Matthew Fish
Impact in
- Cell Biology top 5%
- Cellular transport and secretion
- Hippo pathway signaling and YAP/TAZ
- Aging top 5%
Papers in
-
- Developmental Biology and Gene Regulation 4
- Wnt/β-catenin signaling in development and cancer 3
- CRISPR and Genetic Engineering 3
- Genomics and Chromatin Dynamics 2
-
- COVID-19 Clinical Research Studies 3
- Co-authors
- Roel Nusse (8 shared papers)Michèle P. Calos (2 shared papers)Amy C. Groth (2 shared papers)Ken M. Cadigan (4 shared papers)Eric Rulifson (3 shared papers)Matthew P. Scott (5 shared papers)Kaye Suyama (3 shared papers)P. Robin Hiesinger (1 shared paper)
- Journals
- Genetics (3 papers)Development (2 papers)eLife (2 papers)Nature Medicine (1 paper)Molecular & Cellular Proteomics (1 paper)
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Matthew Fish
20 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 104
- Cell Biology 441
- Aging 43
- Cellular and Molecular Neuroscience 336
- Molecular Biology 1.2k
- Infectious Diseases 159
Countries citing papers authored by Matthew Fish
This map shows the geographic impact of Matthew Fish'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 Fish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Fish more than expected).
Fields of papers citing papers by Matthew Fish
This network shows the impact of papers produced by Matthew Fish. 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 Fish. The network helps show where Matthew Fish may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Fish, 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 | 2004 | 386 | |
| 2 | 1998 | 279 | |
| 3 | 2020 | 258 | |
| 4 | 2007 | 251 | |
| 5 | 1999 | 146 | |
| 6 | 2001 | 136 | |
| 7 | 2007 | 77 | |
| 8 | 2006 | 55 | |
| 9 | 2005 | 40 | |
| 10 | 2021 | 31 | |
| 11 | Cell culture and whole animal approaches to understanding signaling by Wnt proteins in Drosophila. | 1997 | 27 |
| 12 | 2022 | 17 | |
| 13 | 2011 | 15 | |
| 14 | 2020 | 10 | |
| 15 | 2013 | 9 | |
| 16 | 2023 | 6 | |
| 17 | 2023 | 6 | |
| 18 | 2016 | 5 | |
| 19 | 2020 | 2 | |
| 20 | 2023 | 1 |
About Matthew Fish
Matthew Fish is a scholar working on Molecular Biology, Infectious Diseases, Epidemiology, Cell Biology and Genetics, having authored 20 papers that have together received 1.8k indexed citations. Recurring topics across this work include Developmental Biology and Gene Regulation (4 papers), Wnt/β-catenin signaling in development and cancer (3 papers), CRISPR and Genetic Engineering (3 papers), COVID-19 Clinical Research Studies (3 papers), Sepsis Diagnosis and Treatment (3 papers), Animal Genetics and Reproduction (3 papers), Genomics and Chromatin Dynamics (2 papers) and Hippo pathway signaling and YAP/TAZ (2 papers). The work is most often cited by research in Cell Biology (441 citations), Aging (43 citations), Cellular and Molecular Neuroscience (336 citations), Molecular Biology (1.2k citations) and Infectious Diseases (159 citations). Matthew Fish has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Roel Nusse, Michèle P. Calos, Amy C. Groth, Ken M. Cadigan, Eric Rulifson, Matthew P. Scott, Kaye Suyama, P. Robin Hiesinger, Hugo J. Bellen and Karen L. Schulze. Their work appears in journals such as Genetics, Development, eLife, Nature Medicine and Molecular & Cellular Proteomics.
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.