Daniel Williamson

60 papers receiving 1.9k citations

Daniel Williamson's Hit Papers

Novel molecular subgroups for clinical classification and outcome prediction in childhood medulloblastoma: a cohort study 2017 · 352 citations
3520+3+6Years since publication100200300

Peers

Daniel Williamson
Comparison fields: 5 of 121
  • Genetics 518
  • Cancer Research 322
  • Molecular Biology 1.1k
  • Hematology 140
  • Neurology 150
Replace Paula Schaiquevich with:
Paula Schaiquevich Argentina
Pierre Verrelle France
James Y. Chen United States
Sven Skog Sweden
Larry J. Schaaf United States
Y. Edward Hsia United States
C. Brock United Kingdom
Kenneth S. Bauer United States
Nicholas Papadopoulos United States
David M. Kurtz United States
Daniel Williamson relative to Paula Schaiquevich Argentina Paula Schaiquevich's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel Williamson

Since Specialization
Citations

This map shows the geographic impact of Daniel Williamson'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 Daniel Williamson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Williamson more than expected).

Fields of papers citing papers by Daniel Williamson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Williamson. 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 Daniel Williamson. The network helps show where Daniel Williamson may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Williamson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Williamson Line = papers co-authored together Daniel Williamson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Novel molecular subgroups for clinical classification and outcome prediction in childhood medulloblastoma: a cohort study
Hit paper breakdown →
2017352
2 2019131
3 2012130
4 2013113
5 2005104
6 200986
7 200780
8 201170
9 201258
10 201751
11 202051
12 200146
13 201642
14
Detection of 1,N6-propanodeoxyadenosine in acrolein-modified polydeoxyadenylic acid and DNA by 32P postlabeling.
199041
15 202238
16 201335
17 201933
18 200631
19 199931
20 202129

About Daniel Williamson

Daniel Williamson is a scholar working on Molecular Biology, Genetics, Cancer Research, Pathology and Forensic Medicine and Spectroscopy, having authored 62 papers that have together received 2.0k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (14 papers), Chromatin Remodeling and Cancer (8 papers), Cancer-related molecular mechanisms research (5 papers), Cancer Mechanisms and Therapy (4 papers), Epigenetics and DNA Methylation (4 papers), Sarcoma Diagnosis and Treatment (4 papers), Advanced NMR Techniques and Applications (3 papers) and Acute Lymphoblastic Leukemia research (3 papers). The work is most often cited by research in Genetics (518 citations), Cancer Research (322 citations), Molecular Biology (1.1k citations), Hematology (140 citations) and Neurology (150 citations). Daniel Williamson has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Steven C. Clifford, Simon Bailey, Ed C. Schwalbe, Janet Shipley, Janet C. Lindsey, Kathy Pritchard‐Jones, Stephen Crosier, Samuel M. Cohen, Thomas S. Jacques and Abhijit Joshi. Their work appears in journals such as Neuro-Oncology, Acta Neuropathologica, Neuropathology and Applied Neurobiology, Cancer Research and BMJ Open.

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.

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