Michael E. Cusick
- Computational Theory and Mathematics top 0.2%
- Molecular Biology top 0.5%
- Bioinformatics and Genomic Networks 17
- Fungal and yeast genetics research 10
- RNA and protein synthesis mechanisms 10
- RNA Research and Splicing 8
- Microbial Metabolic Engineering and Bioproduction 7
- Genomics and Phylogenetic Studies 5
- Biomedical Text Mining and Ontologies 3
- Aging top 2%
- Genetics top 2%
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- Bacteriophages and microbial interactions 3
- Co-authors
- Marc VidalK.-I. GohAlbert-Ĺaszló BarabásiDavid ValleBarton ChildsMuhammed A. YıldırımDenis DupuyJing‐Dong J. Han
- Journals
- Nature Methods (7 papers)Nature Biotechnology (3 papers)Proceedings of the National Academy of Sciences (3 papers)
- Partner nations
- United StatesBelgiumFrance
In The Last Decade
Michael E. Cusick
40 papers receiving 8.2k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Computational Theory and Mathematics 1.7k
- Molecular Biology 6.9k
- Aging 90
- Genetics 1.1k
- Statistical and Nonlinear Physics 375
Countries citing papers authored by Michael E. Cusick
This map shows the geographic impact of Michael E. Cusick'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 E. Cusick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael E. Cusick more than expected).
Fields of papers citing papers by Michael E. Cusick
This network shows the impact of papers produced by Michael E. Cusick. 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 E. Cusick. The network helps show where Michael E. Cusick may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael E. Cusick, 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 | 2013 | 102 | |
| 2 | 2011 | 26 | |
| 3 | 2010 | 92 | |
| 4 | 2010 | 48 | |
| 5 | 2010 | 12 | |
| 6 | 2009 | 14 | |
| 7 | 2009 | 12 | |
| 8 | 2008 | 19 | |
| 9 | 2008 | 321 | |
| 10 | 2008 | 23 | |
| 11 | 2008 | 212 | |
| 12 | The human disease networkbreakdown → | 2007 | 2301 |
| 13 | 2007 | 202 | |
| 14 | 2006 | 463 | |
| 15 | 2005 | 241 | |
| 16 | Evidence for dynamically organized modularity in the yeast protein–protein interaction networkbreakdown → | 2004 | 1301 |
| 17 | 1998 | 50 | |
| 18 | 1994 | 5 | |
| 19 | 1994 | 2 | |
| 20 | 1988 | 45 |
About Michael E. Cusick
Michael E. Cusick is a scholar working on Aging, Molecular Biology and Cell Biology, having authored 40 papers that have together received 8.3k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (17 papers), Fungal and yeast genetics research (10 papers), RNA and protein synthesis mechanisms (10 papers), RNA Research and Splicing (8 papers), Microbial Metabolic Engineering and Bioproduction (7 papers), Genomics and Phylogenetic Studies (5 papers), Bacteriophages and microbial interactions (3 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Computational Theory and Mathematics (1.7k citations), Molecular Biology (6.9k citations) and Aging (90 citations). Michael E. Cusick has collaborated with scholars based in United States, Belgium and France. Frequent co-authors include Marc Vidal, K.-I. Goh, Albert-Ĺaszló Barabási, David Valle, Barton Childs, Muhammed A. Yıldırım, Denis Dupuy, Jing‐Dong J. Han, Nicolas Bertin and Frederick P. Roth. Their work appears in journals such as Nature Methods, Nature Biotechnology, Proceedings of the National Academy of Sciences, Molecular and Cellular Biology and Nature.
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.