Daniel Sylvester

1.2k citations
18 papers · 1.1k · h-index 14

Impact in

Papers in

    • Signaling Pathways in Disease 3
    • Glycosylation and Glycoproteins Research 2
    • Bacterial Genetics and Biotechnology 4

Daniel Sylvester

18 papers receiving 1.0k citations

Peers

Daniel Sylvester
Comparison fields: 5 of 90
  • Molecular Medicine 71
  • Immunology 221
  • Molecular Biology 689
  • Infectious Diseases 165
  • Virology 37
Replace Gaétan Burgio with:
Gaétan Burgio Australia
Masami Miyake Japan
Saman Habib India
Danielle Desjardins United States
Andrea Riehle Germany
Alyson Swimm United States
Paul O’Donnell Australia
A Brown United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Sylvester

Since Specialization
Citations

This map shows the geographic impact of Daniel Sylvester'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 Sylvester with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Sylvester more than expected).

Fields of papers citing papers by Daniel Sylvester

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Sylvester. 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 Sylvester. The network helps show where Daniel Sylvester may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Sylvester, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Sylvester Line = papers co-authored together Daniel Sylvester links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 1991171
2 1993142
3 1994116
4 2000113
5 199683
6 200074
7 200373
8 199063
9 199258
10 199334
11
T-cell receptor genes and insulin-dependent diabetes mellitus (IDDM): no evidence for linkage from affected sib pairs.
199034
12 200129
13 198927
14 199020
15 200112
16 20018
17 20205
18 19911

About Daniel Sylvester

Daniel Sylvester is a scholar working on Molecular Biology, Genetics, Immunology, Public Health, Environmental and Occupational Health and Virology, having authored 18 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (4 papers), Signaling Pathways in Disease (3 papers), Nitric Oxide and Endothelin Effects (2 papers), Glycosylation and Glycoproteins Research (2 papers), Force Microscopy Techniques and Applications (2 papers), Malaria Research and Control (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers) and Antibiotic Resistance in Bacteria (2 papers). The work is most often cited by research in Molecular Medicine (71 citations), Immunology (221 citations), Molecular Biology (689 citations), Infectious Diseases (165 citations) and Virology (37 citations). Daniel Sylvester has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include Derk J. Bergsma, Mitchell Gross, Nabil A. Elshourbagy, John E. Hodgson, K. G. H. Dyke, Roy O. Morris, S.P. Curnock, G P Livi, Edward R. Appelbaum and Megan M. McLaughlin. Their work appears in journals such as Journal of Bacteriology, Biochemical Journal, Nucleic Acids Research, Journal of Biological Chemistry and Gene.

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.

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