Daniel O’Connor

17.7k total citations
111 papers, 5.0k citations indexed

About

Daniel O’Connor is a scholar working on Surgery, Epidemiology and Molecular Biology. According to data from OpenAlex, Daniel O’Connor has authored 111 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Surgery, 25 papers in Epidemiology and 15 papers in Molecular Biology. Recurrent topics in Daniel O’Connor's work include Orthopaedic implants and arthroplasty (38 papers), Total Knee Arthroplasty Outcomes (25 papers) and Orthopedic Infections and Treatments (19 papers). Daniel O’Connor is often cited by papers focused on Orthopaedic implants and arthroplasty (38 papers), Total Knee Arthroplasty Outcomes (25 papers) and Orthopedic Infections and Treatments (19 papers). Daniel O’Connor collaborates with scholars based in United States, United Kingdom and Australia. Daniel O’Connor's co-authors include Murali Jasty, William H. Harris, C.R. Bragdon, Orhun K. Muratoglu, Charles R. Bragdon, Jay D. Lowenstein, Andrew J. Pollard, William H. Harris, Dennis W. Burke and Dennis K. Burke and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Daniel O’Connor

108 papers receiving 4.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel O’Connor United States 35 3.4k 476 452 396 355 111 5.0k
Jeffrey M. Davidson United States 61 2.3k 0.7× 236 0.5× 479 1.1× 3.6k 9.0× 1.3k 3.6× 191 13.2k
Soo Young Lee South Korea 27 445 0.1× 115 0.2× 567 1.3× 967 2.4× 132 0.4× 185 3.1k
Seung Hyun Lee South Korea 30 571 0.2× 479 1.0× 687 1.5× 338 0.9× 1.8k 5.0× 266 4.9k
Richard M. Day United Kingdom 33 1.1k 0.3× 117 0.2× 159 0.4× 489 1.2× 1.5k 4.2× 101 3.7k
Lori A. Setton United States 73 4.9k 1.4× 318 0.7× 281 0.6× 1.8k 4.4× 3.6k 10.3× 191 14.4k
Yan Liu China 46 1.1k 0.3× 104 0.2× 237 0.5× 1.8k 4.6× 2.9k 8.1× 208 7.3k
Emeka Nkenke Germany 51 2.1k 0.6× 156 0.3× 286 0.6× 1.1k 2.7× 1.8k 5.0× 242 9.1k
Susumu Saito Japan 41 1.6k 0.5× 26 0.1× 398 0.9× 1.4k 3.6× 304 0.9× 204 6.3k
Michael J. Raschke Germany 54 8.8k 2.6× 63 0.1× 3.8k 8.4× 707 1.8× 1.4k 3.9× 513 11.1k
Hiroyuki Hosokawa Japan 42 438 0.1× 1.1k 2.3× 184 0.4× 2.0k 4.9× 349 1.0× 172 5.6k

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-authorship network of co-authors of Daniel O’Connor

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel O’Connor. A scholar is included among the top collaborators of Daniel O’Connor 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 O’Connor. Daniel O’Connor 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
1.
Ben‐Moshe, Noa Bossel, Shelly Hen‐Avivi, Jennifer Hill, et al.. (2025). Salmonella Typhi gut invasion drives hypoxic immune subsets associated with disease outcomes. Nature Communications. 16(1). 6755–6755.
2.
Drury, Ruth, Susana Camara, Irina Chelysheva, et al.. (2024). Multi-omics analysis reveals COVID-19 vaccine induced attenuation of inflammatory responses during breakthrough disease. Nature Communications. 15(1). 3402–3402. 5 indexed citations
3.
Lin, Gu-Lung, Simon B. Drysdale, Matthew D. Snape, et al.. (2024). Targeted metagenomics reveals association between severity and pathogen co-detection in infants with respiratory syncytial virus. Nature Communications. 15(1). 2379–2379. 20 indexed citations
4.
Chelysheva, Irina, Luke Blackwell, Celina Jin, et al.. (2023). Molecular correlates of vaccine-induced protection against typhoid fever. Journal of Clinical Investigation. 133(16). 4 indexed citations
5.
Garrido‐Estepa, Macarena, Daniel O’Connor, Rima Nabbout, et al.. (2023). Targeting shared molecular etiologies to accelerate drug development for rare diseases. EMBO Molecular Medicine. 15(7). e17159–e17159. 19 indexed citations
6.
O’Connor, Daniel, et al.. (2022). Viral vector vaccines. Current Opinion in Immunology. 77. 102210–102210. 74 indexed citations
7.
Pischedda, Sara, Daniel O’Connor, Benjamin P. Fairfax, et al.. (2021). Changes in epigenetic profiles throughout early childhood and their relationship to the response to pneumococcal vaccination. Clinical Epigenetics. 13(1). 29–29. 6 indexed citations
8.
Chelysheva, Irina, Andrew J. Pollard, & Daniel O’Connor. (2021). RNA2HLA: HLA-based quality control of RNA-seq datasets. Briefings in Bioinformatics. 22(5). 10 indexed citations
9.
Drury, Ruth, Andrew J. Pollard, & Daniel O’Connor. (2019). The effect of H1N1 vaccination on serum miRNA expression in children: A tale of caution for microRNA microarray studies. PLoS ONE. 14(8). e0221143–e0221143. 7 indexed citations
10.
Stein, Dan F., et al.. (2016). Gene expression profiles are different in venous and capillary blood: Implications for vaccine studies. Vaccine. 34(44). 5306–5313. 3 indexed citations
11.
12.
O’Connor, Daniel & Andrew J. Pollard. (2013). Characterizing Vaccine Responses Using Host Genomic and Transcriptomic Analysis. Clinical Infectious Diseases. 57(6). 860–869. 27 indexed citations
13.
O’Connor, Daniel. (2005). Research Methods for Students, Academics and Professionals; Information Management and Systems, 2nd ed. Library & Information Science Research. 271–273. 16 indexed citations
14.
Bragdon, Charles R., Murali Jasty, Orhun K. Muratoglu, Daniel O’Connor, & William H. Harris. (2003). Third-body wear of highly cross-linked polyethylene in a hip simulator. The Journal of Arthroplasty. 18(5). 553–561. 92 indexed citations
15.
Muratoglu, O, C.R. Bragdon, Daniel O’Connor, et al.. (1999). Unified wear model for highly crosslinked ultra-high molecular weight polyethylenes (UHMWPE). Biomaterials. 20(16). 1463–1470. 352 indexed citations
16.
Liu, Anmin, Daniel O’Connor, & William H. Harris. (1997). Comparison of cerclage techniques using a hose clamp versus monofilament cerclage wire or cable. The Journal of Arthroplasty. 12(7). 772–776. 15 indexed citations
17.
Jasty, Murali, Daniel O’Connor, Robert M. Henshaw, Timothy P. Harrigan, & William H. Harris. (1994). Fit of the uncemented femoral component and the use of cement influence the strain transfer to the femoral cortex. Journal of Orthopaedic Research®. 12(5). 648–656. 39 indexed citations
18.
O’Connor, Daniel. (1990). Gospel, Raj and Swaraj: The Missionary Years of C.F. Andrews 1904-14. Medical Entomology and Zoology. 3 indexed citations
19.
O’Connor, Daniel. (1982). Evaluating Public Libraries Using Standard Scores: The Library Quotient.. 4(1). 51–70. 1 indexed citations
20.
O’Connor, Daniel, et al.. (1981). Empirical Laws, Theory Construction and Bibliometrics.. Library trends. 30(1). 9–20. 37 indexed citations

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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