Jordan M. Eizenga

5.6k total citations
20 papers, 1.3k citations indexed

About

Jordan M. Eizenga is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Jordan M. Eizenga has authored 20 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 9 papers in Genetics and 6 papers in Plant Science. Recurrent topics in Jordan M. Eizenga's work include Genomics and Phylogenetic Studies (15 papers), Chromosomal and Genetic Variations (6 papers) and Bioinformatics and Genomic Networks (3 papers). Jordan M. Eizenga is often cited by papers focused on Genomics and Phylogenetic Studies (15 papers), Chromosomal and Genetic Variations (6 papers) and Bioinformatics and Genomic Networks (3 papers). Jordan M. Eizenga collaborates with scholars based in United States, United Kingdom and Italy. Jordan M. Eizenga's co-authors include Benedict Paten, Erik Garrison, Adam M. Novak, Miten Jain, Mark Akeson, Hugh E. Olsen, Glenn Hickey, Jouni Sirén, Jonas A. Sibbesen and Jean Monlong and has published in prestigious journals such as Science, Bioinformatics and Nature Methods.

In The Last Decade

Jordan M. Eizenga

20 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jordan M. Eizenga United States 13 1.0k 434 326 121 107 20 1.3k
Weichun Huang United States 17 1.5k 1.5× 419 1.0× 369 1.1× 223 1.8× 224 2.1× 26 1.9k
Pegah Tootoonchi Afshar United States 8 997 1.0× 380 0.9× 210 0.6× 347 2.9× 54 0.5× 12 1.5k
Florian Hahne United States 10 1.1k 1.1× 201 0.5× 112 0.3× 153 1.3× 71 0.7× 17 1.6k
Ilan Wapinski United States 15 1.6k 1.5× 522 1.2× 337 1.0× 88 0.7× 237 2.2× 38 2.0k
Natalia Maltsev United States 18 1.7k 1.7× 373 0.9× 157 0.5× 83 0.7× 188 1.8× 47 2.0k
Andrew Yates United Kingdom 14 1.1k 1.1× 317 0.7× 321 1.0× 126 1.0× 93 0.9× 30 1.6k
W. James Kent United States 4 1.2k 1.2× 299 0.7× 218 0.7× 188 1.6× 200 1.9× 4 1.7k
Preston W. Estep United States 10 2.2k 2.2× 362 0.8× 251 0.8× 73 0.6× 47 0.4× 16 2.5k
Cédric Chauve Canada 20 802 0.8× 440 1.0× 386 1.2× 43 0.4× 76 0.7× 78 1.1k
Mary Mangan United States 10 1.1k 1.1× 247 0.6× 167 0.5× 135 1.1× 168 1.6× 13 1.6k

Countries citing papers authored by Jordan M. Eizenga

Since Specialization
Citations

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

Fields of papers citing papers by Jordan M. Eizenga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jordan M. Eizenga. 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 Jordan M. Eizenga. The network helps show where Jordan M. Eizenga may publish in the future.

