Daniel J. Weisenberger

126.1k citations
109 papers · 9.7k indexed · 3 hit papers · h-index 47

Daniel J. Weisenberger

108 papers receiving 9.6k citations

Hit Papers

Epigenetic stem cell signature in cancer2005202620122019200620052013250500750

Peers

Daniel J. Weisenberger
Comparison fields: 5 of 145
  • Molecular Biology 7.2k
  • Oncology 1.9k
  • Cancer Research 1.8k
  • Pathology and Forensic Medicine 1.4k
  • Genetics 1.4k
Replace Kimberly D. Siegmund with:
Kimberly D. Siegmund United States
Gail E. Tomlinson United States
Issei Imoto Japan
Martin Widschwendter United Kingdom
Rachel H. Giles Netherlands
Sharon E. Plon United States
Reinhard Buettner Germany
Hamish S. Scott Australia
Gangning Liang United States
Irene L. Andrulis Canada
Daniel J. Weisenberger relative to Kimberly D. Siegmund United States Kimberly D. Siegmund's profile →
Citations per field
00.5×1.7×
Kimberly D. Siegmund · 1×
Citations per year

Countries citing papers authored by Daniel J. Weisenberger

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Weisenberger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel J. Weisenberger

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Weisenberger. A scholar is included among the top collaborators of Daniel J. Weisenberger 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 Daniel J. Weisenberger. Daniel J. Weisenberger 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 3
2 11
3 16
4 27
5 45
6 3
7
Wnt5a promotes diabetic corneal epithelial wound healing and limbal stem cell expression
2
8 27
9 24
10 49
11 43
12 29
13 21
14 10
15 19
16 32
17 58
18 144
19 168
20 254

About Daniel J. Weisenberger

Daniel J. Weisenberger is a scholar working on Cancer Research, Pathology and Forensic Medicine and Molecular Biology, having authored 109 papers that have together received 9.7k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (71 papers), Genetic factors in colorectal cancer (24 papers) and RNA modifications and cancer (22 papers). The work is most often cited by research in Cancer Research (1.8k citations), Molecular Biology (7.2k citations) and Pathology and Forensic Medicine (1.4k citations). Daniel J. Weisenberger has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Peter W. Laird, Gangning Liang, Kimberly D. Siegmund, Peter A. Jones, Mihaela Campan, David Van Den Berg, Felicidad A. Gonzales, Jonathan Cheng, Toshinori Hinoue and Timothy J. Triche. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

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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