Eric M. Sobel

6.5k total citations · 3 hit papers
74 papers, 4.2k citations indexed

About

Eric M. Sobel is a scholar working on Genetics, Molecular Biology and Oncology. According to data from OpenAlex, Eric M. Sobel has authored 74 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Genetics, 31 papers in Molecular Biology and 11 papers in Oncology. Recurrent topics in Eric M. Sobel's work include Genetic Associations and Epidemiology (32 papers), Genetic Mapping and Diversity in Plants and Animals (23 papers) and Genetic and phenotypic traits in livestock (15 papers). Eric M. Sobel is often cited by papers focused on Genetic Associations and Epidemiology (32 papers), Genetic Mapping and Diversity in Plants and Animals (23 papers) and Genetic and phenotypic traits in livestock (15 papers). Eric M. Sobel collaborates with scholars based in United States, United Kingdom and Finland. Eric M. Sobel's co-authors include Kenneth Lange, Jeanette C. Papp, Tong Tong Wu, Trevor Hastie, Mark Lathrop, Hugo M. Martínez, Robert C. Elston, Janet S. Sinsheimer, Daniel E. Weeks and Muriel Meier and has published in prestigious journals such as Nucleic Acids Research, Nature Genetics and Journal of Neuroscience.

In The Last Decade

Eric M. Sobel

73 papers receiving 4.1k 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.

Descent graphs in pedigree analysis: applications to haplotyping, location scores, and marker-sharing statistics.

1996 961 citations Eric M. Sobel, Kenneth Lange profile →
Identification of the gene altered in Berardinelli–Seip congenital lipodystrophy on chromosome 11q13

2001 560 citations Jocelyne Magré, Marc Délepine et al. Nature Genetics profile →
Genome-wide association analysis by lasso penalized logistic regression

2009 526 citations Eric M. Sobel, Kenneth Lange et al. Bioinformatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eric M. Sobel United States	24	1.9k	1.9k	374	338	244	74	4.2k
Anne E. Kwitek United States	34	2.0k 1.1×	1.5k 0.8×	214 0.6×	651 1.9×	393 1.6×	125	4.5k
Samuel S. Chong Singapore	35	2.1k 1.1×	1.2k 0.7×	394 1.1×	331 1.0×	170 0.7×	167	4.8k
Massimo Carella Italy	39	2.9k 1.5×	1.1k 0.6×	249 0.7×	542 1.6×	231 0.9×	225	6.1k
Alfredo Ciccodicola Italy	36	3.3k 1.7×	1.1k 0.6×	429 1.1×	282 0.8×	202 0.8×	101	4.4k
Matthew DeFelice United States	5	2.0k 1.0×	2.4k 1.3×	121 0.3×	403 1.2×	358 1.5×	7	5.1k
Stuart MacGregor Australia	42	1.5k 0.8×	2.1k 1.1×	194 0.5×	335 1.0×	580 2.4×	187	5.7k
Brendan Blumenstiel United States	8	2.1k 1.1×	2.4k 1.3×	133 0.4×	406 1.2×	363 1.5×	12	5.4k
Harald H.H. Göring United States	40	2.2k 1.1×	2.1k 1.1×	331 0.9×	582 1.7×	528 2.2×	147	5.9k
P. Naresh Kumar United States	5	3.7k 2.0×	2.5k 1.3×	403 1.1×	279 0.8×	312 1.3×	7	6.5k
J Ott United States	7	2.1k 1.1×	2.2k 1.2×	276 0.7×	250 0.7×	188 0.8×	8	4.5k

Countries citing papers authored by Eric M. Sobel

Since Specialization

Citations

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

Fields of papers citing papers by Eric M. Sobel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric M. Sobel

This figure shows the co-authorship network connecting the top 25 collaborators of Eric M. Sobel. A scholar is included among the top collaborators of Eric M. Sobel 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 Eric M. Sobel. Eric M. Sobel 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

Sobel, Eric M., et al.. (2024). Estimation of genetic admixture proportions via haplotypes. Computational and Structural Biotechnology Journal. 23. 4384–4395.

Peterson, Daniel G., Jeanette C. Papp, David H. Alexander, et al.. (2023). Unsupervised discovery of ancestry-informative markers and genetic admixture proportions in biobank-scale datasets. The American Journal of Human Genetics. 110(2). 314–325. 4 indexed citations

Sobel, Eric M., et al.. (2021). A fast data-driven method for genotype imputation, phasing and local ancestry inference: MendelImpute.jl. Bioinformatics. 37(24). 4756–4763. 4 indexed citations

German, Chris, Kenneth Lange, Janet S. Sinsheimer, et al.. (2021). Modern simulation utilities for genetic analysis. BMC Bioinformatics. 22(1). 228–228. 2 indexed citations