Co-authorship network of co-authors of Jordan M. Eizenga

This figure shows the co-authorship network connecting the top 25 collaborators of Jordan M. Eizenga. A scholar is included among the top collaborators of Jordan M. Eizenga 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 Jordan M. Eizenga. Jordan M. Eizenga 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.
Sirén, Jouni, Glenn Hickey, Jordan M. Eizenga, et al.. (2024). Personalized pangenome references. Nature Methods. 21(11). 2017–2023. 9 indexed citations
2.
Taylor, Dylan J., Jordan M. Eizenga, Katharine M. Jenike, et al.. (2024). Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References. Annual Review of Genomics and Human Genetics. 25(1). 77–104. 9 indexed citations
3.
Marco‐Sola, Santiago, Jordan M. Eizenga, Andrea Guarracino, et al.. (2023). Optimal gap-affine alignment in O ( s ) space. Bioinformatics. 39(2). 33 indexed citations
4.
Sibbesen, Jonas A., Jordan M. Eizenga, Adam M. Novak, et al.. (2023). Haplotype-aware pantranscriptome analyses using spliced pangenome graphs. Nature Methods. 20(2). 239–247. 31 indexed citations
5.
Markello, Charles, Charles Huang, Álex Rodríguez, et al.. (2022). A complete pedigree-based graph workflow for rare candidate variant analysis. Genome Research. 32(5). 893–903. 5 indexed citations
6.
Sirén, Jouni, Jean Monlong, Xian Chang, et al.. (2021). Pangenomics enables genotyping of known structural variants in 5202 diverse genomes. Science. 374(6574). abg8871–abg8871. 165 indexed citations
7.
Shafin, Kishwar, Trevor Pesout, Pi-Chuan Chang, et al.. (2021). Haplotype-aware variant calling with PEPPER-Margin-DeepVariant enables high accuracy in nanopore long-reads. Nature Methods. 18(11). 1322–1332. 133 indexed citations
8.
Vivian, John, Jordan M. Eizenga, Holly C. Beale, Olena M. Vaske, & Benedict Paten. (2020). Bayesian Framework for Detecting Gene Expression Outliers in Individual Samples. JCO Clinical Cancer Informatics. 4(4). 160–170. 9 indexed citations
9.
Eizenga, Jordan M., Adam M. Novak, Flavia Villani, et al.. (2020). Efficient dynamic variation graphs. Bioinformatics. 36(21). 5139–5144. 13 indexed citations
10.
Hickey, Glenn, David N. Heller, Jean Monlong, et al.. (2020). Genotyping structural variants in pangenome graphs using the vg toolkit. Genome biology. 21(1). 35–35. 156 indexed citations
11.
Eizenga, Jordan M., Adam M. Novak, Jonas A. Sibbesen, et al.. (2020). Pangenome Graphs. Annual Review of Genomics and Human Genetics. 21(1). 139–162. 135 indexed citations
12.
Chang, Xian, Jordan M. Eizenga, Adam M. Novak, Jouni Sirén, & Benedict Paten. (2020). Distance indexing and seed clustering in sequence graphs. Bioinformatics. 36(Supplement_1). i146–i153. 9 indexed citations
13.
Schultz, Darrin T., Jordan M. Eizenga, Russell Corbett‐Detig, et al.. (2020). Conserved novel ORFs in the mitochondrial genome of the ctenophore Beroe forskalii. PeerJ. 8. e8356–e8356. 16 indexed citations
14.
Rahav, Eyal, Natalia Belkin, Peng Xian, et al.. (2019). Aerosol Microbiome over the Mediterranean Sea Diversity and Abundance. Atmosphere. 10(8). 440–440. 30 indexed citations
15.
Haussler, David, et al.. (2018). A Flow Procedure for Linearization of Genome Sequence Graphs. Journal of Computational Biology. 25(7). 664–676. 2 indexed citations
16.
Paten, Benedict, et al.. (2018). Superbubbles, Ultrabubbles, and Cacti. Journal of Computational Biology. 25(7). 649–663. 35 indexed citations
17.
Eizenga, Jordan M., et al.. (2017). Modelling haplotypes with respect to reference cohort variation graphs. Bioinformatics. 33(14). i118–i123. 8 indexed citations
18.
Paten, Benedict, Adam M. Novak, Jordan M. Eizenga, & Erik Garrison. (2017). Genome graphs and the evolution of genome inference. Genome Research. 27(5). 665–676. 165 indexed citations
19.
Vohr, Samuel H., et al.. (2017). A phylogenetic approach for haplotype analysis of sequence data from complex mitochondrial mixtures. Forensic Science International Genetics. 30. 93–105. 32 indexed citations
20.
Jain, Miten, et al.. (2017). Mapping DNA methylation with high-throughput nanopore sequencing. Nature Methods. 14(4). 411–413. 325 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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