Thomas Todd
Impact in
- Endocrinology top 10%
- Escherichia coli research studies
- Small Animals top 10%
Papers in ⓘ
-
- vaccines and immunoinformatics approaches 4
- Biomedical Text Mining and Ontologies 3
- Machine Learning in Bioinformatics 1
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- Tuberculosis Research and Epidemiology 2
- Clostridium difficile and Clostridium perfringens research 1
- Co-authors
- Yongqun He (5 shared papers)Thomas E. Gorochowski (1 shared paper)Zuoshuang Xiang (4 shared papers)Antoni Matyjaszkiewicz (1 shared paper)Krasimira Tsaneva‐Atanasova (1 shared paper)Claire Grierson (1 shared paper)Nigel J. Savery (1 shared paper)Mario di Bernardo (1 shared paper)
- Journals
- Nucleic Acids Research (2 papers)Molecular Microbiology (1 paper)Lab Animal (1 paper)PLoS ONE (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Thomas Todd
8 papers receiving 267 citations
Peers
Comparison fields: 5 of 61
- Endocrinology 46
- Small Animals 26
- Infectious Diseases 51
- Molecular Biology 176
- Molecular Medicine 12
Countries citing papers authored by Thomas Todd
This map shows the geographic impact of Thomas Todd'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 Thomas Todd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Todd more than expected).
Fields of papers citing papers by Thomas Todd
This network shows the impact of papers produced by Thomas Todd. 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 Thomas Todd. The network helps show where Thomas Todd may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Todd, 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 | 2012 | 78 | |
| 2 | 2007 | 59 | |
| 3 | 2013 | 59 | |
| 4 | 2014 | 40 | |
| 5 | 2013 | 23 | |
| 6 | 2013 | 6 | |
| 7 | Ontology representation and ANOVA analysis of vaccine protection investigation | 2010 | 6 |
| 8 | Vaxar: A Web-Based Database of Laboratory Animal Responses to Vaccinations and Its Application in the Meta-Analysis of Different Animal Responses to Tuberculosis Vaccinations. | 2016 | 4 |
About Thomas Todd
Thomas Todd is a scholar working on Molecular Biology, Infectious Diseases, Epidemiology, Endocrinology and Small Animals, having authored 8 papers that have together received 275 indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (4 papers), Biomedical Text Mining and Ontologies (3 papers), Tuberculosis Research and Epidemiology (2 papers), Escherichia coli research studies (2 papers), Machine Learning in Bioinformatics (1 paper), Chemical Reactions and Isotopes (1 paper), Bacteriophages and microbial interactions (1 paper) and Clostridium difficile and Clostridium perfringens research (1 paper). The work is most often cited by research in Endocrinology (46 citations), Small Animals (26 citations), Infectious Diseases (51 citations), Molecular Biology (176 citations) and Molecular Medicine (12 citations). Thomas Todd has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Yongqun He, Thomas E. Gorochowski, Zuoshuang Xiang, Antoni Matyjaszkiewicz, Krasimira Tsaneva‐Atanasova, Claire Grierson, Nigel J. Savery, Mario di Bernardo, Stephen A. Reid and Boyang Zhao. Their work appears in journals such as Nucleic Acids Research, Molecular Microbiology, Lab Animal, PLoS ONE and BMC 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.