Daniel Shegogue
Impact in
- Dermatology top 10%
- Dermatologic Treatments and Research
- Nephrology top 10%
Papers in
-
- Connective Tissue Growth Factor Research 3
- Protein Kinase Regulation and GTPase Signaling 2
- Bioinformatics and Genomic Networks 2
- Gene Regulatory Network Analysis 2
- Kruppel-like factors research 1
-
- Systemic Sclerosis and Related Diseases 3
- Co-authors
- Maria Trojanowska (6 shared papers)Edwin A. Smith (2 shared papers)Gary R. Grotendorst (1 shared paper)Paul J. McDermott (1 shared paper)Debra J. Hazen‐Martin (1 shared paper)Eddie L. Greene (1 shared paper)M Markiewicz (1 shared paper)W. Jim Zheng (2 shared papers)
- Journals
- Bioinformatics (2 papers)Journal of Biological Chemistry (2 papers)Matrix Biology (1 paper)BMC Bioinformatics (1 paper)American Journal of Physiology-Renal Physiology (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Daniel Shegogue
9 papers receiving 546 citations
Peers
Comparison fields: 5 of 75
- Dermatology 63
- Nephrology 44
- Cell Biology 83
- Molecular Biology 349
- Pathology and Forensic Medicine 86
Countries citing papers authored by Daniel Shegogue
This map shows the geographic impact of Daniel Shegogue'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 Daniel Shegogue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Shegogue more than expected).
Fields of papers citing papers by Daniel Shegogue
This network shows the impact of papers produced by Daniel Shegogue. 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 Daniel Shegogue. The network helps show where Daniel Shegogue may publish in the future.
Co-authors
The 18 scholars most cited alongside Daniel Shegogue, 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 | 2002 | 133 | |
| 2 | 2004 | 130 | |
| 3 | 2004 | 106 | |
| 4 | 2002 | 100 | |
| 5 | 2001 | 28 | |
| 6 | 2004 | 28 | |
| 7 | 2005 | 20 | |
| 8 | 2005 | 9 | |
| 9 | 2004 | 3 |
About Daniel Shegogue
Daniel Shegogue is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Genetics, Urology and Information Systems and Management, having authored 9 papers that have together received 557 indexed citations. Recurring topics across this work include Systemic Sclerosis and Related Diseases (3 papers), Connective Tissue Growth Factor Research (3 papers), Dermatological and Skeletal Disorders (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Bioinformatics and Genomic Networks (2 papers), Gene Regulatory Network Analysis (2 papers), Kruppel-like factors research (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Dermatology (63 citations), Nephrology (44 citations), Cell Biology (83 citations), Molecular Biology (349 citations) and Pathology and Forensic Medicine (86 citations). Daniel Shegogue has collaborated with scholars based in United States and Japan. Frequent co-authors include Maria Trojanowska, Edwin A. Smith, Gary R. Grotendorst, Paul J. McDermott, Debra J. Hazen‐Martin, Eddie L. Greene, M Markiewicz, W. Jim Zheng, Yusuf A. Hannun and Benjamin J. Pettus. Their work appears in journals such as Bioinformatics, Journal of Biological Chemistry, Matrix Biology, BMC Bioinformatics and American Journal of Physiology-Renal Physiology.
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.