George S. Michaels
- Molecular Biology top 10%
- RNA and protein synthesis mechanisms 4
- Genomics and Phylogenetic Studies 3
- Mitochondrial Function and Pathology 2
- Gene Regulatory Network Analysis 2
- Epigenetics and DNA Methylation 2
- Bioinformatics and Genomic Networks 2
- Gene expression and cancer classification 2
- RNA modifications and cancer 1
- Clinical Biochemistry top 5%
- Artificial Intelligence top 10%
- Co-authors
- Stefanie FuhrmanRoland SomogyiDaniel B. CarrXiling WenSusan V. SmithJeffery L. BarkerWilliam W. HauswirthP.J. Laipis
- Partner nations
- United States
In The Last Decade
George S. Michaels
12 papers receiving 881 citations
Peers
Comparison fields: 5 of 109
- Molecular Biology 794
- Clinical Biochemistry 72
- Aging 10
- Genetics 118
- Artificial Intelligence 116
Countries citing papers authored by George S. Michaels
This map shows the geographic impact of George S. Michaels'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 George S. Michaels with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George S. Michaels more than expected).
Fields of papers citing papers by George S. Michaels
This network shows the impact of papers produced by George S. Michaels. 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 George S. Michaels. The network helps show where George S. Michaels may publish in the future.
Co-authorship network
The 25 scholars most cited alongside George S. Michaels, 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 | 2004 | 14 | |
| 2 | 2002 | 0 | |
| 3 | Genetic network inference | 2000 | 10 |
| 4 | Cluster analysis and data visualization of large-scale gene expression data. | 1998 | 137 |
| 5 | 1998 | 16 | |
| 6 | 1998 | 471 | |
| 7 | 1993 | 3 | |
| 8 | 1989 | 28 | |
| 9 | 1988 | 90 | |
| 10 | 1985 | 3 | |
| 11 | 1982 | 156 | |
| 12 | 1980 | 12 | |
| 13 | 1979 | 13 |
About George S. Michaels
George S. Michaels is a scholar working on Molecular Biology, Clinical Biochemistry, Information Systems and Management, Genetics and Management Science and Operations Research, having authored 13 papers that have together received 953 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (4 papers), Genomics and Phylogenetic Studies (3 papers), Mitochondrial Function and Pathology (2 papers), Gene Regulatory Network Analysis (2 papers), Epigenetics and DNA Methylation (2 papers), Bioinformatics and Genomic Networks (2 papers), Gene expression and cancer classification (2 papers) and RNA modifications and cancer (1 paper). The work is most often cited by research in Molecular Biology (794 citations), Clinical Biochemistry (72 citations), Aging (10 citations), Genetics (118 citations) and Artificial Intelligence (116 citations). George S. Michaels has collaborated with scholars based in United States. Frequent co-authors include Stefanie Fuhrman, Roland Somogyi, Daniel B. Carr, Xiling Wen, Susan V. Smith, Jeffery L. Barker, William W. Hauswirth, P.J. Laipis, Manor Askenazi and Xi Wen. Their work appears in journals such as Developmental Biology, Gene, Journal of Biological Chemistry, Journal of Theoretical Biology and Nature Biotechnology.
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.