Matthew Thayer
Impact in
- Aging top 5%
- Molecular Biology top 5%
- Muscle Physiology and Disorders
- DNA Repair Mechanisms
- RNA Research and Splicing
- Genomics and Chromatin Dynamics
- Ubiquitin and proteasome pathways
- Developmental Biology and Gene Regulation
- CRISPR and Genetic Engineering
- Congenital heart defects research
Papers in
-
- DNA Repair Mechanisms 1
- Ubiquitin and proteasome pathways 1
- Protein Degradation and Inhibitors 1
- Genetics 3
- Chronic Lymphocytic Leukemia Research 3
- Co-authors
- Stephen J. Tapscott (1 shared paper)Stanley M. Hollenberg (1 shared paper)Robert L. Davis (1 shared paper)Andrew B. Lassar (1 shared paper)Michael Krause (1 shared paper)Robert Benezra (1 shared paper)Yuan Zhuang (1 shared paper)David L. Turner (1 shared paper)
- Journals
- Blood (2 papers)Cancer Research (2 papers)Science (1 paper)Gastroenterology (1 paper)Molecular Cell (1 paper)
- Partner nations
- United States
In The Last Decade
Matthew Thayer
8 papers receiving 1.9k citations
Matthew Thayer's Hit Papers
Peers
Comparison fields: 5 of 89
- Aging 50
- Molecular Biology 1.6k
- Cancer Research 231
- Cell Biology 224
- Genetics 333
Countries citing papers authored by Matthew Thayer
This map shows the geographic impact of Matthew Thayer'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 Thayer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Thayer more than expected).
Fields of papers citing papers by Matthew Thayer
This network shows the impact of papers produced by Matthew Thayer. 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 Thayer. The network helps show where Matthew Thayer may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Thayer, 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 | The myoD Gene Family: Nodal Point During Specification of the Muscle Cell Lineage Hit paper breakdown → | 1991 | 1464 |
| 2 | 2001 | 339 | |
| 3 | 2011 | 156 | |
| 4 | 2020 | 8 | |
| 5 | 2020 | 4 | |
| 6 | 2020 | 2 | |
| 7 | 2020 | 1 | |
| 8 | 2018 | 1 |
About Matthew Thayer
Matthew Thayer is a scholar working on Molecular Biology, Genetics, Organic Chemistry, Surgery and Pathology and Forensic Medicine, having authored 8 papers that have together received 2.0k indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (3 papers), DNA Repair Mechanisms (1 paper), Orthopedic Surgery and Rehabilitation (1 paper), Ubiquitin and proteasome pathways (1 paper), Protein Degradation and Inhibitors (1 paper), Liver physiology and pathology (1 paper), Lymphoma Diagnosis and Treatment (1 paper) and Chromosomal and Genetic Variations (1 paper). The work is most often cited by research in Aging (50 citations), Molecular Biology (1.6k citations), Cancer Research (231 citations), Cell Biology (224 citations) and Genetics (333 citations). Matthew Thayer has collaborated with scholars based in United States. Frequent co-authors include Stephen J. Tapscott, Stanley M. Hollenberg, Robert L. Davis, Andrew B. Lassar, Michael Krause, Robert Benezra, Yuan Zhuang, David L. Turner, Harold Weintraub and T. Keith Blackwell. Their work appears in journals such as Blood, Cancer Research, Science, Gastroenterology and Molecular Cell.
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.