Nicholas Miliaras
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
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- Cellular transport and secretion
Papers in
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- Biomedical Text Mining and Ontologies 4
- Bioinformatics and Genomic Networks 3
- CRISPR and Genetic Engineering 2
- Ubiquitin and proteasome pathways 1
- Gene expression and cancer classification 1
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- Microtubule and mitosis dynamics 2
- Cellular transport and secretion 2
- Co-authors
- Beverly Wendland (3 shared papers)Craig C. Mello (1 shared paper)Jungsoon Lee (1 shared paper)Tae Ho Shin (1 shared paper)Anatoli B. Meriin (1 shared paper)Michael Y. Sherman (1 shared paper)J. Michael McCaffery (1 shared paper)Yury O. Chernoff (1 shared paper)
- Journals
- Database (2 papers)Traffic (1 paper)Current Opinion in Cell Biology (1 paper)Journal of Biomedical Informatics (1 paper)Cell Biochemistry and Biophysics (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Nicholas Miliaras
10 papers receiving 366 citations
Peers
Comparison fields: 5 of 48
- Aging 102
- Cell Biology 96
- Molecular Biology 307
- Cellular and Molecular Neuroscience 63
- Endocrine and Autonomic Systems 11
Countries citing papers authored by Nicholas Miliaras
This map shows the geographic impact of Nicholas Miliaras'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 Nicholas Miliaras with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Miliaras more than expected).
Fields of papers citing papers by Nicholas Miliaras
This network shows the impact of papers produced by Nicholas Miliaras. 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 Nicholas Miliaras. The network helps show where Nicholas Miliaras may publish in the future.
Co-authors
The 21 scholars most cited alongside Nicholas Miliaras, 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 | 2002 | 165 | |
| 2 | 2003 | 94 | |
| 3 | 2004 | 44 | |
| 4 | 2021 | 25 | |
| 5 | 2004 | 21 | |
| 6 | 2008 | 15 | |
| 7 | 2022 | 5 | |
| 8 | 2014 | 3 | |
| 9 | 2024 | 2 | |
| 10 | 2024 | 1 | |
| 11 | 2014 | 0 | |
| 12 | 2014 | 0 |
About Nicholas Miliaras
Nicholas Miliaras is a scholar working on Molecular Biology, Cell Biology, Artificial Intelligence, Cellular and Molecular Neuroscience and Computational Theory and Mathematics, having authored 12 papers that have together received 375 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Bioinformatics and Genomic Networks (3 papers), Microtubule and mitosis dynamics (2 papers), Cellular transport and secretion (2 papers), CRISPR and Genetic Engineering (2 papers), Ubiquitin and proteasome pathways (1 paper), Gene expression and cancer classification (1 paper) and Genetically Modified Organisms Research (1 paper). The work is most often cited by research in Aging (102 citations), Cell Biology (96 citations), Molecular Biology (307 citations), Cellular and Molecular Neuroscience (63 citations) and Endocrine and Autonomic Systems (11 citations). Nicholas Miliaras has collaborated with scholars based in United States and China. Frequent co-authors include Beverly Wendland, Craig C. Mello, Jungsoon Lee, Tae Ho Shin, Anatoli B. Meriin, Michael Y. Sherman, J. Michael McCaffery, Yury O. Chernoff, Nina Peel and Mi Hye Song. Their work appears in journals such as Database, Traffic, Current Opinion in Cell Biology, Journal of Biomedical Informatics and Cell Biochemistry and Biophysics.
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.