Ellen M. Schmidt

24.4k total citations · 1 hit paper
16 papers, 751 citations indexed

About

Ellen M. Schmidt is a scholar working on Genetics, Molecular Biology and Biochemistry. According to data from OpenAlex, Ellen M. Schmidt has authored 16 papers receiving a total of 751 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Genetics, 5 papers in Molecular Biology and 4 papers in Biochemistry. Recurrent topics in Ellen M. Schmidt's work include Genetic Associations and Epidemiology (8 papers), Genomics and Rare Diseases (4 papers) and BRCA gene mutations in cancer (3 papers). Ellen M. Schmidt is often cited by papers focused on Genetic Associations and Epidemiology (8 papers), Genomics and Rare Diseases (4 papers) and BRCA gene mutations in cancer (3 papers). Ellen M. Schmidt collaborates with scholars based in United States, Germany and Norway. Ellen M. Schmidt's co-authors include Gonçalo R. Abecasis, Seunggeun Lee, Rounak Dey, Cristen J. Willer, Matthew Zawistowski, Sachin Kheterpal, Lars G. Fritsche, Chad M. Brummett, Jin Chen and Gareth Peat and has published in prestigious journals such as Nature Genetics, Nature Neuroscience and Bioinformatics.

In The Last Decade

Ellen M. Schmidt

16 papers receiving 732 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.

An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci

2021 223 citations Edward Mountjoy, Ellen M. Schmidt et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ellen M. Schmidt United States	12	352	288	67	50	46	16	751
Claudia Cabrera United Kingdom	18	312 0.9×	427 1.5×	66 1.0×	49 1.0×	56 1.2×	42	943
Qin Qin Huang United Kingdom	8	524 1.5×	383 1.3×	62 0.9×	64 1.3×	54 1.2×	9	1.1k
Emil Uffelmann Netherlands	3	421 1.2×	305 1.1×	45 0.7×	46 0.9×	42 0.9×	6	880
Jeffery R. O’Connell United States	11	578 1.6×	222 0.8×	64 1.0×	80 1.6×	24 0.5×	19	947
Raffaella Sciajno Italy	19	293 0.8×	378 1.3×	22 0.3×	69 1.4×	79 1.7×	27	1.6k
Judit Bene Hungary	17	179 0.5×	381 1.3×	88 1.3×	49 1.0×	61 1.3×	77	1.0k
Hsin‐Chou Yang Taiwan	20	346 1.0×	429 1.5×	154 2.3×	67 1.3×	39 0.8×	73	1.2k
William J. Astle United Kingdom	9	273 0.8×	357 1.2×	66 1.0×	34 0.7×	17 0.4×	14	807
William L. Duren United States	9	428 1.2×	407 1.4×	45 0.7×	24 0.5×	19 0.4×	23	901
R. E. OAKEY United Kingdom	17	347 1.0×	222 0.8×	61 0.9×	24 0.5×	70 1.5×	79	1.1k

Countries citing papers authored by Ellen M. Schmidt

Since Specialization

Citations

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

Fields of papers citing papers by Ellen M. Schmidt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ellen M. Schmidt

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

All Works

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16 of 16 papers shown

Zawistowski, Matthew, Lars G. Fritsche, Anita Pandit, et al.. (2023). The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients. Cell Genomics. 3(2). 100257–100257. 40 indexed citations

Mountjoy, Edward, Ellen M. Schmidt, Miguel Carmona, et al.. (2021). An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci. Nature Genetics. 53(11). 1527–1533. 223 indexed citations breakdown →

Goldstein, Jeffrey A., Joshua S. Weinstock, Lisa A. Bastarache, et al.. (2020). LabWAS: Novel findings and study design recommendations from a meta-analysis of clinical labs in two independent biobanks. PLoS Genetics. 16(11). e1009077–e1009077. 13 indexed citations

Fritsche, Lars G., Stephen B. Gruber, Zhenke Wu, et al.. (2018). Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative. The American Journal of Human Genetics. 102(6). 1048–1061. 102 indexed citations

Larach, Daniel B., Milo Engoren, Ellen M. Schmidt, & Michael Heung. (2017). Genetic variants and acute kidney injury: A review of the literature. Journal of Critical Care. 44. 203–211. 20 indexed citations

Sanchez‐Roige, Sandra, Pierre Fontanillas, Sarah L. Elson, et al.. (2017). Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry. Nature Neuroscience. 21(1). 16–18. 70 indexed citations

Dey, Rounak, Ellen M. Schmidt, Gonçalo R. Abecasis, & Seunggeun Lee. (2017). A Fast and Accurate Algorithm to Test for Binary Phenotypes and Its Application to PheWAS. The American Journal of Human Genetics. 101(1). 37–49. 87 indexed citations

Schmidt, Ellen M. & Cristen J. Willer. (2015). Insights into blood lipids from rare variant discovery. Current Opinion in Genetics & Development. 33. 25–31. 4 indexed citations

Schmidt, Ellen M., Ji Zhang, Wei Zhou, et al.. (2015). GREGOR: evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach. Bioinformatics. 31(16). 2601–2606. 81 indexed citations

10.

Holmen, Oddgeir L., He Zhang, Wei Zhou, et al.. (2014). No large-effect low-frequency coding variation found for myocardial infarction. Human Molecular Genetics. 23(17). 4721–4728. 5 indexed citations

11.

Schmidt, Ellen M., et al.. (2007). PATOLOGIA CLÍNICA EM AVES DE PRODUÇÃO – UMA FERRAMENTA PARA MONITORAR A SANIDADE AVÍCOLA – REVISÃO. Archives of Veterinary Science. 12(3). 49 indexed citations

12.

Schmidt, Ellen M. & Friedrich W. Schmidt. (1978). Sex Differences of Plasma Cholinesterase in the Rat. Enzyme. 23(1). 52–55. 19 indexed citations

13.

Schmidt, Ellen M., et al.. (1977). Diagnosis of liver diseases : an illustrated textbook. Thieme eBooks. 1 indexed citations

14.

Lesch, P., et al.. (1973). Effects of Chronic Alcohol Abuse on the Fatty Acid Composition of Major Lipids in the Human Brain. 7 indexed citations

15.

Lesch, P., et al.. (1973). Effects of Chronic Alcohol Abuse on the Fatty Acid Composition of Major Lipids in the Human Brain. Hepatocerebral Degeneration, II.. Clinical Chemistry and Laboratory Medicine (CCLM). 11(4). 159–66. 14 indexed citations

16.

Lesch, P., et al.. (1972). Effects of Chronic Alcohol Abuse on the Structural Lipids in the Human Brain. Clinical Chemistry and Laboratory Medicine (CCLM). 10(9). 16 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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