David K. Crockett
- Toxicology top 5%
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications 9
- Mass Spectrometry Techniques and Applications 7
- Clinical Biochemistry top 5%
- Pathology and Forensic Medicine top 10%
- Lymphoma Diagnosis and Treatment 9
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- Ubiquitin and proteasome pathways 10
- Glycosylation and Glycoproteins Research 4
- Machine Learning in Bioinformatics 3
- Genomics and Phylogenetic Studies 3
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- Genomics and Rare Diseases 3
- Co-authors
- Kojo S.J. Elenitoba‐JohnsonMegan S. LimZhaosheng LinRong MaoCecily P. VaughnFernanda R.O. CalderonAlan L. RockwoodMark M. Kushnir
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Blood (2 papers)Bioinformatics (1 paper)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
David K. Crockett
49 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 98
- Toxicology 56
- Spectroscopy 221
- Clinical Biochemistry 74
- Pathology and Forensic Medicine 164
- Molecular Biology 619
Countries citing papers authored by David K. Crockett
This map shows the geographic impact of David K. Crockett'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 David K. Crockett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David K. Crockett more than expected).
Fields of papers citing papers by David K. Crockett
This network shows the impact of papers produced by David K. Crockett. 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 David K. Crockett. The network helps show where David K. Crockett may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David K. Crockett, 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 | 2023 | 1 | |
| 2 | 2023 | 5 | |
| 3 | 2013 | 16 | |
| 4 | 2012 | 4 | |
| 5 | 2011 | 27 | |
| 6 | 2011 | 6 | |
| 7 | 2010 | 74 | |
| 8 | 2009 | 102 | |
| 9 | 2008 | 31 | |
| 10 | 2007 | 32 | |
| 11 | 2007 | 14 | |
| 12 | 2007 | 85 | |
| 13 | 2006 | 11 | |
| 14 | Sequence alignment by cross-correlation. | 2005 | 17 |
| 15 | 2005 | 29 | |
| 16 | 2005 | 124 | |
| 17 | 2004 | 44 | |
| 18 | 2004 | 87 | |
| 19 | 2000 | 17 | |
| 20 | 1999 | 14 |
About David K. Crockett
David K. Crockett is a scholar working on Health Informatics, Pathology and Forensic Medicine and Spectroscopy, having authored 49 papers that have together received 1.2k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (10 papers), Advanced Proteomics Techniques and Applications (9 papers), Lymphoma Diagnosis and Treatment (9 papers), Mass Spectrometry Techniques and Applications (7 papers), Glycosylation and Glycoproteins Research (4 papers), Genomics and Rare Diseases (3 papers), Machine Learning in Bioinformatics (3 papers) and Genomics and Phylogenetic Studies (3 papers). The work is most often cited by research in Toxicology (56 citations), Spectroscopy (221 citations) and Clinical Biochemistry (74 citations). David K. Crockett has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Kojo S.J. Elenitoba‐Johnson, Megan S. Lim, Zhaosheng Lin, Rong Mao, Cecily P. Vaughn, Fernanda R.O. Calderon, Alan L. Rockwood, Mark M. Kushnir, Jonathan A. Schumacher and Rebecca L. Margraf. Their work appears in journals such as Proceedings of the National Academy of Sciences, Blood and 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.