Justin L. Mott
- Molecular Biology top 2%
- Cancer Research top 0.5%
- Epidemiology top 2%
- Surgery top 5%
- Cell Biology top 2%
- Co-authors
- Gregory J. GoresAshley M. MohrSteven F. BronkShogo KobayashiNathan W. WerneburgSophie C. CazanaveMaria Eugenia GuicciardiYuko Akazawa
- Topics
- MicroRNA in disease regulation (17 papers)Liver Disease Diagnosis and Treatment (16 papers)Cell death mechanisms and regulation (13 papers)
- Partner nations
- United StatesBelgiumGermany
In The Last Decade
Justin L. Mott
77 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Molecular Biology 3.2k
- Cancer Research 2.1k
- Epidemiology 1.1k
- Surgery 741
- Cell Biology 587
Countries citing papers authored by Justin L. Mott
This map shows the geographic impact of Justin L. Mott'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 Justin L. Mott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin L. Mott more than expected).
Fields of papers citing papers by Justin L. Mott
This network shows the impact of papers produced by Justin L. Mott. 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 Justin L. Mott. The network helps show where Justin L. Mott may publish in the future.
Co-authorship network of co-authors of Justin L. Mott
This figure shows the co-authorship network connecting the top 25 collaborators of Justin L. Mott. A scholar is included among the top collaborators of Justin L. Mott 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 Justin L. Mott. Justin L. Mott is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Morphological Segmentation for Low Resource Languages | 3 |
| 2 | Cross-Document, Cross-Language Event Coreference Annotation Using Event Hoppers | 4 |
| 3 | 30 | |
| 4 | Parallel Chinese-English Entities, Relations and Events Corpora | 1 |
| 5 | 31 | |
| 6 | 91 | |
| 7 | Incorporating Alternate Translations into English Translation Treebank | 3 |
| 8 | 30 | |
| 9 | Using Derivation Trees for Informative Treebank Inter-Annotator Agreement Evaluation | 4 |
| 10 | 25 | |
| 11 | Further Developments in Treebank Error Detection Using Derivation Trees | 1 |
| 12 | Linguistic Resources for 2012 Knowledge Base Population Evaluations | 13 |
| 13 | 163 | |
| 14 | 211 | |
| 15 | 7 | |
| 16 | 9 | |
| 17 | 14 | |
| 18 | 35 | |
| 19 | 1 | |
| 20 | 15 |
About Justin L. Mott
Justin L. Mott is a scholar working on Cancer Research, Hepatology and Developmental Neuroscience, having authored 79 papers that have together received 5.4k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (17 papers), Liver Disease Diagnosis and Treatment (16 papers) and Cell death mechanisms and regulation (13 papers). The work is most often cited by research in Cancer Research (2.1k citations), Hepatology (417 citations) and Molecular Biology (3.2k citations). Justin L. Mott has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include Gregory J. Gores, Ashley M. Mohr, Steven F. Bronk, Shogo Kobayashi, Nathan W. Werneburg, Sophie C. Cazanave, Maria Eugenia Guicciardi, Yuko Akazawa, Harmeet Malhi and Christian D. Fingas. Their work appears in journals such as Journal of Biological Chemistry, Journal of Neuroscience and Gastroenterology.
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.