Dana Weekes
Impact in
- Virology top 10%
- HIV Research and Treatment
-
- Microbial Metabolic Engineering and Bioproduction
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
Papers in
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- Bioinformatics and Genomic Networks 2
- RNA modifications and cancer 2
- RNA and protein synthesis mechanisms 2
- RNA Research and Splicing 1
- Gene expression and cancer classification 1
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- Enzyme Structure and Function 3
- Co-authors
- Gary B. Fogel (4 shared papers)Adam Godzik (6 shared papers)Ian A. Wilson (5 shared papers)Zhanwen Li (2 shared papers)John Wooley (3 shared papers)Scott A. Lesley (3 shared papers)Lukasz Jaroszewski (3 shared papers)Ashley M. Deacon (3 shared papers)
- Journals
- Biosystems (3 papers)PLoS ONE (1 paper)Nucleic Acids Research (1 paper)Science (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- United StatesJapanPoland
In The Last Decade
Dana Weekes
10 papers receiving 350 citations
Peers
Comparison fields: 5 of 73
- Virology 41
- Molecular Biology 243
- Computational Theory and Mathematics 46
- Aging 3
- Infectious Diseases 26
Countries citing papers authored by Dana Weekes
This map shows the geographic impact of Dana Weekes'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 Dana Weekes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dana Weekes more than expected).
Fields of papers citing papers by Dana Weekes
This network shows the impact of papers produced by Dana Weekes. 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 Dana Weekes. The network helps show where Dana Weekes may publish in the future.
Co-authors
The 25 scholars most cited alongside Dana Weekes, 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 | 2009 | 147 | |
| 2 | 2013 | 52 | |
| 3 | 2003 | 37 | |
| 4 | 2005 | 34 | |
| 5 | 2010 | 31 | |
| 6 | 2011 | 17 | |
| 7 | 2004 | 14 | |
| 8 | 2010 | 13 | |
| 9 | 2010 | 8 | |
| 10 | 2004 | 5 |
About Dana Weekes
Dana Weekes is a scholar working on Molecular Biology, Materials Chemistry, Virology, Information Systems and Management and Clinical Biochemistry, having authored 10 papers that have together received 358 indexed citations. Recurring topics across this work include Enzyme Structure and Function (3 papers), Bioinformatics and Genomic Networks (2 papers), RNA modifications and cancer (2 papers), RNA and protein synthesis mechanisms (2 papers), RNA Research and Splicing (1 paper), AI-based Problem Solving and Planning (1 paper), Gene expression and cancer classification (1 paper) and Metabolism and Genetic Disorders (1 paper). The work is most often cited by research in Virology (41 citations), Molecular Biology (243 citations), Computational Theory and Mathematics (46 citations), Aging (3 citations) and Infectious Diseases (26 citations). Dana Weekes has collaborated with scholars based in United States, Japan and Poland. Frequent co-authors include Gary B. Fogel, Adam Godzik, Ian A. Wilson, Zhanwen Li, John Wooley, Scott A. Lesley, Lukasz Jaroszewski, Ashley M. Deacon, Ines Thiele and Ying Zhang. Their work appears in journals such as Biosystems, PLoS ONE, Nucleic Acids Research, Science and BMC 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.