Daniel Stafford

855 citations
10 papers · 765 · h-index 8

Impact in

Papers in

    • Microbial Metabolic Engineering and Bioproduction 4
    • Enzyme Catalysis and Immobilization 3
    • Viral Infectious Diseases and Gene Expression in Insects 1
    • Cell death mechanisms and regulation 1
    • Pharmacogenetics and Drug Metabolism 3

Daniel Stafford

10 papers receiving 744 citations

Peers

Daniel Stafford
Comparison fields: 5 of 90
  • Cell Biology 251
  • Cellular and Molecular Neuroscience 146
  • Molecular Biology 530
  • Organic Chemistry 145
  • Toxicology 14
Replace Irene de Miguel with:
Irene de Miguel Spain
Seung‐Shick Shin South Korea
Shinichiro Atsumi Japan
P M Blumberg United States
Robert A. Lepley United States
Kuniaki Sano Japan
Kohei Hosaka Japan
Marina Y. Pushkareva United States
N Kajikawa Japan
Chin‐Chun Hung Taiwan
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Citations per field
00.5×4.6×
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Citations per year

Countries citing papers authored by Daniel Stafford

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Stafford

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Daniel Stafford, 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 Stafford Line = papers co-authored together Daniel Stafford links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 1996395
2 1998149
3 1996108
4 200131
5 200225
6 200224
7 200118
8 200110
9
Machine learning in option pricing
20193
10 20182

About Daniel Stafford

Daniel Stafford is a scholar working on Molecular Biology, Pharmacology, Cell Biology, Pharmaceutical Science and Physiology, having authored 10 papers that have together received 765 indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (4 papers), Pharmacogenetics and Drug Metabolism (3 papers), Enzyme Catalysis and Immobilization (3 papers), Calpain Protease Function and Regulation (2 papers), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Stock Market Forecasting Methods (1 paper), Adenosine and Purinergic Signaling (1 paper) and Cell death mechanisms and regulation (1 paper). The work is most often cited by research in Cell Biology (251 citations), Cellular and Molecular Neuroscience (146 citations), Molecular Biology (530 citations), Organic Chemistry (145 citations) and Toxicology (14 citations). Daniel Stafford has collaborated with scholars based in United States. Frequent co-authors include Rathna Nath, Kadee J. Raser, Kevin Wang, Hamish Allen, Avigail Posner, Po‐wai Yuen, Iradj Hajimohammadreza, Robert V. Talanian, Richard B. Gilbertsen and Gregory Stephanopoulos. Their work appears in journals such as Neuroreport, Journal of Medicinal Chemistry, Current Opinion in Microbiology, Biochemical Journal and European Journal of Biochemistry.

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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