Tim O’Connor

3.0k citations
21 papers · 1.9k · 3 hit papers · h-index 16

Impact in

  • Hematology top 2%
    • Acute Myeloid Leukemia Research
  • Genetics top 5%
    • Genetic Associations and Epidemiology
    • Genomics and Rare Diseases
    • Myeloproliferative Neoplasms: Diagnosis and Treatment

Papers in

    • Genetic Associations and Epidemiology 10
    • Genomics and Rare Diseases 1
    • Acute Myeloid Leukemia Research 2

Tim O’Connor

21 papers receiving 1.9k citations

Tim O’Connor's Hit Papers

Clonal haematopoiesis and risk of chronic liver disease 2023 · 151 citations
1510+2+4Years since publication100200300400500

Peers

Tim O’Connor
Comparison fields: 5 of 65
  • Hematology 398
  • Genetics 522
  • Aging 6
  • Cancer Research 48
  • Genetics 30
Replace Snow Xueyan Zhao with:
Snow Xueyan Zhao United States
Fei Fei Wang United States
Larry Bielak United States
Sylvia Smoller United States
Lesley Tinker United States
Susan K Mathai United States
Jody M. Sylvia United States
Seunggeun Shawn Lee United States
Xiaoqi Priscilla Geng United States
Christopher Scheller United States
Tim O’Connor relative to Snow Xueyan Zhao United States Snow Xueyan Zhao's profile →
Citations per field
00.5×1.5×
Snow Xueyan Zhao · 1×
Citations per year

Countries citing papers authored by Tim O’Connor

Since Specialization
Citations

This map shows the geographic impact of Tim 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 Tim 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 Tim O’Connor more than expected).

Fields of papers citing papers by Tim O’Connor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Inherited causes of clonal haematopoiesis in 97,691 whole genomes
Hit paper breakdown →
2020555
2
Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data
Hit paper breakdown →
2022229
3 2020166
4
Clonal haematopoiesis and risk of chronic liver disease
Hit paper breakdown →
2023151
5 2018135
6 2021132
7 201889
8 202375
9 202072
10 202267
11 202247
12 202135
13 202233
14 202231
15 202122
16 202122
17 202116
18 202515
19 202313
20 20257

About Tim O’Connor

Tim O’Connor is a scholar working on Genetics, Hematology, Physiology, Cardiology and Cardiovascular Medicine and Epidemiology, having authored 21 papers that have together received 1.9k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (10 papers), Acute Myeloid Leukemia Research (2 papers), Cardiac electrophysiology and arrhythmias (1 paper), Liver Disease Diagnosis and Treatment (1 paper), Obstructive Sleep Apnea Research (1 paper), Lipoproteins and Cardiovascular Health (1 paper), Asthma and respiratory diseases (1 paper) and Genomics and Rare Diseases (1 paper). The work is most often cited by research in Hematology (398 citations), Genetics (522 citations), Aging (6 citations), Cancer Research (48 citations) and Genetics (30 citations). Tim O’Connor has collaborated with scholars based in United States and Finland. Their work appears in journals such as Nature Communications, Nature Genetics, Nature, Nature Methods and Nature Computational Science.

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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