Daniel Dvorkin
Impact in
- Genetics top 10%
- Genetic Mapping and Diversity in Plants and Animals
- Genetic and phenotypic traits in livestock
- Genetic Associations and Epidemiology
- High Altitude and Hypoxia
Papers in
-
- Bioinformatics and Genomic Networks 4
- Genetics 6
- Genetic and phenotypic traits in livestock 3
- Genetic Associations and Epidemiology 2
- Genetic Mapping and Diversity in Plants and Animals 2
- High Altitude and Hypoxia 2
- Co-authors
- Yang Da (2 shared papers)John Garbe (2 shared papers)Li Ma (1 shared paper)Hakizumwami Birali Runesha (1 shared paper)Shengwen Wang (1 shared paper)Li Ma (2 shared papers)Lawrence Hunter (1 shared paper)Karin Verspoor (1 shared paper)
- Journals
- BMC Bioinformatics (2 papers)Artificial Intelligence in Medicine (1 paper)Statistical Applications in Genetics and Molecular Biology (1 paper)Journal of Proteome Research (1 paper)Bioinformatics (1 paper)
- Partner nations
- United StatesAustraliaIndia
In The Last Decade
Daniel Dvorkin
13 papers receiving 355 citations
Peers
Comparison fields: 5 of 74
- Genetics 189
- Speech and Hearing 22
- Cancer Research 48
- Physiology 57
- Molecular Biology 143
Countries citing papers authored by Daniel Dvorkin
This map shows the geographic impact of Daniel Dvorkin'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 Dvorkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Dvorkin more than expected).
Fields of papers citing papers by Daniel Dvorkin
This network shows the impact of papers produced by Daniel Dvorkin. 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 Dvorkin. The network helps show where Daniel Dvorkin may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Dvorkin, 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 | 2016 | 95 | |
| 2 | 2008 | 87 | |
| 3 | 2006 | 47 | |
| 4 | 2012 | 45 | |
| 5 | 2009 | 32 | |
| 6 | 2020 | 20 | |
| 7 | 2020 | 12 | |
| 8 | 2021 | 9 | |
| 9 | 2007 | 8 | |
| 10 | 2013 | 5 | |
| 11 | 2005 | 1 | |
| 12 | 2021 | 1 | |
| 13 | 2014 | 1 |
About Daniel Dvorkin
Daniel Dvorkin is a scholar working on Molecular Biology, Genetics, Physiology, Surgery and Pulmonary and Respiratory Medicine, having authored 13 papers that have together received 363 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Genetic and phenotypic traits in livestock (3 papers), Genetic Associations and Epidemiology (2 papers), Genetic Mapping and Diversity in Plants and Animals (2 papers), Dysphagia Assessment and Management (2 papers), Esophageal and GI Pathology (2 papers), Cancer, Hypoxia, and Metabolism (2 papers) and High Altitude and Hypoxia (2 papers). The work is most often cited by research in Genetics (189 citations), Speech and Hearing (22 citations), Cancer Research (48 citations), Physiology (57 citations) and Molecular Biology (143 citations). Daniel Dvorkin has collaborated with scholars based in United States, Australia and India. Frequent co-authors include Yang Da, John Garbe, Li Ma, Hakizumwami Birali Runesha, Shengwen Wang, Li Ma, Yang Da, Lawrence Hunter, Karin Verspoor and Kevin Bretonnel Cohen. Their work appears in journals such as BMC Bioinformatics, Artificial Intelligence in Medicine, Statistical Applications in Genetics and Molecular Biology, Journal of Proteome Research and Bioinformatics.
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.