Walter R. Gilks
- Statistics and Probability top 0.05%
- Statistical Methods and Bayesian Inference 13
- Statistical Methods and Inference 13
- Artificial Intelligence top 0.2%
- Bayesian Methods and Mixture Models 13
- Finance top 2%
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- Genomics and Phylogenetic Studies 8
- RNA and protein synthesis mechanisms 8
- Genomics and Chromatin Dynamics 8
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- Renal Transplantation Outcomes and Treatments 7
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- Organ Transplantation Techniques and Outcomes 6
- Co-authors
- Sylvia RichardsonDavid J. SpiegelhalterPascal WildGareth O. RobertsCarlo BerzuiniSusan A. GelmanNicky BestD. J. Spiegelhalter
- Journals
- Journal of the Royal Statistical Society Series C (Applied Statistics) (6 papers)Transplantation (6 papers)Bioinformatics (4 papers)
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
Walter R. Gilks
76 papers receiving 11.6k citations
Hit Papers
Peers
Comparison fields: 5 of 208
- Statistics and Probability 3.7k
- Statistics, Probability and Uncertainty 884
- Artificial Intelligence 3.4k
- Management Science and Operations Research 776
- Finance 378
Countries citing papers authored by Walter R. Gilks
This map shows the geographic impact of Walter R. Gilks'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 Walter R. Gilks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Walter R. Gilks more than expected).
Fields of papers citing papers by Walter R. Gilks
This network shows the impact of papers produced by Walter R. Gilks. 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 Walter R. Gilks. The network helps show where Walter R. Gilks may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Walter R. Gilks, 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 | 2017 | 3 | |
| 2 | 2009 | 37 | |
| 3 | 2007 | 3 | |
| 4 | 2007 | 83 | |
| 5 | 2006 | 3 | |
| 6 | 2005 | 62 | |
| 7 | 2005 | 6 | |
| 8 | 2005 | 26 | |
| 9 | 2005 | 26 | |
| 10 | 2005 | 22 | |
| 11 | 2004 | 67 | |
| 12 | Highly Conserved Non-Coding Sequences Are Associated with Vertebrate Developmentbreakdown → | 2004 | 723 |
| 13 | 1997 | 149 | |
| 14 | 1997 | 6 | |
| 15 | Comment on "Bayesian Computation and Stochastic Systems" | 1995 | 6 |
| 16 | 1994 | 35 | |
| 17 | 1994 | 95 | |
| 18 | 1994 | 1 | |
| 19 | 1993 | 110 | |
| 20 | Cyclosporine: its time of impact on kidney graft survival. | 1990 | 2 |
About Walter R. Gilks
Walter R. Gilks is a scholar working on Transplantation, Statistics and Probability and Aging, having authored 78 papers that have together received 12.4k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (13 papers), Statistical Methods and Bayesian Inference (13 papers), Statistical Methods and Inference (13 papers), Genomics and Phylogenetic Studies (8 papers), RNA and protein synthesis mechanisms (8 papers), Genomics and Chromatin Dynamics (8 papers), Renal Transplantation Outcomes and Treatments (7 papers) and Organ Transplantation Techniques and Outcomes (6 papers). The work is most often cited by research in Statistics and Probability (3.7k citations), Statistics, Probability and Uncertainty (884 citations) and Artificial Intelligence (3.4k citations). Walter R. Gilks has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Sylvia Richardson, David J. Spiegelhalter, Pascal Wild, Gareth O. Roberts, Carlo Berzuini, Susan A. Gelman, Nicky Best, D. J. Spiegelhalter, Andrew C. Thomas and Keith Tan. Their work appears in journals such as Journal of the Royal Statistical Society Series C (Applied Statistics), Transplantation, Bioinformatics, Statistical Applications in Genetics and Molecular Biology and Journal of the American Statistical Association.
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.