan Raghavan, Carla Márquez‐Luna, et al.. (2022). Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation. 146(8). e93–e118. 207 indexed citations breakdown →

Forrest, Iain S., Ben Omega Petrazzini, Áine Duffy, et al.. (2022). Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts. The Lancet. 401(10372). 215–225. 94 indexed citations

Camarena, Beatríz, Elizabeth G. Atkinson, Mark R. Baker, et al.. (2021). Neuropsychiatric Genetics of Psychosis in the Mexican Population: A Genome-Wide Association Study Protocol for Schizophrenia, Schizoaffective, and Bipolar Disorder Patients and Controls. PubMed. 7(3-4). 60–70. 4 indexed citations

10.

Forrest, Iain S., Kumardeep Chaudhary, Ishan Paranjpe, et al.. (2021). Genome-wide polygenic risk score for retinopathy of type 2 diabetes. Human Molecular Genetics. 30(10). 952–960. 15 indexed citations

11.

Kim, Samuel S., Kushal K. Dey, Omer Weissbrod, et al.. (2020). Improving the informativeness of Mendelian disease-derived pathogenicity scores for common disease. Nature Communications. 11(1). 9 indexed citations

12.

Weissbrod, Omer, Farhad Hormozdiari, Christian Benner, et al.. (2020). Functionally informed fine-mapping and polygenic localization of complex trait heritability. Nature Genetics. 52(12). 1355–1363. 140 indexed citations

13.

Márquez‐Luna, Carla, Po‐Ru Loh, & Alkes L. Price. (2017). Multiethnic polygenic risk scores improve risk prediction in diverse populations. Genetic Epidemiology. 41(8). 811–823. 152 indexed citations

14.

García‐Velázquez, Lizbeth, Samuel Canizales‐Quinteros, Sandra Romero‐Hidalgo, et al.. (2013). Founder effect and ancestral origin of the spinocerebellar ataxia type 7 (SCA7) mutation in Mexican families. Neurogenetics. 15(1). 13–17. 11 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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