Dustin Ebert

17.8k total citations · 4 hit papers
8 papers, 4.7k citations indexed

About

Dustin Ebert is a scholar working on Molecular Biology, Genetics and Infectious Diseases. According to data from OpenAlex, Dustin Ebert has authored 8 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Genetics and 0 papers in Infectious Diseases. Recurrent topics in Dustin Ebert's work include Bioinformatics and Genomic Networks (6 papers), Genomics and Phylogenetic Studies (5 papers) and Machine Learning in Bioinformatics (2 papers). Dustin Ebert is often cited by papers focused on Bioinformatics and Genomic Networks (6 papers), Genomics and Phylogenetic Studies (5 papers) and Machine Learning in Bioinformatics (2 papers). Dustin Ebert collaborates with scholars based in United States and China. Dustin Ebert's co-authors include Anushya Muruganujan, Paul D. Thomas, Xiaosong Huang, Huaiyu Mi, Laurent‐Philippe Albou, Tremayne Mushayahama, Xinyu Guo, Juan Pablo Lewinger, Qian Li and Eva Huala and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Nature Protocols.

In The Last Decade

Dustin Ebert

7 papers receiving 4.7k citations

Hit Papers

PANTHER version 14: more genomes, a new PANTHER GO-slim a... 2018 2026 2020 2023 2018 2019 2021 2020 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dustin Ebert United States 6 2.9k 660 564 541 455 8 4.7k
Liis Kolberg Estonia 7 2.8k 1.0× 858 1.3× 435 0.8× 664 1.2× 621 1.4× 9 4.9k
Ivan Kuzmin Estonia 6 2.4k 0.8× 714 1.1× 379 0.7× 532 1.0× 486 1.1× 9 4.1k
Uku Raudvere Estonia 4 2.2k 0.8× 639 1.0× 378 0.7× 515 1.0× 461 1.0× 4 3.9k
Vered Chalifa‐Caspi Israel 32 2.4k 0.8× 857 1.3× 548 1.0× 358 0.7× 598 1.3× 86 4.5k
David J. Arenillas Canada 15 3.7k 1.3× 623 0.9× 434 0.8× 734 1.4× 449 1.0× 28 4.6k
Ananth Prakash United Kingdom 11 3.2k 1.1× 368 0.6× 386 0.7× 327 0.6× 495 1.1× 18 4.9k
Ge Tan Switzerland 27 3.9k 1.3× 811 1.2× 731 1.3× 788 1.5× 746 1.6× 65 6.3k
Ping Liang United States 42 3.7k 1.3× 1.0k 1.6× 898 1.6× 440 0.8× 379 0.8× 151 5.5k
Eran Eden Israel 13 3.6k 1.2× 684 1.0× 231 0.4× 522 1.0× 439 1.0× 25 4.9k
Attila Csordás United Kingdom 17 4.0k 1.4× 496 0.8× 565 1.0× 367 0.7× 543 1.2× 24 6.3k

Countries citing papers authored by Dustin Ebert

Since Specialization
Citations

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

Fields of papers citing papers by Dustin Ebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dustin Ebert. 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 Dustin Ebert. The network helps show where Dustin Ebert may publish in the future.

Co-authorship network of co-authors of Dustin Ebert

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

All Works

8 of 8 papers shown
1.
Ebert, Dustin, et al.. (2024). Enrichment on steps, not genes, improves inference of differentially expressed pathways. PLoS Computational Biology. 20(3). e1011968–e1011968.
2.
Liu, Zhu, Tremayne Mushayahama, Dustin Ebert, et al.. (2022). Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation. Nucleic Acids Research. 50(W1). W57–W65. 2 indexed citations
3.
Thomas, Paul D., Dustin Ebert, Anushya Muruganujan, et al.. (2021). PANTHER: Making genome‐scale phylogenetics accessible to all. Protein Science. 31(1). 8–22. 896 indexed citations breakdown →
4.
Muruganujan, Anushya, Dustin Ebert, Crystal N. Marconett, et al.. (2020). PEREGRINE: A genome-wide prediction of enhancer to gene relationships supported by experimental evidence. PLoS ONE. 15(12). e0243791–e0243791. 13 indexed citations
5.
Mi, Huaiyu, et al.. (2020). PANTHER version 16: a revised family classification, tree-based classification tool, enhancer regions and extensive API. Nucleic Acids Research. 49(D1). D394–D403. 862 indexed citations breakdown →
6.
Zhang, Peifen, Tanya Berardini, Dustin Ebert, et al.. (2020). PhyloGenes: An online phylogenetics and functional genomics resource for plant gene function inference. Plant Direct. 4(12). e00293–e00293. 26 indexed citations
7.
Mi, Huaiyu, Anushya Muruganujan, Xiaosong Huang, et al.. (2019). Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nature Protocols. 14(3). 703–721. 967 indexed citations breakdown →
8.
Muruganujan, Anushya, et al.. (2018). PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Research. 47(D1). D419–D426. 1928 indexed citations breakdown →

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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