Eric M. Sobel
- Genetics top 0.5%
- Genetic Associations and Epidemiology 32
- Genetic Mapping and Diversity in Plants and Animals 23
- Genetic and phenotypic traits in livestock 15
- Biochemistry top 2%
- Molecular Biology top 5%
- Metabolism, Diabetes, and Cancer 8
- Bioinformatics and Genomic Networks 7
- Gene expression and cancer classification 6
- Cell Biology top 5%
- Statistics and Probability top 2%
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- Cancer Risks and Factors 10
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- Cancer, Lipids, and Metabolism 8
Eric M. Sobel
73 papers receiving 4.1k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Genetics 1.9k
- Biochemistry 213
- Molecular Biology 1.9k
- Cell Biology 374
- Statistics and Probability 174
Countries citing papers authored by Eric M. Sobel
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
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
The 25 scholars most cited alongside Eric M. Sobel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2023 | 4 | |
| 3 | 2021 | 4 | |
| 4 | 2021 | 2 | |
| 5 | 2020 | 10 | |
| 6 | 2020 | 15 | |
| 7 | 2019 | 19 | |
| 8 | 2019 | 5 | |
| 9 | 2019 | 8 | |
| 10 | 2018 | 12 | |
| 11 | 2017 | 4 | |
| 12 | 2016 | 9 | |
| 13 | 2015 | 58 | |
| 14 | 2011 | 7 | |
| 15 | 2008 | 5 | |
| 16 | 2007 | 1 | |
| 17 | 2007 | 20 | |
| 18 | 2006 | 54 | |
| 19 | 2004 | 23 | |
| 20 | Identification of the gene altered in Berardinelli–Seip congenital lipodystrophy on chromosome 11q13breakdown → | 2001 | 560 |
About Eric M. Sobel
Eric M. Sobel is a scholar working on Genetics, Cancer Research, Molecular Biology, Oncology and Biological Psychiatry, having authored 74 papers that have together received 4.2k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (32 papers), Genetic Mapping and Diversity in Plants and Animals (23 papers), Genetic and phenotypic traits in livestock (15 papers), Cancer Risks and Factors (10 papers), Metabolism, Diabetes, and Cancer (8 papers), Cancer, Lipids, and Metabolism (8 papers), Bioinformatics and Genomic Networks (7 papers) and Gene expression and cancer classification (6 papers). The work is most often cited by research in Genetics (1.9k citations), Biochemistry (213 citations), Molecular Biology (1.9k citations), Cell Biology (374 citations) and Statistics and Probability (174 citations). Eric M. Sobel has collaborated with scholars based in United States, United Kingdom and Finland. Frequent 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. Their work appears in journals such as Genetic Epidemiology, Bioinformatics, Cancer Prevention Research, Human Heredity and The American Journal of Human Genetics.
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.