Michael Smoot
Impact in
- Molecular Biology top 1%
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- Endocrinology top 1%
Papers in
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- Adenosine and Purinergic Signaling 1
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- Cell Image Analysis Techniques 1
- Co-authors
- Trey IdekerKeiichiro OnoPengliang WangMartin ShumwayAdam M. PhillippySteven L. SalzbergStefan KurtzCorina Antonescu
- Journals
- Bioinformatics (3 papers)Nature Methods (1 paper)PLoS Computational Biology (1 paper)BMC Bioinformatics (1 paper)Genome biology (1 paper)
- Partner nations
- United StatesCanadaBelgium
In The Last Decade
Michael Smoot
11 papers receiving 8.9k citations
Hit Papers
Peers
Comparison fields: 5 of 179
- Molecular Biology 5.9k
- Endocrinology 341
- Cancer Research 819
- Plant Science 2.0k
- Ecology 1.1k
Countries citing papers authored by Michael Smoot
This map shows the geographic impact of Michael Smoot'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 Smoot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Smoot more than expected).
Fields of papers citing papers by Michael Smoot
This network shows the impact of papers produced by Michael Smoot. 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 Smoot. The network helps show where Michael Smoot may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael Smoot, 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 | A travel guide to Cytoscape plugins Hit paper breakdown → | 2012 | 1149 |
| 2 | 2012 | 9 | |
| 3 | 2011 | 16 | |
| 4 | 2011 | 39 | |
| 5 | Cytoscape 2.8: new features for data integration and network visualization Hit paper breakdown → | 2010 | 3767 |
| 6 | 2010 | 10 | |
| 7 | 2009 | 259 | |
| 8 | 2008 | 50 | |
| 9 | 2005 | 5 | |
| 10 | Versatile and open software for comparing large genomes Hit paper breakdown → | 2004 | 3747 |
| 11 | 2004 | 5 |
About Michael Smoot
Michael Smoot is a scholar working on Physiology, Biophysics, Information Systems and Management, Molecular Biology and Artificial Intelligence, having authored 11 papers that have together received 9.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Genomics and Phylogenetic Studies (5 papers), Gene expression and cancer classification (3 papers), Machine Learning in Bioinformatics (2 papers), RNA and protein synthesis mechanisms (2 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers), Adenosine and Purinergic Signaling (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Molecular Biology (5.9k citations), Endocrinology (341 citations), Cancer Research (819 citations), Plant Science (2.0k citations) and Ecology (1.1k citations). Michael Smoot has collaborated with scholars based in United States, Canada and Belgium. Frequent co-authors include Trey Ideker, Keiichiro Ono, Pengliang Wang, Martin Shumway, Adam M. Phillippy, Steven L. Salzberg, Stefan Kurtz, Corina Antonescu, Arthur L. Delcher and Gary D. Bader. Their work appears in journals such as Bioinformatics, Nature Methods, PLoS Computational Biology, BMC Bioinformatics and Genome biology.
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.