Jeff O’Connell

6.5k total citations · 1 hit paper
15 papers, 944 citations indexed

About

Jeff O’Connell is a scholar working on Genetics, Plant Science and Epidemiology. According to data from OpenAlex, Jeff O’Connell has authored 15 papers receiving a total of 944 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Genetics, 5 papers in Plant Science and 2 papers in Epidemiology. Recurrent topics in Jeff O’Connell's work include Genetic and phenotypic traits in livestock (9 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers) and Genetics and Plant Breeding (5 papers). Jeff O’Connell is often cited by papers focused on Genetic and phenotypic traits in livestock (9 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers) and Genetics and Plant Breeding (5 papers). Jeff O’Connell collaborates with scholars based in United States, Italy and Canada. Jeff O’Connell's co-authors include Robert D. Schnabel, Michael P. Heaton, Curtis P. Van Tassell, M. F. Allan, Timothy P. L. Smith, S. S. Moore, Lakshmi K. Matukumalli, Jeremy F. Taylor, Tad S. Sonstegard and P.M. VanRaden and has published in prestigious journals such as PLoS ONE, The American Journal of Human Genetics and Journal of Dairy Science.

In The Last Decade

Jeff O’Connell

14 papers receiving 918 citations

Hit Papers

Development and Characterization of a High Density\nSNP G... 2009 2026 2014 2020 2009 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Development and Characterization of a High Density\nSNP Genotyping Assay for Cattle
    2009 752 citations Lakshmi K. Matukumalli, Robert D. Schnabel et al. Insecta mundi profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeff O’Connell United States 9 854 259 189 173 123 15 944
Matthew McClure United States 18 806 0.9× 151 0.6× 198 1.0× 195 1.1× 161 1.3× 34 961
Pascal Croiseau France 17 782 0.9× 263 1.0× 193 1.0× 137 0.8× 86 0.7× 31 922
Peipei Ma China 19 882 1.0× 336 1.3× 171 0.9× 286 1.7× 152 1.2× 55 1.1k
Zhenshuang Tang China 8 556 0.7× 377 1.5× 82 0.4× 141 0.8× 214 1.7× 13 900
Christine A. Ford New Zealand 7 1.2k 1.4× 329 1.3× 241 1.3× 249 1.4× 157 1.3× 8 1.4k
Srinivas R. Kata United States 15 838 1.0× 263 1.0× 100 0.5× 87 0.5× 298 2.4× 21 1.0k
Danny Wagenaar Belgium 7 840 1.0× 302 1.2× 62 0.3× 125 0.7× 233 1.9× 8 953
A. Nejati‐Javaremi Iran 17 1.0k 1.2× 217 0.8× 400 2.1× 168 1.0× 134 1.1× 62 1.3k
Myriam Mni Belgium 7 1.5k 1.8× 486 1.9× 229 1.2× 247 1.4× 205 1.7× 9 1.7k
Joanna Szyda Poland 19 956 1.1× 268 1.0× 304 1.6× 191 1.1× 283 2.3× 86 1.2k

Countries citing papers authored by Jeff O’Connell

Since Specialization
Citations

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

Fields of papers citing papers by Jeff O’Connell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeff O’Connell

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

All Works

15 of 15 papers shown
1.
Bruce, Heather, Peter Kochunov, Joshua Chiappelli, et al.. (2021). Genetic versus stress and mood determinants of sleep in the Amish. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 186(2). 113–121. 2 indexed citations
2.
Bagheri, Minoo, Hemant K. Tiwari, Anarina L. Murillo, et al.. (2020). A lipidome-wide association study of the lipoprotein insulin resistance index. Lipids in Health and Disease. 19(1). 153–153. 7 indexed citations
3.
Null, D.J., et al.. (2019). Using the ARS-UCD1.2 reference genome in U.S. evaluations.. 30–34. 10 indexed citations
4.
VanRaden, P.M., et al.. (2018). Including feed intake data from U.S. Holsteins in genomic prediction. Proceedings of the World Congress on Genetics Applied to Livestock Production. 125. 9 indexed citations
5.
Weller, J.I., Derek M. Bickhart, G.R. Wiggans, et al.. (2018). Determination of quantitative trait nucleotides by concordance analysis between quantitative trait loci and marker genotypes of US Holsteins. Journal of Dairy Science. 101(10). 9089–9107. 18 indexed citations
6.
VanRaden, P.M. & Jeff O’Connell. (2018). Validating Genomic Reliabilities and Gains from Phenotypic Updates. 3 indexed citations
7.
VanRaden, P.M., G Spangler, Jun Jiang, et al.. (2017). 188 Ability to genotype differing variants with arrays vs. whole genome sequencing. Journal of Animal Science. 95(suppl_4). 93–93.
8.
Fuchs, Dietmar, Christopher A. Lowry, Sarah H. Stephens, et al.. (2017). Heritability of plasma neopterin levels in the Old Order Amish. Journal of Neuroimmunology. 307. 37–41. 5 indexed citations
9.
Wojczynski, Mary K., Laurence D. Parnell, Toni I. Pollin, et al.. (2015). Genome-wide association study of triglyceride response to a high-fat meal among participants of the NHLBI Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). Metabolism. 64(10). 1359–1371. 26 indexed citations
10.
Devan, William J., Mike A. Nalls, Silvia Parolo, et al.. (2015). Heritability of young‐ and old‐onset ischaemic stroke. European Journal of Neurology. 22(11). 1488–1491. 9 indexed citations
11.
Sun, Chuanyu, P.M. VanRaden, John B. Cole, & Jeff O’Connell. (2014). Increasing Predictive Ability Using Dominance in Genomic Selection. Proceedings of the World Congress on Genetics Applied to Livestock Production. 291. 1 indexed citations
12.
VanRaden, P.M., et al.. (2013). Mating programs including genomic relationships and dominance effects. Journal of Dairy Science. 96(12). 8014–8023. 66 indexed citations
13.
Matukumalli, Lakshmi K., Robert D. Schnabel, Jeremy F. Taylor, et al.. (2009). Development and Characterization of a High Density\nSNP Genotyping Assay for Cattle. Insecta mundi. 752 indexed citations breakdown →
14.
Matukumalli, Lakshmi K., Robert D. Schnabel, Jeremy F. Taylor, et al.. (2009). Development and Characterization of a High Density SNP Genotyping Assay for Cattle. PLoS ONE. 4(4). e5350–e5350. 27 indexed citations
15.
Gillanders, Elizabeth M., John V. Pearson, Alexa J.M. Sorant, et al.. (2006). The Value of Molecular Haplotypes in a Family-Based Linkage Study. The American Journal of Human Genetics. 79(3). 458–468. 9 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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