Daniel M. Jordan

10.8k total citations · 1 hit paper
36 papers, 3.3k citations indexed

About

Daniel M. Jordan is a scholar working on Genetics, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Daniel M. Jordan has authored 36 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Genetics, 12 papers in Molecular Biology and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Daniel M. Jordan's work include Genetic Associations and Epidemiology (22 papers), Genomics and Rare Diseases (18 papers) and Genomic variations and chromosomal abnormalities (9 papers). Daniel M. Jordan is often cited by papers focused on Genetic Associations and Epidemiology (22 papers), Genomics and Rare Diseases (18 papers) and Genomic variations and chromosomal abnormalities (9 papers). Daniel M. Jordan collaborates with scholars based in United States, France and United Kingdom. Daniel M. Jordan's co-authors include Shamil Sunyaev, Ivan Adzhubei, Ron Do, Christopher A. Cassa, Marie Verbanck, Girish N. Nadkarni, Mark Tong, Hong‐Hee Won, Vasily Ramensky and Daniel J. Balick and has published in prestigious journals such as Nature, Science and The Lancet.

In The Last Decade

Daniel M. Jordan

34 papers receiving 3.3k 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.

Predicting Functional Effect of Human Missense Mutations Using PolyPhen‐2

2013 2.4k citations Ivan Adzhubei, Daniel M. Jordan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel M. Jordan United States	14	1.8k	1.4k	401	239	227	36	3.3k
Jeremy Schwartzentruber Canada	34	2.2k 1.2×	1.3k 0.9×	294 0.7×	232 1.0×	142 0.6×	75	3.7k
Maya Kasowski United States	10	2.0k 1.1×	1.1k 0.8×	448 1.1×	157 0.7×	134 0.6×	14	3.0k
Benjamin C. Hitz United States	14	3.1k 1.7×	1.1k 0.7×	580 1.4×	209 0.9×	171 0.8×	16	4.3k
Samuel A. Lambert United Kingdom	13	2.0k 1.1×	691 0.5×	406 1.0×	246 1.0×	126 0.6×	16	3.1k
Sonia Abdelhak Tunisia	26	1.7k 0.9×	953 0.7×	247 0.6×	162 0.7×	561 2.5×	206	3.3k
Marialuisa Lavitrano Italy	32	2.3k 1.3×	1.6k 1.1×	269 0.7×	298 1.2×	485 2.1×	136	3.5k
Matthew N. Bainbridge United States	30	2.4k 1.4×	1.3k 0.9×	595 1.5×	279 1.2×	81 0.4×	62	3.8k
Marc A. Schaub United States	8	1.5k 0.8×	1.1k 0.8×	341 0.9×	150 0.6×	149 0.7×	9	2.6k
Piotr Kozłowski Poland	33	2.1k 1.2×	706 0.5×	759 1.9×	330 1.4×	160 0.7×	124	3.5k
Vasily Ramensky Russia	15	1.7k 0.9×	986 0.7×	199 0.5×	181 0.8×	160 0.7×	39	2.5k

Countries citing papers authored by Daniel M. Jordan

Since Specialization

Citations

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

Fields of papers citing papers by Daniel M. Jordan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Jordan. 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 Daniel M. Jordan. The network helps show where Daniel M. Jordan may publish in the future.

Co-authorship network of co-authors of Daniel M. Jordan

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Forrest, Iain S., Kuan‐lin Huang, Julie M. Eggington, et al.. (2025). Using large-scale population-based data to improve disease risk assessment of clinical variants. Nature Genetics. 57(7). 1588–1597. 1 indexed citations

Forrest, Iain S., Ha My T. Vy, Ghislain Rocheleau, et al.. (2025). Machine learning–based penetrance of genetic variants. Science. 389(6763). eadm7066–eadm7066. 2 indexed citations

Duffy, Áine, David Stein, Joshua K. Park, et al.. (2025). Development of a genetic priority score to predict drug side effects using human genetic evidence. Nature Communications. 16(1). 8713–8713.

Petrazzini, Ben Omega, Áine Duffy, Ghislain Rocheleau, et al.. (2025). Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease. Genome biology. 26(1). 50–50. 3 indexed citations

Duffy, Áine, Joshua K. Park, David Stein, et al.. (2025). Genetic evidence informs the direction of therapeutic modulation in drug development. PubMed. 2(1). 24–24.

Rocheleau, Ghislain, Ben Omega Petrazzini, Iain S. Forrest, et al.. (2025). Genetic analyses of eight complex diseases using predicted continuous representations of disease. Cell Reports Methods. 5(8). 101115–101115. 1 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

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

Duffy, Áine, Ben Omega Petrazzini, Ha My T. Vy, et al.. (2024). Expanding drug targets for 112 chronic diseases using a machine learning-assisted genetic priority score. Nature Communications. 15(1). 8891–8891. 5 indexed citations

10.

Petrazzini, Ben Omega, Daniel J. Balick, Iain S. Forrest, et al.. (2024). Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease. Cell Reports Methods. 4(12). 100914–100914. 2 indexed citations

11.

Forrest, Iain S., Ben Omega Petrazzini, Áine Duffy, et al.. (2023). A machine learning model identifies patients in need of autoimmune disease testing using electronic health records. Nature Communications. 14(1). 2385–2385. 18 indexed citations

12.

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

13.

Rocheleau, Ghislain, Iain S. Forrest, Áine Duffy, et al.. (2022). A tissue-level phenome-wide network map of colocalized genes and phenotypes in the UK Biobank. Communications Biology. 5(1). 849–849. 1 indexed citations

14.

Jordan, Daniel M., Hyon K. Choi, Marie Verbanck, et al.. (2019). No causal effects of serum urate levels on the risk of chronic kidney disease: A Mendelian randomization study. PLoS Medicine. 16(1). e1002725–e1002725. 93 indexed citations

15.

Cassa, Christopher A., Daniel M. Jordan, Ivan Adzhubei, & Shamil Sunyaev. (2018). A literature review at genome scale: improving clinical variant assessment. Genetics in Medicine. 20(9). 936–941. 1 indexed citations

16.

Cassa, Christopher A., Donate Weghorn, Daniel J. Balick, et al.. (2017). Estimating the selective effects of heterozygous protein-truncating variants from human exome data. Nature Genetics. 49(5). 806–810. 79 indexed citations

17.

Lenz, Tobias L., Victor Spirin, Daniel M. Jordan, & Shamil Sunyaev. (2016). Excess of Deleterious Mutations around HLA Genes Reveals Evolutionary Cost of Balancing Selection. Molecular Biology and Evolution. 33(10). 2555–2564. 39 indexed citations

18.

Jordan, Daniel M., Stephan Frangakis, Christelle Golzio, et al.. (2015). Identification of cis-suppression of human disease mutations by comparative genomics. Nature. 524(7564). 225–229. 67 indexed citations

19.

Jordan, Daniel M., Adam Kieżun, Samantha Baxter, et al.. (2011). Development and Validation of a Computational Method for Assessment of Missense Variants in Hypertrophic Cardiomyopathy. The American Journal of Human Genetics. 88(2). 183–192. 58 indexed citations

20.

Jordan, Daniel M., et al.. (2007). Parameterization of Peptide ¹³C Carbonyl Chemical Shielding Anisotropy in Molecular Dynamics Simulations. ChemPhysChem. 8(9). 1375–1385. 5 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.

Explore authors with similar magnitude of impact