Dan Williams
Impact in
- Water Science and Technology top 2%
- Fecal contamination and water quality
- Environmental Engineering top 5%
- Groundwater flow and contamination studies
Papers in
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- Fecal contamination and water quality 5
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- Groundwater flow and contamination studies 4
- Co-authors
- Gary S. Sayler (6 shared papers)Alice C. Layton (6 shared papers)Larry D. McKay (5 shared papers)Randall W. Gentry (5 shared papers)Ramakrishnan Srikumar (1 shared paper)John S. McCarty (1 shared paper)Jinzi J. Wu (1 shared paper)Michael S. DuBow (1 shared paper)
- Journals
- Journal of Environmental Quality (3 papers)Virology Journal (1 paper)American Water Works Association (1 paper)Nature Biotechnology (1 paper)Applied and Environmental Microbiology (1 paper)
- Partner nations
- United StatesFranceCanada
In The Last Decade
Dan Williams
8 papers receiving 747 citations
Peers
Comparison fields: 5 of 79
- Water Science and Technology 408
- Environmental Engineering 184
- Ecology 233
- Microbiology 49
- Health, Toxicology and Mutagenesis 93
Countries citing papers authored by Dan Williams
This map shows the geographic impact of Dan Williams'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 Dan Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Williams more than expected).
Fields of papers citing papers by Dan Williams
This network shows the impact of papers produced by Dan Williams. 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 Dan Williams. The network helps show where Dan Williams may publish in the future.
Co-authors
The 23 scholars most cited alongside Dan Williams, 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 | 2006 | 445 | |
| 2 | 2004 | 175 | |
| 3 | 2009 | 60 | |
| 4 | 2006 | 36 | |
| 5 | 2008 | 23 | |
| 6 | Development of Bacteroides 16S rRNA Gene TaqMan-Based Real-Time PCR Assays for Estimation of Total, Human, and Bovine Fecal Pollution in Water | 2006 | 20 |
| 7 | 2007 | 19 | |
| 8 | 2015 | 4 |
About Dan Williams
Dan Williams is a scholar working on Water Science and Technology, Environmental Engineering, Molecular Biology, Ecology and Health, Toxicology and Mutagenesis, having authored 8 papers that have together received 782 indexed citations. Recurring topics across this work include Fecal contamination and water quality (5 papers), Groundwater flow and contamination studies (4 papers), Water Treatment and Disinfection (2 papers), Genomics and Phylogenetic Studies (2 papers), Bacteriophages and microbial interactions (2 papers), Soil and Unsaturated Flow (1 paper), Constructed Wetlands for Wastewater Treatment (1 paper) and Microbial Community Ecology and Physiology (1 paper). The work is most often cited by research in Water Science and Technology (408 citations), Environmental Engineering (184 citations), Ecology (233 citations), Microbiology (49 citations) and Health, Toxicology and Mutagenesis (93 citations). Dan Williams has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Gary S. Sayler, Alice C. Layton, Larry D. McKay, Randall W. Gentry, Ramakrishnan Srikumar, John S. McCarty, Jinzi J. Wu, Michael S. DuBow, Mario Callejo and Tony Kwan. Their work appears in journals such as Journal of Environmental Quality, Virology Journal, American Water Works Association, Nature Biotechnology and Applied and Environmental Microbiology.
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.