D. Williams Parsons

38.2k citations
92 papers · 10.2k indexed · 4 hit papers · h-index 31
Topics
Cancer Genomics and Diagnostics (21 papers)Neuroblastoma Research and Treatments (18 papers)Genomics and Rare Diseases (16 papers)

In The Last Decade

D. Williams Parsons

87 papers receiving 10.0k citations

Hit Papers

IDH1andIDH2Mutations in Gliomas2008202620142020200920112009200810002.0k3.0k4.0k

Peers

D. Williams Parsons
Comparison fields: 5 of 129
  • Molecular Biology 5.3k
  • Genetics 4.7k
  • Cancer Research 3.3k
  • Oncology 1.9k
  • Pulmonary and Respiratory Medicine 1.3k
Replace Daniel P. Cahill with:
Daniel P. Cahill United States
Hai Yan United States
Howard Colman United States
Peter Hau Germany
Erik P. Sulman United States
Ryo Nishikawa Japan
Ahmed Idbaïh France
Koichi Ichimura Japan
Annick Desjardins United States
Kristin Waite United States
D. Williams Parsons relative to Daniel P. Cahill United States Daniel P. Cahill's profile →
Citations per field
00.5×1.6×
Daniel P. Cahill · 1×
Citations per year

Countries citing papers authored by D. Williams Parsons

Since Specialization
Citations

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

Fields of papers citing papers by D. Williams Parsons

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Williams Parsons. 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 D. Williams Parsons. The network helps show where D. Williams Parsons may publish in the future.

Co-authorship network of co-authors of D. Williams Parsons

This figure shows the co-authorship network connecting the top 25 collaborators of D. Williams Parsons. A scholar is included among the top collaborators of D. Williams Parsons 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 D. Williams Parsons. D. Williams Parsons is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 4
4 1
5 2
6 4
7 0
8 4
9 13
10 10
11 11
12 34
13 17
14 142
15 72
16 92
17 443
18 412
19
Intragenic SMN mutations : frequency, distribution, evidence of a founder effect, and modification of SMA phenotype by centromeric copy number /
1
20 142

About D. Williams Parsons

D. Williams Parsons is a scholar working on Genetics, Cancer Research and Neurology, having authored 92 papers that have together received 10.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (21 papers), Neuroblastoma Research and Treatments (18 papers) and Genomics and Rare Diseases (16 papers). The work is most often cited by research in Genetics (4.7k citations), Cancer Research (3.3k citations) and Molecular Biology (5.3k citations). D. Williams Parsons has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Victor E. Velculescu, Bert Vogelstein, Kenneth W. Kinzler, Hai Yan, Siân Jones, Darell D. Bigner, Gregory J. Riggins, Genglin Jin, Allan H. Friedman and Henry S. Friedman. Their work appears in journals such as Nature, Science and New England Journal of Medicine.

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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