Dawn E. Wilkins
Impact in
- Hematology top 2%
- Acute Myeloid Leukemia Research
- Chronic Myeloid Leukemia Treatments
-
- Acute Lymphoblastic Leukemia research
Papers in
-
- Machine Learning and Algorithms 5
- Algorithms and Data Compression 4
- Co-authors
- Xiaofei Nan (8 shared papers)Zhendong Zhao (4 shared papers)Yuanyuan Ding (3 shared papers)Pamela B. Lawhead (3 shared papers)Michael Macias (1 shared paper)Yixin Chen (1 shared paper)Krishnan Pillaipakkamnatt (4 shared papers)Vijay Raghavan (3 shared papers)
- Journals
- BMC Bioinformatics (8 papers)BMC Genomics (2 papers)Pattern Recognition (2 papers)Genes (1 paper)DNA and Cell Biology (1 paper)
- Partner nations
- United StatesChinaFrance
In The Last Decade
Dawn E. Wilkins
45 papers receiving 2.3k citations
Dawn E. Wilkins's Hit Papers
Peers
Comparison fields: 5 of 147
- Hematology 435
- Public Health, Environmental and Occupational Health 515
- Molecular Biology 1.0k
- Artificial Intelligence 464
- Computer Vision and Pattern Recognition 261
Countries citing papers authored by Dawn E. Wilkins
This map shows the geographic impact of Dawn E. Wilkins'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 Dawn E. Wilkins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dawn E. Wilkins more than expected).
Fields of papers citing papers by Dawn E. Wilkins
This network shows the impact of papers produced by Dawn E. Wilkins. 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 Dawn E. Wilkins. The network helps show where Dawn E. Wilkins may publish in the future.
Co-authors
The 25 scholars most cited alongside Dawn E. Wilkins, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling Hit paper breakdown → | 2002 | 1560 |
| 2 | 2010 | 264 | |
| 3 | 2006 | 74 | |
| 4 | 1996 | 67 | |
| 5 | 2016 | 62 | |
| 6 | 2000 | 57 | |
| 7 | 2018 | 35 | |
| 8 | 2012 | 29 | |
| 9 | 2013 | 23 | |
| 10 | 2016 | 22 | |
| 11 | 2000 | 22 | |
| 12 | 1997 | 21 | |
| 13 | 2014 | 18 | |
| 14 | 2019 | 15 | |
| 15 | 1998 | 14 | |
| 16 | 2009 | 14 | |
| 17 | 2019 | 13 | |
| 18 | 1995 | 13 | |
| 19 | 2007 | 13 | |
| 20 | 2004 | 12 |
About Dawn E. Wilkins
Dawn E. Wilkins is a scholar working on Artificial Intelligence, Computer Science Applications, Molecular Biology, Computational Theory and Mathematics and Computer Networks and Communications, having authored 51 papers that have together received 2.4k indexed citations. Recurring topics across this work include Gene expression and cancer classification (12 papers), Bioinformatics and Genomic Networks (9 papers), Machine Learning and Algorithms (5 papers), Algorithms and Data Compression (4 papers), Machine Learning in Bioinformatics (4 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers), Genomics and Phylogenetic Studies (3 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Hematology (435 citations), Public Health, Environmental and Occupational Health (515 citations), Molecular Biology (1.0k citations), Artificial Intelligence (464 citations) and Computer Vision and Pattern Recognition (261 citations). Dawn E. Wilkins has collaborated with scholars based in United States, China and France. Frequent co-authors include Xiaofei Nan, Zhendong Zhao, Yuanyuan Ding, Pamela B. Lawhead, Michael Macias, Yixin Chen, Krishnan Pillaipakkamnatt, Vijay Raghavan, Christopher Ma and Lisa Hellerstein. Their work appears in journals such as BMC Bioinformatics, BMC Genomics, Pattern Recognition, Genes and DNA and Cell Biology.
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.