Daryl Waggott
Impact in
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Genetics top 10%
- Genomics and Rare Diseases
- Genomic variations and chromosomal abnormalities
Papers in
-
- RNA modifications and cancer 3
- Gene expression and cancer classification 2
- Circular RNAs in diseases 2
- Genetics 8
- Genomics and Rare Diseases 4
- Genetic Associations and Epidemiology 2
- Co-authors
- Paul C. Boutros (9 shared papers)Euan A. Ashley (9 shared papers)Fei‐Fei Liu (5 shared papers)Matthew T. Wheeler (7 shared papers)Bradly G. Wouters (1 shared paper)Kenneth C. Chu (1 shared paper)Megan E. Grove (4 shared papers)Anna Shcherbina (3 shared papers)
- Journals
- Bioinformatics (1 paper)Oncotarget (1 paper)Scientific Data (1 paper)PLoS Genetics (1 paper)Molecular & Cellular Proteomics (1 paper)
- Partner nations
- United StatesCanadaSweden
In The Last Decade
Daryl Waggott
18 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 121
- Cancer Research 295
- Genetics 305
- Molecular Biology 412
- Otorhinolaryngology 18
- Aging 6
Countries citing papers authored by Daryl Waggott
This map shows the geographic impact of Daryl Waggott'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 Daryl Waggott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daryl Waggott more than expected).
Fields of papers citing papers by Daryl Waggott
This network shows the impact of papers produced by Daryl Waggott. 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 Daryl Waggott. The network helps show where Daryl Waggott may publish in the future.
Co-authors
The 25 scholars most cited alongside Daryl Waggott, 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 | 2015 | 190 | |
| 2 | 2012 | 180 | |
| 3 | 2017 | 166 | |
| 4 | 2016 | 96 | |
| 5 | 2012 | 74 | |
| 6 | 2018 | 71 | |
| 7 | 2019 | 57 | |
| 8 | 2015 | 54 | |
| 9 | 2019 | 52 | |
| 10 | 2015 | 28 | |
| 11 | 2016 | 24 | |
| 12 | 2014 | 18 | |
| 13 | 2019 | 16 | |
| 14 | 2016 | 16 | |
| 15 | 2015 | 13 | |
| 16 | 2013 | 7 | |
| 17 | 2016 | 4 | |
| 18 | Genomic Region Processing using Tools Such as 'BEDTools', 'BEDOPS' and 'Tabix' [R package bedr version 1.0.7] | 2019 | 2 |
About Daryl Waggott
Daryl Waggott is a scholar working on Molecular Biology, Genetics, Cancer Research, Surgery and Cardiology and Cardiovascular Medicine, having authored 18 papers that have together received 1.1k indexed citations. Recurring topics across this work include Genomics and Rare Diseases (4 papers), RNA modifications and cancer (3 papers), Gene expression and cancer classification (2 papers), Circular RNAs in diseases (2 papers), Physical Activity and Health (2 papers), MicroRNA in disease regulation (2 papers), Genetic Associations and Epidemiology (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Cancer Research (295 citations), Genetics (305 citations), Molecular Biology (412 citations), Otorhinolaryngology (18 citations) and Aging (6 citations). Daryl Waggott has collaborated with scholars based in United States, Canada and Sweden. Frequent co-authors include Paul C. Boutros, Euan A. Ashley, Fei‐Fei Liu, Matthew T. Wheeler, Bradly G. Wouters, Kenneth C. Chu, Megan E. Grove, Anna Shcherbina, James R. Priest and Marc Salit. Their work appears in journals such as Bioinformatics, Oncotarget, Scientific Data, PLoS Genetics and Molecular & Cellular Proteomics.
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.