Martin L. Ferguson

93.4k citations
9 papers · 748 indexed · h-index 6

Martin L. Ferguson

8 papers receiving 735 citations

Peers

Martin L. Ferguson
Comparison fields: 5 of 77
  • Immunology 360
  • Hematology 131
  • Oncology 139
  • Space and Planetary Science 6
  • Epidemiology 145
Replace Marion Larroque with:
Marion Larroque France
Jayshree J. Nadkarni India
Diana Paola Granados Canada
HG Drexler Germany
G.C. Spagnoli Switzerland
Deborah Ferriola United States
Vernon M. Coffield United States
AF Gazdar United States
Vasco M. Barreto Portugal
Paula Ladne United States
Martin L. Ferguson relative to Marion Larroque France Marion Larroque's profile →
Citations per field
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Citations per year

Countries citing papers authored by Martin L. Ferguson

Since Specialization
Citations

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

Fields of papers citing papers by Martin L. Ferguson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin L. Ferguson. 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 Martin L. Ferguson. The network helps show where Martin L. Ferguson may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Martin L. Ferguson, 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 Martin L. Ferguson Line = papers co-authored together Martin L. Ferguson links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
epiDonate - distributed serverless data infrastructure for epidemiological studies.
20230
2 201726
3 201732
4 19994
5 1998409
6 19964
7 1992135
8 1992125
9 198613

About Martin L. Ferguson

Martin L. Ferguson is a scholar working on Toxicology, Information Systems and Management, Geriatrics and Gerontology, Health Information Management and Emergency Medical Services, having authored 9 papers that have together received 748 indexed citations. Recurring topics across this work include DNA and Nucleic Acid Chemistry (2 papers), Scientific Computing and Data Management (2 papers), Pharmacovigilance and Adverse Drug Reactions (1 paper), Artificial Intelligence in Healthcare (1 paper), Mast cells and histamine (1 paper), Advanced biosensing and bioanalysis techniques (1 paper), Insect symbiosis and bacterial influences (1 paper) and Research Data Management Practices (1 paper). The work is most often cited by research in Immunology (360 citations), Hematology (131 citations), Oncology (139 citations), Space and Planetary Science (6 citations) and Epidemiology (145 citations). Martin L. Ferguson has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include David C. Ward, Amy Bernard, Seth Levitz, William L. Gerald, Michael Krainer, Daniel A. Haber, D. Paul Harkin, Jennifer Ashley, Marcus B. Valentine and Lin Zuo. Their work appears in journals such as Chromosoma, Earth-Science Reviews, Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

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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