Stephen R. Williams
- Molecular Biology top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Genetics top 5%
- Immunology top 10%
- Cellular and Molecular Neuroscience top 5%
- Co-authors
- Mark NobleDG GadianJutta UrenjakSarah H. ElseaCedric R. UytingcoSarah E. TaylorRaphaël GottardoMatthew R. Stone
- Topics
- Single-cell and spatial transcriptomics (5 papers)Genomic variations and chromosomal abnormalities (5 papers)Genetics and Neurodevelopmental Disorders (5 papers)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Stephen R. Williams
37 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Molecular Biology 1.9k
- Radiology, Nuclear Medicine and Imaging 508
- Genetics 474
- Immunology 314
- Cellular and Molecular Neuroscience 292
Countries citing papers authored by Stephen R. Williams
This map shows the geographic impact of Stephen R. 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 Stephen R. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen R. Williams more than expected).
Fields of papers citing papers by Stephen R. Williams
This network shows the impact of papers produced by Stephen R. 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 Stephen R. Williams. The network helps show where Stephen R. Williams may publish in the future.
Co-authorship network of co-authors of Stephen R. Williams
This figure shows the co-authorship network connecting the top 25 collaborators of Stephen R. Williams. A scholar is included among the top collaborators of Stephen R. Williams 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 Stephen R. Williams. Stephen R. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | High-definition spatial transcriptomic profiling of immune cell populations in colorectal cancerbreakdown → | 27 |
| 2 | 5 | |
| 3 | Spatial transcriptomics at subspot resolution with BayesSpacebreakdown → | 448 |
| 4 | Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortexbreakdown → | 557 |
| 5 | 6 | |
| 6 | 8 | |
| 7 | 6 | |
| 8 | 2 | |
| 9 | 99 | |
| 10 | 14 | |
| 11 | 16 | |
| 12 | 79 | |
| 13 | 9 | |
| 14 | 216 | |
| 15 | 19 | |
| 16 | 61 | |
| 17 | 9 | |
| 18 | 18 | |
| 19 | 19 | |
| 20 | 86 |
About Stephen R. Williams
Stephen R. Williams is a scholar working on Genetics, Molecular Biology and Biochemistry, having authored 38 papers that have together received 3.3k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Genomic variations and chromosomal abnormalities (5 papers) and Genetics and Neurodevelopmental Disorders (5 papers). The work is most often cited by research in Biophysics (221 citations), Molecular Biology (1.9k citations) and Radiology, Nuclear Medicine and Imaging (508 citations). Stephen R. Williams has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Mark Noble, DG Gadian, Jutta Urenjak, Sarah H. Elsea, Cedric R. Uytingco, Sarah E. Taylor, Raphaël Gottardo, Matthew R. Stone, Jamie Guenthoer and Thomas H. Pulliam. Their work appears in journals such as Nucleic Acids Research, Nature Communications and Nature Genetics.
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.