Scott Federhen
- Molecular Biology top 5%
- Ecology top 5%
- Plant Science top 10%
- Genetics top 10%
- Materials Chemistry
- Co-authors
- John C. WoottonTatiana TatusovaIgor TolstoyBoris FedorovLeonid ZaslavskyRichard McVeighStacy CiufoKathleen O’Neill
- Topics
- Genomics and Phylogenetic Studies (5 papers)Machine Learning in Bioinformatics (3 papers)RNA and protein synthesis mechanisms (3 papers)
- Journals
- Nucleic Acids ResearchJournal of VirologyMethods in enzymology on CD-ROM/Methods in enzymology
- 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
- Plant Science 293
- Genetics 255
- Materials Chemistry 149
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 of co-authors of Scott Federhen
This figure shows the co-authorship network connecting the top 25 collaborators of Scott Federhen. A scholar is included among the top collaborators of Scott Federhen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Scott Federhen. Scott Federhen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 129 | |
| 2 | 101 | |
| 3 | 31 | |
| 4 | The NCBI Taxonomy databasebreakdown → | 921 |
| 5 | GUEST COMMENTARY National Center for Biotechnology Information Viral Genomes Project | 1 |
| 6 | 56 | |
| 7 | 17 | |
| 8 | [33] Analysis of compositionally biased regions in sequence databasesbreakdown → | 614 |
| 9 | Statistics of local complexity in amino acid sequences and sequence databasesbreakdown → | 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) and RNA and protein synthesis mechanisms (3 papers). 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.