Michael Smoot
Impact in
- Molecular Biology top 1%
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- RNA and protein synthesis mechanisms
- Endocrinology top 1%
Papers in
-
- Bioinformatics and Genomic Networks 4
- Genomics and Phylogenetic Studies 4
- Gene expression and cancer classification 2
- RNA and protein synthesis mechanisms 2
- Co-authors
- Trey Ideker (5 shared papers)Keiichiro Ono (3 shared papers)Pengliang Wang (3 shared papers)Adam M. Phillippy (1 shared paper)Stefan Kurtz (1 shared paper)Martin Shumway (1 shared paper)Arthur L. Delcher (1 shared paper)Steven L. Salzberg (1 shared paper)
- Journals
- Bioinformatics (3 papers)Nature Methods (1 paper)Genome biology (1 paper)PLoS Computational Biology (1 paper)Nature Protocols (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Michael Smoot
11 papers receiving 9.1k citations
Michael Smoot's Hit Papers
Peers
Comparison fields: 5 of 176
- Molecular Biology 5.1k
- Endocrinology 311
- Cancer Research 667
- Plant Science 1.8k
- Ecology 978
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-authors
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 | Cytoscape 2.8: new features for data integration and network visualization Hit paper breakdown → | 2010 | 3811 |
| 2 | Versatile and open software for comparing large genomes Hit paper breakdown → | 2004 | 3803 |
| 3 | A travel guide to Cytoscape plugins Hit paper breakdown → | 2012 | 1164 |
| 4 | 2009 | 262 | |
| 5 | 2008 | 51 | |
| 6 | 2011 | 39 | |
| 7 | 2011 | 16 | |
| 8 | 2010 | 10 | |
| 9 | 2012 | 9 | |
| 10 | 2004 | 6 | |
| 11 | 2005 | 5 |
About Michael Smoot
Michael Smoot is a scholar working on Molecular Biology, Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition and Information Systems and Management, having authored 11 papers that have together received 9.2k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Genomics and Phylogenetic Studies (4 papers), Gene expression and cancer classification (2 papers), RNA and protein synthesis mechanisms (2 papers), Endoplasmic Reticulum Stress and Disease (1 paper), Adenosine and Purinergic Signaling (1 paper), Chromosomal and Genetic Variations (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Molecular Biology (5.1k citations), Endocrinology (311 citations), Cancer Research (667 citations), Plant Science (1.8k citations) and Ecology (978 citations). Michael Smoot has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Trey Ideker, Keiichiro Ono, Pengliang Wang, Adam M. Phillippy, Stefan Kurtz, Martin Shumway, Arthur L. Delcher, Steven L. Salzberg, Corina Antonescu and Gary D. Bader. Their work appears in journals such as Bioinformatics, Nature Methods, Genome biology, PLoS Computational Biology and Nature Protocols.
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.