Matthew T. Martin
- Health, Toxicology and Mutagenesis top 0.1%
- Computational Theory and Mathematics top 0.1%
- Molecular Biology top 5%
- Small Animals top 0.1%
- Cancer Research top 2%
- Co-authors
- David J. DixRichard JudsonKeith A. HouckRobert J. KavlockAnn M. RichardThomas B. KnudsenDavid M. ReifR. Woodrow Setzer
- Topics
- Effects and risks of endocrine disrupting chemicals (34 papers)Computational Drug Discovery Methods (27 papers)Animal testing and alternatives (22 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Matthew T. Martin
67 papers receiving 6.5k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Health, Toxicology and Mutagenesis 3.3k
- Computational Theory and Mathematics 2.2k
- Molecular Biology 1.8k
- Small Animals 1.4k
- Cancer Research 816
Countries citing papers authored by Matthew T. Martin
This map shows the geographic impact of Matthew T. Martin'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 Matthew T. Martin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew T. Martin more than expected).
Fields of papers citing papers by Matthew T. Martin
This network shows the impact of papers produced by Matthew T. Martin. 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 Matthew T. Martin. The network helps show where Matthew T. Martin may publish in the future.
Co-authorship network of co-authors of Matthew T. Martin
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew T. Martin. A scholar is included among the top collaborators of Matthew T. Martin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthew T. Martin. Matthew T. Martin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 5 | |
| 3 | 62 | |
| 4 | 91 | |
| 5 | 9 | |
| 6 | 26 | |
| 7 | 8 | |
| 8 | 10 | |
| 9 | 90 | |
| 10 | 58 | |
| 11 | 10 | |
| 12 | 12 | |
| 13 | 43 | |
| 14 | 58 | |
| 15 | 39 | |
| 16 | 152 | |
| 17 | 301 | |
| 18 | 95 | |
| 19 | 197 | |
| 20 | A Systematic Approach to Estimating the Age of a Horse | 8 |
About Matthew T. Martin
Matthew T. Martin is a scholar working on Small Animals, Health, Toxicology and Mutagenesis and Computational Theory and Mathematics, having authored 67 papers that have together received 6.7k indexed citations. Recurring topics across this work include Effects and risks of endocrine disrupting chemicals (34 papers), Computational Drug Discovery Methods (27 papers) and Animal testing and alternatives (22 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (3.3k citations), Chemical Health and Safety (126 citations) and Small Animals (1.4k citations). Matthew T. Martin has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include David J. Dix, Richard Judson, Keith A. Houck, Robert J. Kavlock, Ann M. Richard, Thomas B. Knudsen, David M. Reif, R. Woodrow Setzer, Daniel M. Rotroff and Russell S. Thomas. Their work appears in journals such as Environmental Science & Technology, Nature Biotechnology and 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.