Rob Egan

8.7k total citations · 3 hit papers
17 papers, 4.6k citations indexed

About

Rob Egan is a scholar working on Molecular Biology, Ecology and Artificial Intelligence. According to data from OpenAlex, Rob Egan has authored 17 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Ecology and 5 papers in Artificial Intelligence. Recurrent topics in Rob Egan's work include Genomics and Phylogenetic Studies (15 papers), Microbial Community Ecology and Physiology (7 papers) and Algorithms and Data Compression (5 papers). Rob Egan is often cited by papers focused on Genomics and Phylogenetic Studies (15 papers), Microbial Community Ecology and Physiology (7 papers) and Algorithms and Data Compression (5 papers). Rob Egan collaborates with scholars based in United States and China. Rob Egan's co-authors include Zhong Wang, Dongwan Kang, Jeff Froula, Edward Kirton, Feng Li, Hong An, Gary P. Schroth, Matthias Hess, Alexander Sczyrba and Douglas S. Clark and has published in prestigious journals such as Science, Nature Communications and Bioinformatics.

In The Last Decade

Rob Egan

17 papers receiving 4.6k citations

Hit Papers

align trajectories

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.

MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies

2019 2.1k citations Dongwan Kang, Feng Li et al. PeerJ profile →
MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities

2015 1.3k citations Dongwan Kang, Jeff Froula et al. PeerJ profile →
Metagenomic Discovery of Biomass-Degrading Genes and Genomes from Cow Rumen

2011 950 citations Matthias Hess, Alexander Sczyrba et al. Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rob Egan United States	11	2.8k	2.2k	632	581	470	17	4.6k
Alexander Sczyrba Germany	34	2.7k 1.0×	1.8k 0.8×	327 0.5×	409 0.7×	455 1.0×	85	4.4k
Matthias Hess United States	24	2.1k 0.7×	1.4k 0.6×	356 0.6×	318 0.5×	481 1.0×	58	4.0k
Chi-Man Liu Hong Kong	8	3.6k 1.3×	2.8k 1.3×	1.1k 1.8×	615 1.1×	1.0k 2.2×	13	7.4k
Noha H. Youssef United States	36	2.5k 0.9×	2.2k 1.0×	1.6k 2.5×	698 1.2×	888 1.9×	95	5.7k
Aaron J. Mussig Australia	6	3.9k 1.4×	3.4k 1.6×	890 1.4×	873 1.5×	617 1.3×	11	6.4k
Maria Chuvochina Australia	20	4.7k 1.7×	3.9k 1.8×	730 1.2×	1.0k 1.8×	672 1.4×	50	7.2k
Dongwan Kang United States	14	2.9k 1.0×	2.0k 0.9×	596 0.9×	563 1.0×	439 0.9×	18	4.7k
Anja Poehlein Germany	37	2.3k 0.8×	1.2k 0.5×	462 0.7×	470 0.8×	563 1.2×	264	4.6k
Konstantinos Mavromatis United States	32	3.7k 1.3×	2.4k 1.1×	402 0.6×	402 0.7×	894 1.9×	64	5.5k
Marcel Huntemann United States	28	3.6k 1.3×	2.9k 1.4×	402 0.6×	510 0.9×	1.1k 2.3×	93	5.7k

Countries citing papers authored by Rob Egan

Since Specialization

Citations

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

Fields of papers citing papers by Rob Egan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rob Egan

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

All Works

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17 of 17 papers shown

Egan, Rob, et al.. (2023). Designing Efficient SIMD Kernels for High Performance Sequence Alignment. 10. 167–176. 1 indexed citations

Barnett, Samuel E., Rob Egan, Brian Foster, Emiley A. Eloe‐Fadrosh, & Daniel H. Buckley. (2023). Genomic Features Predict Bacterial Life History Strategies in Soil, as Identified by Metagenomic Stable Isotope Probing. mBio. 14(2). e0358422–e0358422. 17 indexed citations

Chovatia, Mansi, Rob Egan, Guifen He, et al.. (2023). Integrating chromatin conformation information in a self-supervised learning model improves metagenome binning. PeerJ. 11. e16129–e16129. 1 indexed citations

Riley, Robert, Robert M. Bowers, Antônio Pedro Camargo, et al.. (2023). Terabase-Scale Coassembly of a Tropical Soil Microbiome. Microbiology Spectrum. 11(4). e0020023–e0020023. 11 indexed citations

Egan, Rob, et al.. (2022). Persistent memory as an effective alternative to random access memory in metagenome assembly. BMC Bioinformatics. 23(1). 513–513. 3 indexed citations

Hofmeyr, Steven, Rob Egan, Nan Ding, et al.. (2021). Accelerating large scale de novo metagenome assembly using GPUs. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–11. 2 indexed citations

Yelick, Katherine, Aydın Buluç, Ariful Azad, et al.. (2020). The parallelism motifs of genomic data analysis. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 378(2166). 20190394–20190394. 13 indexed citations

Hofmeyr, Steven, Rob Egan, Evangelos Georganas, et al.. (2020). Terabase-scale metagenome coassembly with MetaHipMer. Scientific Reports. 10(1). 10689–10689. 31 indexed citations

LaPierre, Nathan, Rob Egan, Wei Wang, & Zhong Wang. (2019). De novo Nanopore read quality improvement using deep learning. BMC Bioinformatics. 20(1). 552–552. 10 indexed citations

10.

Kang, Dongwan, Feng Li, Edward Kirton, et al.. (2019). MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ. 7. e7359–e7359. 2065 indexed citations breakdown →

11.

Roux, Simon, et al.. (2017). Ecogenomics of virophages and their giant virus hosts assessed through time series metagenomics. Nature Communications. 8(1). 858–858. 91 indexed citations

12.

Georganas, Evangelos, Rob Egan, Steven Hofmeyr, et al.. (2017). MerBench. 1–4. 4 indexed citations

13.

Georganas, Evangelos, Aydın Buluç, Jarrod Chapman, et al.. (2015). HipMer. eScholarship (California Digital Library). 1–11. 48 indexed citations

14.

Kang, Dongwan, Jeff Froula, Rob Egan, & Zhong Wang. (2015). MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 3. e1165–e1165. 1274 indexed citations breakdown →

15.

Clark, Scott, Rob Egan, Peter I. Frazier, & Zhong Wang. (2013). ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies. Bioinformatics. 29(4). 435–443. 121 indexed citations

16.

Samak, Taghrid, Rob Egan, Brian Bushnell, et al.. (2013). Automatic Outlier Detection for Genome Assembly Quality Assessment. 45–52. 1 indexed citations

17.

Hess, Matthias, Alexander Sczyrba, Rob Egan, et al.. (2011). Metagenomic Discovery of Biomass-Degrading Genes and Genomes from Cow Rumen. Science. 331(6016). 463–467. 950 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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