Keys, Kevin L., Chris German, Hua Zhou, et al.. (2020). Iterative hard thresholding in genome-wide association studies: Generalized linear models, prior weights, and double sparsity. GigaScience. 9(6). 10 indexed citations

Jung, Su Yon, Peter Scott, Jeanette C. Papp, et al.. (2020). Genome-wide Association Analysis of Proinflammatory Cytokines and Gene–lifestyle Interaction for Invasive Breast Cancer Risk: The WHI dbGaP Study. Cancer Prevention Research. 14(1). 41–54. 15 indexed citations

Jung, Su Yon, Jeanette C. Papp, Eric M. Sobel, Herbert Yu, & Zuo‐Feng Zhang. (2019). Breast Cancer Risk and Insulin Resistance: Post Genome-Wide Gene–Environment Interaction Study Using a Random Survival Forest. Cancer Research. 79(10). 2784–2794. 19 indexed citations

Jung, Su Yon, Jeanette C. Papp, Eric M. Sobel, & Zuo‐Feng Zhang. (2019). Post Genome-Wide Gene–Environment Interaction Study Using Random Survival Forest: Insulin Resistance, Lifestyle Factors, and Colorectal Cancer Risk. Cancer Prevention Research. 12(12). 877–890. 5 indexed citations

Jung, Su Yon, Nicholas Mancuso, Jeanette C. Papp, Eric M. Sobel, & Zuo‐Feng Zhang. (2019). Post genome-wide gene-environment interaction study: The effect of genetically driven insulin resistance on breast cancer risk using Mendelian randomization. PLoS ONE. 14(6). e0218917–e0218917. 8 indexed citations

10.

Jung, Su Yon, Nicholas Mancuso, Herbert Yu, et al.. (2018). Genome-Wide Meta-analysis of Gene–Environmental Interaction for Insulin Resistance Phenotypes and Breast Cancer Risk in Postmenopausal Women. Cancer Prevention Research. 12(1). 31–42. 12 indexed citations

11.

Jung, Su Yon, Jeanette C. Papp, Eric M. Sobel, & Zuo‐Feng Zhang. (2017). Genetic Variants in Metabolic Signaling Pathways and Their Interaction with Lifestyle Factors on Breast Cancer Risk: A Random Survival Forest Analysis. Cancer Prevention Research. 11(1). 44–51. 4 indexed citations

12.

Clark, Michelle M., Olympe Chazara, Eric M. Sobel, et al.. (2016). Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes. Human Heredity. 81(4). 181–193. 9 indexed citations

13.

Chang, Jonathan, Calvin Pan, Eric M. Sobel, et al.. (2015). Genome-wide ultraconserved elements exhibit higher phylogenetic informativeness than traditional gene markers in percomorph fishes. Molecular Phylogenetics and Evolution. 92. 140–146. 58 indexed citations

14.

Childs, Erica J., Eric M. Sobel, Christina G.S. Palmer, & Janet S. Sinsheimer. (2011). Detection of Intergenerational Genetic Effects with Application to HLA-B Matching as a Risk Factor for Schizophrenia. Human Heredity. 72(3). 161–172. 7 indexed citations

15.

Presson, Angela P., Eric M. Sobel, Päivi Pajukanta, et al.. (2008). Merging microsatellite data: enhanced methodology and software to combine genotype data for linkage and association analysis. BMC Bioinformatics. 9(1). 317–317. 5 indexed citations

16.

Brock, Guy, Daniel E. Weeks, Eric M. Sobel, & Eleanor Feingold. (2007). A hierarchical model for estimating significance levels of non‐parametric linkage statistics for large pedigrees. Genetic Epidemiology. 31(5). 417–430. 1 indexed citations

17.

Lesueur, Fabienne, Caroline Lefèvre, Cristina Has, et al.. (2007). Confirmation of Psoriasis Susceptibility Loci on Chromosome 6p21 and 20p13 in French Families. Journal of Investigative Dermatology. 127(6). 1403–1409. 20 indexed citations

18.

Anttila, Verneri, Mikko Kallela, Mari Kaunisto, et al.. (2006). Trait Components Provide Tools to Dissect the Genetic Susceptibility of Migraine. The American Journal of Human Genetics. 79(1). 85–99. 54 indexed citations

19.

Lilja, Heidi E., Elina Suviolahti, Aino Soro‐Paavonen, et al.. (2004). Locus for quantitative HDL-cholesterol on chromosome 10q in Finnish families with dyslipidemia. Journal of Lipid Research. 45(10). 1876–1884. 23 indexed citations

20.

Magré, Jocelyne, Marc Délepine, Eliane Khallouf, et al.. (2001). Identification of the gene altered in Berardinelli–Seip congenital lipodystrophy on chromosome 11q13. Nature Genetics. 28(4). 365–370. 560 indexed citations breakdown →

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