Daniel O’Connor

102 papers receiving 3.0k citations

Daniel O’Connor's Hit Papers

ASPP Proteins Specifically Stimulate the Apoptotic Function of p53 2001 · 518 citations
5180+8+16Years since publication100200300400500

Peers

Daniel O’Connor
Comparison fields: 5 of 168
  • Oncology 1.1k
  • Radiation 217
  • Biotechnology 203
  • Ophthalmology 164
  • Molecular Biology 1.3k
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Daniel O’Connor relative to Philip Hahnfeldt United States Philip Hahnfeldt's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel O’Connor

Since Specialization
Citations

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

Fields of papers citing papers by Daniel O’Connor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel O’Connor, 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 O’Connor Line = papers co-authored together Daniel O’Connor links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 109 papers — load more, or switch the sort, to bring in the rest.

#Work
1
ASPP Proteins Specifically Stimulate the Apoptotic Function of p53
Hit paper breakdown →
2001518
2 2003298
3 1999222
4 2004218
5 2018121
6 200286
7 199583
8 200065
9 201561
10 200556
11 201956
12 201556
13 200254
14 201849
15
p53 phosphorylation mutants retain transcription activity.
199547
16 199345
17 201842
18 200241
19 197938
20 201438

About Daniel O’Connor

Daniel O’Connor is a scholar working on Pulmonary and Respiratory Medicine, Radiation, Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 109 papers that have together received 3.1k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (16 papers), Health Systems, Economic Evaluations, Quality of Life (13 papers), Radiation Therapy and Dosimetry (12 papers), Cancer-related Molecular Pathways (11 papers), Sparse and Compressive Sensing Techniques (7 papers), Medical Imaging Techniques and Applications (7 papers), Genomics and Rare Diseases (6 papers) and Pharmaceutical Economics and Policy (6 papers). The work is most often cited by research in Oncology (1.1k citations), Radiation (217 citations), Biotechnology (203 citations), Ophthalmology (164 citations) and Molecular Biology (1.3k citations). Daniel O’Connor has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Xin Lü, Shan Zhong, Jung-Kuang Hsieh, Tim Crook, Giuseppe Trigiante, Daniele Bergamaschi, Elizabeth A. Slee, Ke Sheng, Louie Naumovski and Dan Ruan. Their work appears in journals such as Medical Physics, Nature Reviews Drug Discovery, IEEE Transactions on Magnetics, Molecular and Cellular Biology and Physics in Medicine and Biology.

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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