Scott Federhen
- Molecular Biology top 5%
- Genomics and Phylogenetic Studies 5
- Machine Learning in Bioinformatics 3
- RNA and protein synthesis mechanisms 3
- Fractal and DNA sequence analysis 2
- Ecology top 5%
- Microbial Community Ecology and Physiology 2
- Endocrinology top 10%
- Genetics top 10%
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- Plant Virus Research Studies 2
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- Animal Virus Infections Studies 2
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- Viral gastroenteritis research and epidemiology 1
- Co-authors
- John C. WoottonTatiana TatusovaIgor TolstoyBoris FedorovLeonid ZaslavskyRichard McVeighStacy CiufoKathleen O’Neill
- Journals
- Nucleic Acids Research (3 papers)Journal of Virology (1 paper)Methods in enzymology on CD-ROM/Methods in enzymology (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Scott Federhen
9 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Molecular Biology 2.0k
- Ecology 406
- Endocrinology 48
- Aging 16
- Genetics 255
Countries citing papers authored by Scott Federhen
This map shows the geographic impact of Scott Federhen'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 Scott Federhen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Federhen more than expected).
Fields of papers citing papers by Scott Federhen
This network shows the impact of papers produced by Scott Federhen. 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 Scott Federhen. The network helps show where Scott Federhen may publish in the future.
Co-authorship network
The 22 scholars most cited alongside Scott Federhen, 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 | 2014 | 129 | |
| 2 | 2014 | 101 | |
| 3 | 2014 | 31 | |
| 4 | The NCBI Taxonomy databasebreakdown → | 2011 | 921 |
| 5 | GUEST COMMENTARY National Center for Biotechnology Information Viral Genomes Project | 2004 | 1 |
| 6 | 2004 | 56 | |
| 7 | 2003 | 17 | |
| 8 | [33] Analysis of compositionally biased regions in sequence databasesbreakdown → | 1996 | 614 |
| 9 | Statistics of local complexity in amino acid sequences and sequence databasesbreakdown → | 1993 | 562 |
About Scott Federhen
Scott Federhen is a scholar working on Animal Science and Zoology, Ecology and Molecular Biology, having authored 9 papers that have together received 2.4k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), Machine Learning in Bioinformatics (3 papers), RNA and protein synthesis mechanisms (3 papers), Microbial Community Ecology and Physiology (2 papers), Fractal and DNA sequence analysis (2 papers), Plant Virus Research Studies (2 papers), Animal Virus Infections Studies (2 papers) and Viral gastroenteritis research and epidemiology (1 paper). The work is most often cited by research in Molecular Biology (2.0k citations), Ecology (406 citations) and Endocrinology (48 citations). Scott Federhen has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include John C. Wootton, Tatiana Tatusova, Igor Tolstoy, Boris Fedorov, Leonid Zaslavsky, Richard McVeigh, Stacy Ciufo, Kathleen O’Neill, Detlef D. Leipe and Sergei Resenchuk. Their work appears in journals such as Nucleic Acids Research, Journal of Virology and Methods in enzymology on CD-ROM/Methods in enzymology.
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.