Brian E. Howard
- Molecular Biology
- Plant Science
- Health, Toxicology and Mutagenesis top 10%
- Artificial Intelligence
- Statistics, Probability and Uncertainty top 5%
- Co-authors
- Steffen HeberRuchir ShahDeepak MavKristina A. ThayerArpit TandonJason PhillipsVickie R. WalkerAndrew A. Rooney
- Topics
- Bioinformatics and Genomic Networks (4 papers)Gene expression and cancer classification (4 papers)Biomedical Text Mining and Ontologies (2 papers)
- Cited by
- Health InformaticsStatistics, Probability and UncertaintyHealth, Toxicology and Mutagenesis
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Brian E. Howard
16 papers receiving 558 citations
Peers
Comparison fields: 5 of 128
- Molecular Biology 194
- Plant Science 80
- Health, Toxicology and Mutagenesis 74
- Artificial Intelligence 64
- Statistics, Probability and Uncertainty 63
Countries citing papers authored by Brian E. Howard
This map shows the geographic impact of Brian E. Howard'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 Brian E. Howard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian E. Howard more than expected).
Fields of papers citing papers by Brian E. Howard
This network shows the impact of papers produced by Brian E. Howard. 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 Brian E. Howard. The network helps show where Brian E. Howard may publish in the future.
Co-authorship network of co-authors of Brian E. Howard
This figure shows the co-authorship network connecting the top 25 collaborators of Brian E. Howard. A scholar is included among the top collaborators of Brian E. Howard 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 Brian E. Howard. Brian E. Howard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 18 | |
| 6 | 90 | |
| 7 | 21 | |
| 8 | 105 | |
| 9 | 120 | |
| 10 | 33 | |
| 11 | 83 | |
| 12 | 28 | |
| 13 | 3 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 49 |
About Brian E. Howard
Brian E. Howard is a scholar working on Biophysics, Statistics, Probability and Uncertainty and Molecular Biology, having authored 16 papers that have together received 567 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Gene expression and cancer classification (4 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Health Informatics (27 citations), Statistics, Probability and Uncertainty (63 citations) and Health, Toxicology and Mutagenesis (74 citations). Brian E. Howard has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Steffen Heber, Ruchir Shah, Deepak Mav, Kristina A. Thayer, Arpit Tandon, Jason Phillips, Vickie R. Walker, Andrew A. Rooney, B. Alex Merrick and Heike Sederoff. Their work appears in journals such as Environmental Science & Technology, PLoS ONE and Environment International.
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.