Michael B. Mayhew
Impact in
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- Fungal and yeast genetics research
- Gene Regulatory Network Analysis
- Genomics and Phylogenetic Studies
- Genomics and Chromatin Dynamics
- Bioinformatics and Genomic Networks
Papers in
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- Fungal and yeast genetics research 3
- Gene Regulatory Network Analysis 3
- Bioinformatics and Genomic Networks 2
- Gene expression and cancer classification 1
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- Machine Learning in Healthcare 3
- Co-authors
- Steven B. Haase (4 shared papers)Samuel Marguerat (1 shared paper)Daniel Keifenheim (1 shared paper)Alexander J. Hartemink (3 shared papers)Nick Rhind (1 shared paper)Uwe Ohler (1 shared paper)Ljubomir Buturović (4 shared papers)Roland Luethy (4 shared papers)
- Journals
- Molecular Cell (2 papers)Nature Communications (1 paper)Genome Research (1 paper)Bioinformatics (1 paper)Journal of Biomedical Informatics (1 paper)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Michael B. Mayhew
16 papers receiving 341 citations
Peers
Comparison fields: 5 of 72
- Health Informatics 5
- Molecular Biology 195
- Critical Care and Intensive Care Medicine 10
- Cell Biology 37
- Aging 4
Countries citing papers authored by Michael B. Mayhew
This map shows the geographic impact of Michael B. Mayhew'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 Michael B. Mayhew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael B. Mayhew more than expected).
Fields of papers citing papers by Michael B. Mayhew
This network shows the impact of papers produced by Michael B. Mayhew. 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 Michael B. Mayhew. The network helps show where Michael B. Mayhew may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael B. Mayhew, 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 | 2020 | 75 | |
| 2 | 2017 | 66 | |
| 3 | 2012 | 53 | |
| 4 | 2011 | 24 | |
| 5 | 2017 | 22 | |
| 6 | 2009 | 21 | |
| 7 | 2017 | 19 | |
| 8 | 2022 | 17 | |
| 9 | 2011 | 14 | |
| 10 | 2016 | 11 | |
| 11 | 2017 | 10 | |
| 12 | 2012 | 6 | |
| 13 | 2018 | 3 | |
| 14 | 2020 | 3 | |
| 15 | 2020 | 3 | |
| 16 | 2013 | 2 |
About Michael B. Mayhew
Michael B. Mayhew is a scholar working on Molecular Biology, Artificial Intelligence, Epidemiology, Computer Vision and Pattern Recognition and Cell Biology, having authored 16 papers that have together received 349 indexed citations. Recurring topics across this work include Fungal and yeast genetics research (3 papers), Machine Learning in Healthcare (3 papers), Sepsis Diagnosis and Treatment (3 papers), Gene Regulatory Network Analysis (3 papers), Microtubule and mitosis dynamics (2 papers), Bioinformatics and Genomic Networks (2 papers), Gene expression and cancer classification (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Health Informatics (5 citations), Molecular Biology (195 citations), Critical Care and Intensive Care Medicine (10 citations), Cell Biology (37 citations) and Aging (4 citations). Michael B. Mayhew has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Steven B. Haase, Samuel Marguerat, Daniel Keifenheim, Alexander J. Hartemink, Nick Rhind, Uwe Ohler, Ljubomir Buturović, Roland Luethy, David A. Orlando and Sayan Mukherjee. Their work appears in journals such as Molecular Cell, Nature Communications, Genome Research, Bioinformatics and Journal of Biomedical Informatics.
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.